1. Овој сајт користи колачиња неопходни за неговото функционирање. Ако продолжиш да го користиш, значи се согласуваш со нашата употреба на колачиња. Прочитај повеќе.

Фемински клуб на читатели – nonfiction (The Idiot Brain – Dean Burnett)

Дискусија во 'Литература и уметност' започната од DAngel, 16 октомври 2020.

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Која од следниве книги би сакале да ја читаме?

Анкетата е затворена на 19 ноември 2022.
  1. Come as You Are: The Surprising New Science that Will Transform Your Sex Life — Emily Nagoski

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  2. The Language of Emotions: What Your Feelings Are Trying to Tell You — Karla McLaren

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  3. The Idiot Brain: A Neuroscientist Explains What Your Head is Really Up To — Dean Burnett

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  4. Why We Sleep: Unlocking the Power of Sleep and Dreams — Matthew Walker

    42,9%
  5. Choice and Consequence — Thomas C. Shelling

    28,6%
  6. Toxic Childhood Stress: The Legacy of Early Trauma and How to Heal — Nadine Burke Harris

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  1. pdb123

    pdb123 Популарен член

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    Воопшто не ни помислив дека опашката би можела да е метафора за dick sizes :rofl:. Додуша, сè уште мислам дека не му било тоа намерата, бидејќи веројатно животните имаат други критериуми за размножување и не им е важна големината на половиот орган како што ни е нам :D.

    Ова за мене беа клучните делови за сексуална селекција:

    Although genes for female preference only express themselves in female behaviour, nevertheless they are present in the bodies of males too. And by the same token, genes for male tail length are present in the bodies of females, whether or not they express themselves in females.

    Males with 4-inch tails might well pull the female birds, but the price the males would pay is their less-efficient flight, greater energy costs and greater vulnerability to predators. We can express this by saying that there is a utilitarian optimum tail length, which is different from the sexually selected optimum: an ideal tail length from the point of view of ordinary useful criteria; a tail length that is ideal from all points of view apart from attracting females.

    Every time a male is chosen because of his long tail, not only are genes for long tails being chosen. At the same time, because of the 'togetherness' coupling, genes for preferring long tails are also being chosen. What this means is that genes that make females choose male tails of a particular length are, in effect, choosing copies of themselves.

    Мислам дека секогаш ќе ме мачат тие, како што рече Лела, кокошка-јајце моменти, и во однос на ова и во однос на претходното поглавје :drunk:. Сакам да знам кое е прво :@.

    Знам како ќе звучи ова, ама... додека го читав поглавјето, се чувствував како женскиот род да е божество што си лабави и чека да се појават peasants што ќе ѝ ги исполнат критериумите :rofl::devil:.
    Се гогласувам дека градуализмот е најлогично решение, и тоа тој со континуирано променлива брзина. Имав чувство дека пуктуалистите доста го фрустрираат и мислам дека 5000000 пати нагласи дека се градуалисти :rofl:.

    Oh, that sweet diss at us humans:

    Obviously a long time by human standards, but human standards aren't relevant.

    Ова е храбра изјава :D:

    Everyone that is not a saltationist is a gradualist, and this includes Eldredge and Gould, however they may choose to describe themselves.
    Мислам дека овде немаше потреба толку многу да се раздробува што значи хиерархиска класификација, бидејќи е многу јасен самиот поим; доволна плус информација беше дека нема преклопување на животните, поточно секое животно припаѓа на точно една гранка.

    Ми се чини дека ова ми беше исто така добро сумирање на претходните поглавја:

    At this point I cannot resist drawing attention to the irony in the challenge that creationists are fond of hurling at evolutionists: 'Produce your intermediates. If evolution were true, there should be animals that are half way between a cat and a dog, or between a frog and an elephant. But has anyone ever seen a frelephant?' I have been sent creationist pamphlets that attempt to ridicule evolution with drawings of grotesque chimeras, horse hindquarters grafted to a dog's front end, for instance. The authors seem to imagine that evolutionists should expect such intermediate animals to exist. This not only misses the point, it is the precise antithesis of the point. One of the strongest expectations the theory of evolution gives us is that intermediates of this kind should not exist.

    Ова го спомена некаде и во претходното поглавје, но не можев да го најдам, ама кога го прочитав, I felt that (lalala):

    To make the point most forcibly, think again of a hypothetically 'kind' nature, providing us with a complete fossil record, with a fossil of every animal that ever lived. When I introduced this fantasy in the previous chapter, I mentioned that from one point of view nature would actually be being unkind.

    Смешно ми падна ова кога почнуваше да ги објаснува различните таксономни училишта, како за деца кои само се караат да зборува, како и крајот :rofl::

    The following brief account of taxonomic schools of thought will probably annoy some members of those schools, but no more than they habitually infuriate each other so no undue harm will be done.

    Now I'd better go out and dig the garden, or something.

    (Јас, после завршувањето на овој вечен пост :tmi::drunk:)
    Се прашувам дали ламаркизмот е толку распространета теорија што посвети најмногу внимание на неа, иако ми изгледаше како тој да мисли дека таа е најапсурдна.

    Понатаму, добар ми беше делот за непроизволноста на мутацијата:

    The first respect in which mutation is non-random is this. Mutations are caused by definite physical events; they don't just spontaneously happen.

    Second, not all genes in any species are equally likely to mutate. Every locus on the chromosomes has its own characteristic mutation rate.


    Third, at each locus on the chromosomes, whether it is a hot spot or not, mutations in certain directions can be more likely than mutations in the reverse direction.

    Mutation is non-random in the sense that it can only make alterations to existing processes of embryonic development. It cannot conjure, out of thin air, any conceivable change that selection might favour.

    Ова исто беше добра поента:

    The creationist, whether a naive Bible-thumper or an educated bishop, simply postulates an already existing being of prodigious intelligence and complexity. If we are going to allow ourselves the luxury of postulating organized complexity without offering an explanation, we might as well make a job of it and simply postulate the existence of life as we know it!

    Исто така, морам да кажам дека кога ја читав карикатурата на Дарвинистот, доста ми звучеше на сè претходно што беше кажано и си помислив дека сè досега погрешно сум сфатила, штом тој се смета за карикатура. При крајот од дијалогот, како и по следственото објаснување ги воочив разликите и не знам за вас, ама навистина е тенка линијата, т.е. разликата е во деталите, а генералната слика е доста слична. Можеби ми треба време да ги сварам сите концепти, па лесно да воочувам вакви работи.

    Сега ќе се обидам да одговорам на вашите постови; се надевам дека добро ги сфаќам прашањата :D.

    Веројатно мислиш на големина, текстура итн на објектите. Мислам дека звучниот бран поинаку се рефлектира во зависност од повеќе параметри, меѓу кои и овие, па така би можеле отприлика да дефинираат за каков објект се работи.

    Не мислам дека има супериорен еволуциски синџир, мислам дека такво нешто е незамисливо моментално за нас. Апсурдно ќе звучи ова, но кога би постоел таков синџир, евентуално „целта“ би му била да настане промена на нашата планета или на останатите планети (во нашиот Сончев систем), но и ова е многу голем stretch. Немам идеја што друго би му била „целта“ на тој синџир, не остана ништо друго што може да еволуира кај нас, или барем јас не го гледам.

    Исто така, мислам дека не можеме да ја процениме нашата сложеност, бидејќи како што кажа и ти, се работи за бесконечен процес на еволуирање; не можеме перманентно да се поставиме на една точка од скалата на сложеност, бидејќи таа вечно се менува. Сега сме на врвот на сложеноста, но можеби за 1000 години ќе сме „полусложени“.

    Претпоставувам дека не можеме да фиксираме почеток. Или не можеме да ја замислиме алтернативата бидејќи сè во нашиот живот е карактеризирано со почеток и крај. Но мислам дека ова веќе навлегува во дискусија од аспект на физиката/философијата.

    Не можам да најдам каде точно се зборува за ова, ама дали можеби задоволителен одговор би бил дека не е проблемот во „подобрувањето“, туку во брзината со која се менува ногата на коњот (1 mm/генерација) - или било која друга промена - не е константна, туку има континуирано променлива брзина, па затоа го отфрла тоа?

    Претпоставувам дека ова е така поради тоа што напишал други книги, нели меѓу твоите предложени имаше уште една од него поврзана со Бог. Можеби таму повеќе го адресира проблемот со Бог.

    Еј, баш интересно (иако не се сеќавам каде спомена memes)! :D

    Што се однесува до теоријата на неутрализмот и статијата што ја постави @f.girl, ми звучи логичен делот со птиците, како што веќе напомена. Сепак, мислам дека е тешко да се дефинира што е голема, а што мала популација, особено што најверојатно не знаеме колкава била таа популација во минатото (или може да дознаеме?). Мислам дека тешко би било да се направи разлика меѓу тоа дали популацијата се намалува/исчезнува како резултат на произволен настан, или можеби ние ја имаме „честа“ да се погодиме во времето кога природната селекција ги „истребува“ тие животни. Можеби па ова е всушност манифестација на природната селекција, а нам ни изгледа произволно. Не знам, можеби со ова што го пишувам всушност и се согласувам со теоријата на неутрализмот, но не можам повеќе да размислувам, ми зовре мозокот :drunk:(poolparty)(hollest)

    Ако издржавте да ги прочитате моите постови, не знам дали да ви честитам или да ве сожалам; еве ви едно коктелче од мене, како нешто што одговара во двете ситуации: :d:. Имајќи предвид дека веројатно нема што (толку) многу да се искоментира на ова што го пишав, би прашала: која е следната книга? Со оглед на тоа што не се предложија други книги, ќе кажам која (прва) би ја читала од тие книги што ги предложив јас: The Death of Expertise: The Campaign Against Established Knowledge and Why it Matters - Tom Nichols (hollest).


    П.С. Уште еднаш да ви се извинам за должината на мислењето. Го копирав постот во Word за да избројам карактери, т.е. да знам од каде до каде да биде еден пост, па друг, и испадна дека постот ми е 8 и пол страни :tmi::sweat:. Нема шанси да бришам сега, не ни препрочитувам што сум пишала, ако сакате не читајте :rofl:.
     
    Последна измена: 13 јануари 2021
    На Lella му/ѝ се допаѓа ова.
  2. sweet-cherry

    sweet-cherry Форумски идол

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    Ќе има книга за месецов или ќе бираме за фебруари? :D
    Од мене предлог a brief history of time - Stephen hawking и blink-malcolm gladwell
     
  3. pdb123

    pdb123 Популарен член

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    Јас сум за да има книга за овој месец, меѓутоа не знам дали има доволно време и за да изгласаме нова книга (нели требаше на крајот од декември додека се дискутира да го направиме тоа, иако се оддолжи работата...), да ја прочитаме (зависи од тежина што не ја знаеме однапред) и да ја издискутираме 4-7 дена до крај на јануари, освен ако не е апла јасно дека повеќето (што не знаеме колку се на број) се за иста книга и уште од утре-задутре да почнеме да читаме... Мислам дека @f.girl полага испити овој месец, па не знам дали ќе има време да прочита, т.е. да учествува овој месец. За другите освен Чери (и верувам Лела и Дангел) не знам.
     
  4. Lella

    Lella Форумски идол

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    @pdb123 Ако пишуваш со овој интензитет баш убаво ќе се збогати темава. Јас одма ги ,,голтнав" твоите две мислења и уживав во секој момент. :D Многу сакам да читам некој како си ги остава мислите во некој текст надолго и нашироко, така што од мене имаш поддршка да пишуваш колку ти душа сака. 8-| Барем на оваа тема не сме ограничени со кратки рецензии. :lol:

    Јас мислам дека на Докинс многу му се допаднаа неговите биоморфи. :D Па ситуацијата испадна он ни ги покажува како возбудено дете на show and tell, а ние сме ко...

    [​IMG]

    Во секој случај, Докинс е стварно темелен и не штеди на зборови и време, гледам како за некои читатели би било тоа фрустрирачки. Ќе беше и за мене ако не се навраќаше на крај да повтори зошто е релевантно, ама за среќа на крај секогаш без исклучок повторуваше и тоа ми даваше илузија на убаво свиткано пакетче. :D

    Токму така. Дури би рекла дека таа глава, а и некои други (како првата на пример) беа љубовно писмо до Евангелосите на светов, баш од причина што тие се фатени за тинчењата што викаш како слеп за стап. Оваа глава за веројатностите всушност функционира како prebuttal на сè што може бог-армијата да му одговори на Докинс. Ако ја прочиташ книгата на Евангелос (за жал I took one for the team и ја прочитав) ќе го видиш баш сево ова што Докинс го поби. Мораше да ситничари до толку за да може на крај да каже океј, го тргнавме тоа од пат? Може сега да збориме за природна селекција и долгоопашни птици на раат? :D

    И мене ова ми падна во очи и планирав да го потенцирам во минатите мислења ама заборавив. :D Се гледа низ читањето дека главава е последица на долги измачувачки препирки меѓу него и пунктуалистите. Особено се приметувше ви оние subtle shade моменти кои ги цитира ти.
    Што би рекле на тамблр, things are heating up in the evolution fandom. :D

    Да, тенка е линијата меѓу еволуционист и карикатура, и баш поради ова сметам дека е одлично што Докинс одвои време да го расчисти тој проблем. Еден голем проблем кај негирачите на еволуцијата е недоразбирањето што произлегува од нејзината мисрепрезентација. Многу луѓе уште мислат дека еволуцијата е само мајмуни мајмуни мајмуни. Не знам на кој би ја префрлила вината за ова, на креационистите ли, на училиштата ли, или пак на општеството како целина што сè уште не разграничува мит од наука. Првично не ми беа интересни последниве глави каде почна да зборува за луѓе и школи, наместо за лилјаци и мутирани риби, ама in hindsight, потребно е. Особено во книга што првично има за цел да ја побие заблудата дека животот ,,бара" интелигентен часовничар.

    Хмм, можеби е само во изборот на зборови што го употреби, ама мислам дека нема простор да збориме за цел кога се работи за еволуција. Бидејќи нели природата е слепа, не цели кон ништо, туку во неа пасивно преживуваат оние што победуваат во кршењето на раце како што вели Докинс. На сличен начин, можеби нашите компјутери еден ден ќе го почнат тоа кршење раце со нас, и who's to say дека нема да победат. Ама ова веќе е прилично длабока сај-фај територија. :D

    Да, ова звучи сосема логично. Се навратив сега на моето прашање баш и видов дека во иста реченица сум спомнала ,,во секоја генерација" без да го приметам ова. Еве баш затоа е добро што можеме да ја дискутираме книгава напред назад. Ќе ми останеше заблудава неразјаснета. :lol:

    Најверојатно, да. Сепак, тоа го кажав бидејќи книгава ја има напишано како одговор на Евангелос-реториката: поради сложеноста на животот мора да постои интелигентен дизајнер. Во суштина целата книга вели не мора да постои интелигентен дизајнер. Може, ама не мора. Во секој случај, уште не сум и' седнала на God Delusion, само и' се восхитувам од далечина. :wasntme:

    Инаку многу ми се допадна што ја коментираше книгава глава по глава, а и цитатите беа одличен додаток. Баш се потсетив на некои делови, а и некои од нив видов дека се стварно впечатливи, а не се ни сеќавам дека сум ги прочитала.

    Инаку, за следна книга, би рекла да читаме нешто не толку поврзано со наука. Книгата на pdb ми стои интересна, би се нафатила да ја читам, иако не сум читала од телефон досега. 8-| А секако, и за Blink сум тука, ми стои на полица одма до Часовничарот, и онака евентуално ќе ја прочитам. Предлагам да го истераме месецов со оваа, бидејќи ако не се лажам и SWAG и Ејнџл ја имаат прочитано, па може ќе допишат уште нешто. Моите колоквиуми завршуваат за околу една недела, после сум слободна за читање. Викам нова да почнеме од февруари лагано, да не ја бркаме низ јануари, кој стигнал, кој не стигнал да прочита. :D

    Во анкетата засега ќе одат The Death of Expertise, Blink и A Brief History of Time. Може уште некоја да се предложи пред да ја поставам.
     
    На pdb123 му/ѝ се допаѓа ова.
  5. pdb123

    pdb123 Популарен член

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    Не вели два пати :D:devil:.
    Да бидам реална, не сум се сретнала со толку хардкор верници во животот, а и никогаш религијата не ми била „турана во врат“ за да се заинтересирам за неа до тој степен; би рекла дури и дека сум религиски неписмена :?:. Од денешна перспектива, би сакала повеќе да научам за религиите како појава, за „приказните“ поврзани со нив, чисто колку да имам подетална претстава, повеќе од културолошки аспект.
    Би ја барала вината во училиштата. Мислам дека треба да се посвети поголемо внимание и признание, исто како што на пример, во географија се посветува на теоријата на тектонски плочи (додуша не се сеќавам колку :D, ама мислам дека некаде се зборува; барем ние на факултет ги споменувавме во однос на потеклото на земјотрес). Да, двете се теории и доказите за нив можеби не се толку бројни како за други појави, но сепак се општоприфатени и моментално двете науки како почетна точка ги имаат нив.
    Да, во право си. Објективно сфаќам дека е така, иако (ми) треба вежбање околу тоа при изразување да не тргнувам од субјективниот аспект: „Што би направила јас? Што мене ми е (не)логичен чекор?“. Претпоставувам дека (ми)е тешко да се вмрежи во главата дека останатите работи/појави не функционираат онака како што функционираме ние. Исто како што од социјален аспект ни е потешко да се ставиме во туѓа кожа и да гледаме низ туѓи очи. Полесно е вака кога го читаш, бидејќи има смисла, но мислам дека е потешко да го применуваш (во разговор) освен ако не си доволно „навлезен“ во (шемата на) темата; во спротивно, ризикуваш да звучиш како карикатуристот Дарвинист.
    Во склоп на научна фантастика, баш пред некој ден ми излезе ова.
    Кога сме веќе тука, не можам да дочекам да излезат нови епизоди од Black Mirror, што е сепак bittersweet, бидејќи и да излезат, ќе се малку епизоди :envy:.
    Мислам дека ова тактички го направи: повеќе ќе ја примами таа публика ако уште во насловот ги испровоцира :devil:.
    Познавајќи се себеси и дека и покрај тоа што вчера откако ги постирав мислењата не можев да ја „исклучам“ главата во следните 4 саати, односно и покрај толку мозгање, разгледување, размислување, голема е веројатноста по месец-два да ми избледат деталите, ова е делумно и за моја придобивка - да можам секогаш да се потсетам барем на главните поенти поврзани со темата :rofl:. Иако, тогаш кога ќе ги читам ќе ми звучи како сосема некој друг да ги напишал, а не јас :lol:.
    Мене секако ми одговара, бидејќи сега сум релативно послободна (wfh).
     
    На Lella му/ѝ се допаѓа ова.
  6. DAngel

    DAngel Форумски идол

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    Со поприлично ниски очекувања влегов во читање на книгава, и можам да кажам дека дефинитивни ги надмина моите очекувања. Морам да се објаснам: Зошто со ниски? Затоа што од лично искуство, премногу цитирани книги обично ми се на ниво или на некој булшит или на "ништо не разбирам од книгава ама се правам паметен па ќе ја спомнам и јас." Dawkins се покажа дека не е еден од тие автори.
    Од друга страна, книгата постепено го губеше оној жар на "уау, ова е феноменално", па кога стигна до делот на другите тоерии ми беше тотално неинтересно за мојот симпл мозок и тотално незаинтересиран за внатрешни препукувања во науката. Така, на крај ме остави тотално без збор: Did I love it? Did I want to love it, but I didn't love it enough? Did I want to hate it, but loved it more than expected? Искрено, немам појма. Премногу емоции за нефикција.

    Сакам да спомнам неколку работи надвор од книгата, што можеби не ви се познати, а од друга страна се интересни, па преку нив ќе ги доловам елементи од книгата.

    Доцниот 20ти век бележи појава на една мултидисциплинарна научна гранка позната како комплексност или комплексни системи. Прецизно дефинирање на комплексност, дури и гледано од страна на научниците кои се бават со тоа, е невозможна мисија. Комплексните системи, во било која дисциплина, долгорочно делат една карактеристика: невозможно е да се направи долгорочно предвидување. Ако сте го гледале филмот "The butterfly effect", сигурно ви е позната барем по име теоријата на хаосот:
    Временската прогноза е уште еден комплексен систем во кој минимални варијации во условите може да донесат до огромни промени. Затоа е речиси невозможно да се направи временска прогноза која ќе предвиди повеќе од 5 дена во иднината. Или зошто е невозможно да се предвидат земјотресите.
    Постојат и математички фукнции кои за одредени коефициенти се однесуваат хаотично, па разлика од само 0.00001 во почетните вредности дава непрепознатливо различни графици на тие фукнции.
    Не знам дали некогаш сум размислувала за еволуцијата како комплексен систем. За делови од еволуцијата да, особено околу фукнционирањето на мравките и начинот на кој стигнуваат до храна, ама веројатно никогаш за еволуцијата во целост. Веројатно никогаш не сум ни премногу размислувала за еволуцијата. Не дека некогаш сум се посомневала во неа :?:
    Ама да, еволуцијата како што и самиот Dawkins кажува, е комплексен систем. Од една страна, имаш резултати кои е тешко да се предвидат и два исти проблеми кои можат да дојдат до различни решенија (пример, цицачита во Австралија и остатокот на светот), но и сосема различни единки кои независно развиле исти механизми за справување со еден проблем (ова е искрено фасцинантно).
    Bottom line is. Еволуцијата е комплексна затоа што не може да се предвиди, но во духот на теоријата на хаосот, пандан на ова со пеперутката, мали и незначителни придвижувања на едно место создаваат големи и значителни промени. Тие промени се само значителни, но не и дефинивно позитивни, не и секогаш во една насока. Патем, и еволуцијата како природен систем подлежи на физичките закони (на многу поголема скала и многу понеприметливо, но подложи), а според вториот закон на термодинамиката ентропијата на затворен систем никогаш не се намалува. Значи, не можеме да станеме посовршени, секоја еволутивна промена не прави само "посложени, помалку подредени, похаотични", но не и посовршени.

    Во компјутерски науки, посебно машинско учење и вештачка интелигенција постои група на алгоритми наречени "генетски алгоритми".
    (Можеби сте ме фатиле како го зезам Витали дека нема да може да програмира генетски алгоритми штом не верува во еволуција :rofl:). Генетски алгоритам буквално претставува моделирање на еволуција за решавање на одредена задача.
    Иако биоморфите на Dawkins се интересни, и можеби се low-level генетски алгоритам, не можат ни да се споредат со магијата на генетските алгоритми. Trust me on this one.
    А, и тој самиот си признава дека горе - долу со малку труд може да предвиди што ќе добие и да тригерира одреден исход. Со генетски алгоритам - не можеш да го предвидиш исходот, а често и решението до кое ќе дојде алгоритамот еволутивно ќе биде сосема различно од одејата која си ја имал ти.

    Како работи еден генетски алгоритам? Одредени елементи кои се битни карактеристики за задачата која сакаме да је постигнеме ги земаме како "гени" со одредени параметри. Првата генерација е целосно рандом, или барем educated guess. Пуштаме повеќе интанци до агентот (софтвери што ја врши фунцијата) и им даваме одредено време да ја завршат. Успешноста во вршење на фукцијата се одредува според некој параметар, некој fitness, a со тоа и нивната веројатност дека ќе остават потомство.
    Се бираат родители од генерацијата и секој од родителите според некој алгоритам пренесува гени на своето потомство.
    Се додава и можност за мутација со одередена веројатност, што ќе промени некој ген за некоја вредност.
    Така се креира нова генерација агенти што ќе ги замени старите и се пушта да ја извршува задачата.
    Евентуално, се добива агент кој "еволуирал" за доволно добро да ја изврши задачата, или доволно добро да преживее во околината која сме му ја создале.
    Ова од прилика изгледа вака
    [​IMG]
    А за директно пробање и "играње" со генетски алгоритми и еволуција постои игра - симулатор Evolution

    Целта е со помош на "зглобови", "коски" и "мускули" да создадеш суштество кое се движи. Ти го градиш и го пушташ да еволуира, а негова работа е да научи да се движи

    https://keiwan.itch.io/evolution

    Така. Уште нешто за книгата.
    Од една страна, Dawkins ми остави доста позитивен впечаток. Ми се допадна тој негов "geeky vibe" и ентузијазмот со кој објаснува за работите што го интересираат, мислам oчигледно беше Која страст е вложена во книгата and I reallz think he enjozed writing it. Од друга страна, концептите погоре ми фалеа во соодветните поглавја, затоа ги додавам.
    Overall, супер книга.

    Како предлог:

    1. Thinking Fast and Slow - Daniel Kahneman (интуиција наспроти рационалност и како фукционираат заедно)
    2. The Righteous Mind: Why Good People Are Divided by Politics and Religion - Jonathan Haidt (зошто луѓето имаат тендеција да се делат и групираат во "ние" и "тие"
    3. Catch and Kill: Lies, Spies, and a Conspiracy to Protect Predators - Ronan Farrow (за обидите да се прикрие и заштити Harvey Weinstein)
    4. Braiding Sweetgrass: Indigenous Wisdom, Scientific Knowledge, and the Teachings of Plants - Robin Wall Kimmerer (би рекла дека спаѓа во Indigenous wisdom, giving and receiving from Earth)
    И една фикшн?
    5. A Clockwork Orange - Anthony Burgess (дистопија)
     
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  7. Lella

    Lella Форумски идол

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    Решив да ги ставам сите предлози од месецов во анкетата. Ќе има малку повеќе опции ама се надевам нема да дојде до проблем.

    Еве ги објаснувањата за книгите:
    A Brief History of Time – Stephen Hawking (pop-science класик, космологија и астрофизика)


    Неколку дена ќе гласаме, во зависност од бројот на гласови во анкетата.

    Патем, ова ми беше многу интересен момент:
    Интересно е бидејќи еден од главните аргументи за интелигентен дизајн е дека поради фактот што природата се стреми кон максимална ентропија, заклучуваме дека сме вакви какви што сме бидејќи сме биле плански дизајнирани, односно последица на план, а не последица на природата. Ама ова е под претпоставка дека нашиот дизајн е комплексен, што тука подразбира нехаотичен, orderly, не-рандом. Ако гледаме така, тогаш да, еволуцијата е невозможна, бидејќи според ова резонирање еволуцијата ја намалува ентропијата. Ама ако на комплексноста гледаме како на randomness т.е. хаос, а на природната селекција како надворешен нерандом фактор кој одбира кој ќе преживее, тогаш аргументот се распаѓа. Мислам и Докинс спомна: еволуцијата го крши Вториот термодинамички закон исто колку што и растењето на бебе го крши.
     
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  8. pdb123

    pdb123 Популарен член

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    Се премислив за The Story of Stuff :doh:. Сакав релевантна книга посветена на одржување на животната средина и со оглед на тоа што авторката работела со голем број организации, а според Википедија моментално е извршен директор на Greenpeace USA, мислев дека ќе е ок. Мислам дека пред да ја напише книгата, направила и краток анимиран филм со истото име во 2007 кој доста станал познат, а оттогаш имаат направено и поспецијализирани филмови, за поконкретни проблематики. Може има и доста точни информации, не велам не, меѓутоа вчера го изгледав филмот за тоа што колку-толку разбирам - козметика - и кога почна со тоа колку токсични состојки содржат производите (а не е така), се напнав и разочарав и сега мислам дека во сè ќе се сомневам ако ја читам книгата (wtf).
     
  9. sweet-cherry

    sweet-cherry Форумски идол

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    Ја отварам темава и кога и да влезам деновиве изедначени се гласовите :D дај некој нека ни реши
     
  10. Lella

    Lella Форумски идол

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    Си го сменив гласот јас, нека биде Thinking, fast and slow. :D Комплетно заборавив на анкетава.
     
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  11. pdb123

    pdb123 Популарен член

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    1/9

    Eве ме, два и пол-три месеци подоцна :D. Имам проблеми со концентрација и ми требаше долго време да ја прочитам книгата (а и искрено, правев долги паузи), но сепак не се откажувам, сакам да „се исфорсирам“ низ мрзата и дефокусираноста и сепак да прочитам, затоа што знам дека потоа ќе ми е мило што сум го направила тоа. Сега, доцнам многу, ама моето мото е „подобро некогаш отколку никогаш“ :!: (кај мене најчесто „некогаш“ наместо „навреме“ доминира, but hey, at least I do it (waiting)).

    Главниот впечаток од книгата е дека ми се допадна премногу и би сакала да можев да меморизирам сè што е напоменато. Многу ми се допадна стилот на пишување, не беше ни прекомплициран, да си ја мачиш душата, но не беше ни преедноставен, за читање во 2 дена. Преинтересно ми беше сè поврзано околу студиите, односно резултатите кои се добија, баш ми се интересни trivia информации кои би му ги кажувал некому низ муабет, како рандом факти :D. Книгата е ПРЕполна со информации, не можам ни да процесирам и запаметам сè од едно читање. Четвртиот дел ми беше особено интересен - интерактивен, имаше доста примери за избор меѓу две или повеќе опции.

    Веројатно најмногу ми се допадна неутралниот, дури и понизен стил на Даниел, кој можеби е последица на некои лични соочувања и препознавања на резултатите кои се добивале со студиите. Лично, имам посебен восхит и многу ценам луѓе кои и покрај својот докажан капацитет и стручност, успеваат да ја задржат понизноста и скромноста. И мислам дека овие студии совршено ги „спуштаат на земја“ експертите дека не треба да се поставуваат над другите луѓе.

    Звучам како да сум од луѓето што не веруваат во доктори и општо наука, што не е така: верувам во „разумност“ пред пополнување на празнини со сопствени приказни. Само сакав да кажам дека не го ценам односот кој понекогаш е придружен со стручноста и интелигенцијата на личноста, без разлика дека е во право 8-|. Едноставно не ми се допаѓа надменост/арогантност/директно или индиректно омаловажување или потценување. Звучи малку дволично, затоа што сигурна сум дека и јас некогаш сум се поставила на тој начин спрема некого. Ама се трудам.

    Назад на книгата. Особено во деловите каде се зборуваше за среќа или веројатност (на пример, војниците кои се подобриле/влошиле по прекорување (ете еден збор кој не сум го искористила/слушнала одамна, којзнае од која длабочина на мозокот го ископав :o) /пофалба, се потсетив на претходната книга каде што Ричард исто велеше дека не можеме да се помириме дека некои работи се едноставно произволни и немаат скриена причина. Истото се зборува и овде, постојано си наоѓаме причини и шеми за работите кои се случуваат.

    До неодамна мислев дека е комплицирано да ја знаеш „вистината“ за некоја област чии мислења се поделени (ок, а која област реално не е таква? :^)), затоа што освен ако не си и ти навлезен докрај во тематиката, многу е тешко да ги процениш финесите на различните тврдења и сè се сведува на тоа дека на крајот од денот сепак не си ти толку „знаен“ за темата, туку си нашол некого (од таа област) кому си ја дал довербата.

    Дури и ние ова што го правиме, читањето на книги за одредени тематики е всушност давање на доверба на некој автор. Не е дека не можеме да имаме критичка мисла и да се посомневаме во напишаното, но сметам дека практично невозможно е лаик да го „опипа“ „најразумната“ теорија. Би требало сега ние да прочитаме еден куп книги со теории против тврдењата на Даниел, да претпоставиме дека тие автори се добри претставници од поборниците на тие тврдења, како и да знаеме доволно и добро да ги увидиме сите ситни (не очигледни) недоследности.

    Буквално да сме критички на научнички начин, нешто што е претешко дури и за човек кој цел живот го посветил на оваа конкретна тема. И тоа ова е само зрнце, едно атомче од милионите области и прашања кои може да го интересира некој човек. Едноставно нема време за да сме совршено опремени ниту во една област, а камоли во повеќе области.

    Ова сè звучи многу јасно и очигледно, ама работите лично за мене се искомплицираа уште повеќе кога од неодамна почнав да дознавам за предрасудите кои се чести во научниот, т.е. псевдо-научниот свет и сфатив дека и експертите, кои би требало да се објективни и „реални“ ги имаат овие предрасуди, па книгата ми дојде само како јаготка на шлагот.

    И ова звучи очигледно и неимпресивно, ама барем јас, кога навистина почнав да размислувам дека не можеш да си сигурен ниту во научните тврдења во кои се „крстиш“, добив како некое парализирачко, кризирачки мисли од стилот: Е сега во што можам да верувам? Дали значи дека никогаш не можам да постигнам објективност? Дали воопшто имаат поента моите или туѓите мислења?? Мислам дека отсекогаш мислев дека има факти кои не можеш да ги игнорираш и дека можеш да добиеш детална и прецизна претстава за многу работи, па сега буквално се соочувам со рушење на цел таков свет, па почувствував тежината од огромна несигурност. Теоретски јасно ми е дека „тоа е животот“ и „задоволи се дека никогаш нема да знаеш ништо докрај“, ама тешко ми е да го усогласам тоа сознание со претходните чувства.

    Ок, доста е од беспотребни автобиографски моменти кои имаат или воопшто немаат врска со темата :wasntme:. Друго што многу ми се допадна е што Даниел постојано го споменува Amos; имам чувство како да имале супер bromance, се гледа дека навистина го почитува и несебично сака да му даде заслуга за нивното заедничко работење. Повторно се навраќам на скромноста на Даниел, но многу ми се допадна и што самиот лично ги призна и ги напомена недостатоците/слабостите на prospect theory и дури и изрази сочувство зошто други поточни теории не станале попопуларни досега.

    За крај, би рекла дека малку жалам што ги прочитав додатоците на крајот од книгата; поентите беа исти како во остатокот од книгата, но барем лично ми беа далеку потешки и за читање и за разбирање, имајќи предвид дека се користеа доста термини од статистика и обработка на податоци што мене ми беа нејасни, па не ми значеа ништо.

    Мислам дека опфатив сè што сакав да кажам во однос на книгата, т.е. главните моменти - чувства и побуди кај мене. Како и претходниот пат, би извадила цитати коишто ги бележев додека читав, но не знам дали имам коментари за давање, затоа што ќе треба постојано да повторувам колку ми е интересно/се пронаоѓам/ми има смисла итн ^_^. Можно е некои работи да се повторуваат (и тој често повторуваше работи), затоа што селектирав како што читав, без да знам дали понатаму подетално ќе се образложи некоја поента.

    The capabilities of System 1 include innate skills that we share with other animals. We are born prepared to perceive the world around us, recognize objects, orient attention, avoid losses, and fear spiders. Other mental activities become fast and automatic through prolonged practice. System 1 has learned associations between ideas (the capital of France?); it has also learned skills such as reading and understanding nuances of social situations.

    Orienting to a loud sound is normally an involuntary operation of System 1, which immediately mobilizes the voluntary attention of System 2. You may be able to resist turning toward the source of a loud and offensive comment at a crowded party, but even if your head does not move, your attention is initially directed to it, at least for a while.

    The often-used phrase “pay attention” is apt: you dispose of a limited budget of attention that you can allocate to activities, and if you try to go beyond your budget, you will fail. It is the mark of effortful activities that they interfere with each other, which is why it is difficult or impossible to conduct several at once.

    You can do several things at once, but only if they are easy and undemanding.

    Intense focusing on a task can make people effectively blind, even to stimuli that normally attract attention. The most dramatic demonstration was offered by Christopher Chabris and Daniel Simons in their book The Invisible Gorilla.
    System 1 runs automatically and System 2 is normally in a comfortable low-effort mode, in which only a fraction of its capacity is engaged. System 1 continuously generates suggestions for System 2: impressions, intuitions, intentions, and feelings. If endorsed by System 2, impressions and intuitions turn into beliefs, and impulses turn into voluntary actions. When all goes smoothly, which is most of the time, System 2 adopts the suggestions of System 1 with little or no modification. You generally believe your impressions and act on your desires, and that is fine—usually.

    In summary, most of what you (your System 2) think and do originates in your System 1, but System 2 takes over when things get difficult, and it normally has the last word.
    The division of labor between System 1 and System 2 is highly efficient: it minimizes effort and optimizes performance. The arrangement works well most of the time because System 1 is generally very good at what it
    does: its models of familiar situations are accurate, its short-term predictions are usually accurate as well, and its initial reactions to challenges are swift and generally appropriate. System 1 has biases, however, systematic errors that it is prone to make in specified circumstances.
    Conflict between an automatic reaction and an intention to control it is common in our lives.

    And every human being has had the experience of not telling someone to go to hell ( :rofl::rofl:). One of the tasks of System 2 is to overcome the impulses of System 1. In other words, System 2 is in charge of self-control.
    “Mental arithmetic is a voluntary activity that requires effort, should not be performed while making a left turn, and is associated with dilated pupils and an accelerated heart rate.”

    Systems 1 and 2 are not systems in the standard sense of entities with interacting aspects or parts. And there is no one part of the brain that either of the systems would call home.
    (Искрено, ова ми е истовремено и лесно и тешко да го сфатам. Океј, мозокот работи во целина, јасно е тоа, но како не може да се направи некоја позначајна „физичка“ разлика меѓу брзо и бавно размислување, како не постои нешто што „одлучува“ кое ќе се „приклучи“ во моментот. Не знам како да го поставам прашањето, знам дека ова што го напишав оди против поентата на реченицата :?:.)
    In the first 5 seconds, the pupil dilates by about 50% of its original area and heart rate increases by about 7 beats per minute. This is as hard as people can work—they give up if more is asked of them.

    An image came to mind: mental life—today I would speak of the life of System 2—is normally conducted at the pace of a comfortable walk, sometimes interrupted by episodes of jogging and on rare occasions by a frantic sprint. The Add-1 and Add-3 exercises are sprints, and casual chatting is a stroll.

    As you become skilled in a task, its demand for energy diminishes. Studies of the brain have shown that the pattern of activity associated with an action changes as skill increases, with fewer brain regions involved. Talent has similar effects. Highly intelligent individuals need less effort to solve the same problems, as indicated by both pupil size and brain activity. A general “law of least effort” applies to cognitive as well as physical exertion. The law asserts that if there are several ways of achieving the same goal, people will eventually gravitate to the least demanding course of action. In the economy of action, effort is a cost, and the acquisition of skill is driven by the balance of benefits and costs. Laziness is built deep into our nature.

    Effort is required to maintain simultaneously in memory several ideas that require separate actions, or that need to be combined according to a rule—rehearsing your shopping list as you enter the supermarket, choosing between the fish and the veal at a restaurant, or combining a surprising result from a survey with the information that the sample was small, for example. System 2 is the only one that can follow rules, compare objects on several attributes, and make deliberate choices between options. The automatic System 1 does not have these capabilities. System 1 detects simple relations (“they are all alike,” “the son is much taller than the father”) and excels at integrating information about one thing, but it does not deal with multiple distinct topics at once, nor is it adept at using purely statistical information. System 1 will detect that a person described as “a meek and tidy soul, with a need for order and structure, and a passion for detail” resembles a caricature librarian, but combining this
    intuition with knowledge about the small number of librarians is a task that only System 2 can perform—if System 2 knows how to do so, which is true of few people.

    One of the significant discoveries of cognitive psychologists in recent decades is that switching from one task to another is effortful, especially under time pressure.

    The most effortful forms of slow thinking are those that require you to think fast.
    (Имајќи предвид дека постојано размислуваме брзо, која е иронијата во оваа реченица, зарем не?)
    Although I have not conducted a systematic survey, I suspect that frequent switching of tasks and speeded-up mental work are not intrinsically pleasurable, and that people avoid them when possible. This is how the law of least effort comes to be a law. Even in the absence of time pressure, maintaining a coherent train of thought requires discipline. An observer of the number of times I look at e-mail or investigate the refrigerator during an hour of writing could infer an urge to escape and conclude that keeping at it requires more self-control than I can readily muster.

    People who experience flow describe it as “a state of effortless concentration so deep that they lose their sense of
    time, of themselves, of their problems,” and their descriptions of the joy of that state are so compelling that Csikszentmihalyi has called it an “optimal experience.”
    (Совршен опис според мене. Исто така, what the hell со името на научникот :D)
     
    Последна измена: 11 април 2021
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  12. pdb123

    pdb123 Популарен член

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    System 1 has more influence on behavior when System 2 is busy, and it has a sweet tooth.
    (You and me both, System 1 :lol:)

    The conclusion is straightforward: self-control requires attention and effort. Another way of saying this is that
    controlling thoughts and behaviors is one of the tasks that System 2 performs.

    Baumeister’s group has repeatedly found that an effort of will or self-control is tiring; if you have had to force yourself to do something, you are less willing or less able to exert self-control when the next challenge comes
    around. The phenomenon has been named ego depletion (фенси израз за „ама сакам по мое да е!!!“ :rofl:).

    The nervous system consumes more glucose than most other parts of the body, and effortful mental activity appears to be especially expensive in the currency of glucose. When you are actively involved in difficult cognitive
    reasoning or engaged in a task that requires self-control, your blood glucose level drops. The effect is analogous to a runner who draws down glucose stored in her muscles during a sprint. The bold implication of this idea is that the effects of ego depletion could be undone by ingesting glucose, and Baumeister and his colleagues have confirmed this hypothesis in several experiments.
    (Којзнае колку тешки резонирања правам што толку ми бара мозокот благо ]:)]:))

    As you might expect, this is an unwelcome result and the authors carefully checked many alternative explanations. The best possible account of the data provides bad news: tired and hungry judges tend to fall back on the easier default position of denying requests for parole. Both fatigue and hunger probably play a role.
    (Не можам, замислувам hangry судии :rofl::rofl:)
    This experiment has discouraging implications for reasoning in everyday life. It suggests that when people believe a conclusion is true, they are also very likely to believe arguments that appear to support it, even when these arguments are unsound.

    Memory function is an attribute of System 1.

    The extent of deliberate checking and search is a characteristic of System 2, which varies among individuals.

    “Lazy” is a harsh judgment about the self-monitoring of these young people and their System 2, but it does not seem to be unfair. Those who avoid the sin of intellectual sloth could be called “engaged.” They are more alert, more intellectually active, less willing to be satisfied with superficially attractive answers, more skeptical about their intuitions. The psychologist Keith Stanovich would call them more rational.
    (Замислете да добиете ваков комплимент од некој научник :smirk::inlove:)
    System 1 is impulsive and
    intuitive; System 2 is capable of reasoning, and it is cautious, but at least for some people it is also lazy. We recognize related differences among individuals: some people are more like their System 2; others are closer to
    their System 1.
    As cognitive scientists have emphasized in recent years, cognition is embodied; you think with your body, not only with your brain.
    We call this a priming effect and say that the idea of EAT primes the idea of SOUP, and that WASH primes SOAP.

    Furthermore, the primed ideas have some ability to prime other ideas, although more weakly.

    This remarkable priming phenomenon—the influencing of an action by the idea—is known as the ideomotor effect.

    Reciprocal priming effects tend to produce a coherent reaction: if you were primed to think of old age, you
    would tend to act old, and acting old would reinforce the thought of old age.
    The general theme of these findings is that the idea of money primes individualism: a reluctance to be involved with others, to depend on others, or to accept demands from others.

    You have no choice but to accept that the major conclusions of these studies are true. More important, you must accept that they are true about you. If you had been exposed to a screen saver of floating dollar bills, you too would likely have picked up fewer pencils to help a clumsy stranger. You do not believe that these results apply to you because they correspond to nothing in your subjective experience. But your subjective experience consists largely of the story that your System 2 tells itself about what is going on. Priming phenomena arise in System 1, and you have no conscious access to them.
    The assessments are carried out automatically by System 1, and one of their functions is to determine whether extra effort is required from System 2. One of the dials measures cognitive ease, and its range is between
    “Easy” and “Strained.” Easy is a sign that things are going well—no threats, no major news, no need to redirect attention or mobilize effort. Strained indicates that a problem exists, which will require increased mobilization of System 2. Conversely, you experience cognitive strain. Cognitive strain is affected by both the current level of effort and the presence of unmet demands.

    When you are in a state of cognitive ease, you are probably in a good mood, like what you see, believe what you hear, trust your intuitions, and feel that the current situation is comfortably familiar. You are also likely to be relatively casual and superficial in your thinking. When you feel strained, you are more likely to be vigilant and suspicious, invest more effort in what you are doing, feel less comfortable, and make fewer errors, but you also are less intuitive and less creative than usual.
    Jacoby nicely stated the problem: “The experience of familiarity has a simple but powerful quality of ‘pastness’ that seems to indicate that it is a direct reflection of prior experience.” This quality of pastness is an illusion. The truth is, as Jacoby and many followers have shown, that the name David Stenbill will look familiar when you see it because you will see it more clearly. Words that you have seen before become easier to see again—you can identify them better than other words when they are shown very briefly or masked by noise, and you will be quicker (by a few hundredths of a second) to read them than to read other words. In short, you experience greater cognitive ease in perceiving a word you have seen earlier, and it is this sense of ease that gives you the impression of familiarity.
    The lesson of figure 5 is that predictable illusions inevitably occur if a judgment is based on an impression of cognitive ease or strain. Anything that makes it easier for the associative machine to run smoothly will also bias beliefs. A reliable way to make people believe in falsehoods is frequent repetition, because familiarity is not easily distinguished from truth. Authoritarian institutions and marketers have always known this fact. But it was psychologists who discovered that you do not have to repeat the entire statement of a fact or idea to make it appear true.
    If you care about being thought credible and intelligent, do not use complex language where simpler language will do.

    In addition to making your message simple, try to make it memorable. Put your ideas in verse if you can; they will be more likely to be taken as truth.

    Finally, if you quote a source, choose one with a name that is easy to pronounce.

    All this is very good advice, but we should not get carried away. High-quality paper, bright colors, and rhyming or simple language will not be much help if your message is obviously nonsensical, or if it contradicts facts that your audience knows to be true.
    Cognitive strain, whatever its source, mobilizes System 2, which is more likely to reject the intuitive answer suggested by System 1.
    As we saw in figure 5, repetition induces cognitive ease and a comforting feeling of familiarity...[ ] Zajonc called it the mere exposure effect.

    The mere exposure effect does not depend on the conscious experience of familiarity. In fact, the effect does not depend on consciousness at all: it occurs even when the repeated words or pictures are shown so quickly that the observers never become aware of having seen them.

    The mere exposure effect occurs, Zajonc claimed, because the repeated exposure of a stimulus is followed by nothing bad. Such a stimulus will eventually become a safety signal, and safety is good.

    Zajonc offered an eloquent summary of his program of research:
    The consequences of repeated exposures benefit the organism in its relations to the immediate animate and inanimate environment. They allow the organism to distinguish objects and habitats that are safe from those that are not, and they are the most primitive basis of social attachments. Therefore, they form the basis for social organization and cohesion—the basic sources of psychological and social stability.
    These findings add to the growing evidence that good mood, intuition, creativity, gullibility, and increased reliance on System 1 form a cluster. At the other pole, sadness, vigilance, suspicion, an analytic approach, and increased effort also go together. A happy mood loosens the control of System 2 over performance: when in a good mood, people become more intuitive and more creative but also less vigilant and more prone to logical errors. Here again, as in the mere exposure effect, the connection makes biological sense. A good mood is a signal that things are generally going well, the environment is safe, and it is all right to let one’s guard down. A bad mood indicates that things are not going very well, there may be a threat, and vigilance is required. Cognitive ease is both a cause and a consequence of a pleasant feeling.
    (Затоа сум почесто нерасположена значи!!!! Се шегувам :rofl::rofl:)
    Some expectations are active and conscious—you know you are waiting for a particular event to happen. When the hour is near, you may be expecting the sound of the door as your child returns from school; when the door opens you expect the sound of a familiar voice. You will be surprised if an actively expected event does not occur. But there is a much larger category of events that you expect passively; you don’t wait for them, but you are not surprised when they happen. These are events that are normal in a situation, though not sufficiently probable to be actively expected.
    We are evidently ready from birth to have impressions of causality, which do not depend on reasoning about patterns of causation. They are products of System 1.

    The prominence of causal intuitions is a recurrent theme in this book because people are prone to apply causal thinking inappropriately, to situations that require statistical reasoning. Statistical thinking derives conclusions about individual cases from properties of categories and ensembles. Unfortunately, System 1 does not have the capability for this mode of reasoning; System 2 can learn to think statistically, but few people receive the necessary training.
    Jumping to conclusions is efficient if the conclusions are likely to be correct and the costs of an occasional mistake acceptable, and if the jump saves much time and effort. Jumping to conclusions is risky when the situation is unfamiliar, the stakes are high, and there is no time to collect more information.

    When uncertain, System 1 bets on an answer, and the bets are guided by experience. The rules of the betting are intelligent: recent events and the current context have the most weight in determining an interpretation. When no recent event comes to mind, more distant memories govern.

    The most important aspect of both examples is that a definite choice was made, but you did not know it. Only one interpretation came to mind, and you were never aware of the ambiguity. System 1 does not keep track of alternatives that it rejects, or even of the fact that there were alternatives. Conscious doubt is not in the repertoire of System 1; it requires maintaining incompatible interpretations in mind at the same time, which demands mental effort. Uncertainty and doubt are the domain of System 2.
    The moral is significant: when System 2 is otherwise engaged, we will believe almost anything. System 1 is gullible and biased to believe, System 2 is in charge of doubting and unbelieving, but System 2 is sometimes busy, and often lazy. Indeed, there is evidence that people are more likely to be influenced by empty persuasive messages, such as commercials, when they are tired and depleted.
    The operations of associative memory contribute to a general confirmation bias. When asked, “Is Sam friendly?” different instances of Sam’s behavior will come to mind than would if you had been asked “Is Sam unfriendly?” A deliberate search for confirming evidence, known as positive test strategy, is also how System 2 tests a hypothesis. Contrary to the rules of philosophers of science, who advise testing hypotheses by trying to refute them, people (and scientists, quite often) seek data that are likely to be compatible with the beliefs they currently hold. The confirmatory bias of System 1 favors uncritical acceptance of suggestions and exaggeration of the likelihood of extreme and improbable events.
    If you like the president’s politics, you probably like his voice and his appearance as well. The tendency to like (or dislike) everything about a person—including things you have not observed—is known as the halo effect. The term has been in use in psychology for a century, but it has not come into wide use in everyday language. This is a pity, because the halo effect is a good name for a common bias that plays a large role in shaping our view of people and situations. It is one of the ways the representation of the world that System 1 generates is simpler and more coherent than the real thing.

    To derive the most useful information from multiple sources of evidence, you should always try to make these sources independent of each other.
     
    Последна измена: 11 април 2021
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  13. pdb123

    pdb123 Популарен член

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    The measure of success for System 1 is the coherence of the story it manages to create. The amount and quality of the data on which the story is based are largely irrelevant. When information is scarce, which is a common occurrence, System 1 operates as a machine for jumping to conclusions.

    The combination of a coherence-seeking System 1 with a lazy System 2 implies that System 2 will endorse many intuitive beliefs, which closely reflect the impressions generated by System 1. Of course, System 2 also is capable of a more systematic and careful approach to evidence, and of following a list of boxes that must be checked before making a decision—think of buying a home, when you deliberately seek information that you don’t have. However, System 1 is expected to influence even the more careful decisions. Its input never ceases.

    However, I will also invoke WY SIATI to help explain a long and diverse list of biases of judgment and choice, including the following among many others:
    - Overconfidence: As the WY SIATI rule implies, neither the quantity nor the quality of the evidence counts for much in subjective confidence. The confidence that individuals have in their beliefs depends mostly on the quality of the story they can tell about what they see, even if they see little. We often fail to allow for the possibility that evidence that should be critical to our judgment is missing—what we see is all there is. Furthermore, our associative system tends to settle on a coherent pattern of activation and suppresses doubt and ambiguity.
    - Framing effects: Different ways of presenting the same information often evoke different emotions. The statement that “the odds of survival one month after surgery are 90%” is more reassuring than the equivalent statement that “mortality within one month of surgery is 10%.” Similarly, cold cuts described as “90% fat-free” are more attractive than when they are described as “10% fat.” The equivalence of the alternative formulations is transparent, but an
    individual normally sees only one formulation, and what she sees is all there is.
    System 2 receives
    questions or generates them: in either case it directs attention and searches memory to find the answers. System 1 operates differently. It continuously monitors what is going on outside and inside the mind, and continuously generates assessments of various aspects of the situation without specific intention and with little or no effort.
    You do not automatically count the number of syllables of every word you read, but you can do it if you so choose. However, the control over intended computations is far from precise: we often compute much more than we want or need. I call this excess computation the mental shotgun. It is impossible to aim at a single point with a shotgun because it shoots pellets that scatter, and it seems almost equally difficult for System 1 not to do more than System 2 charges it to do.
    The normal state of your mind is that you have intuitive feelings and opinions about almost everything that comes your way.
    I propose a simple account of how we generate intuitive opinions on complex matters. If a satisfactory answer to a hard question is not found quickly, System 1 will find a related question that is easier and will answer it. I call the operation of answering one question in place of another substitution. I also adopt the following terms:
    The target question is the assessment you intend to produce.
    The heuristic question is the simpler question that you answer instead.
    The technical definition of heuristic is a simple procedure that helps find adequate, though often imperfect, answers to difficult questions. The word comes from the same root as eureka.

    On some occasions, substitution will occur and a heuristic answer will be endorsed by System 2. Of course, System 2 has the opportunity to reject this intuitive answer, or to modify it by incorporating other information. However, a lazy System 2 often follows the path of least effort and endorses a heuristic answer without much
    scrutiny of whether it is truly appropriate.
    Self-criticism is one of the functions of System 2. In the context of attitudes, however, System 2 is more of an apologist for the emotions of System 1 than a critic of those emotions—an endorser rather than an enforcer. Its
    search for information and arguments is mostly constrained to information that is consistent with existing beliefs, not with an intention to examine them. An active, coherence-seeking System 1 suggests solutions to an undemanding System 2.
    Even now, you must exert some mental effort to see that the following two statements mean exactly the same thing:
    - Large samples are more precise than small samples.
    - Small samples yield extreme results more often than large samples do.
    The associative machinery seeks causes. The difficulty we have with statistical regularities is that they call for a different approach. Instead of focusing on how the event at hand came to be, the statistical view relates it to what could have happened instead. Nothing in particular caused it to be what it is—chance selected it from among its alternatives.

    We do not expect to see regularity produced by a random process, and when we detect what appears to be a rule, we quickly reject the idea that the process is truly random. Random processes produce many sequences that convince people that the process is not random after all. You can see why assuming causality could have had evolutionary advantages. It is part of the general vigilance that we have inherited from ancestors. We are automatically on the lookout for the possibility that the environment has changed.

    The exaggerated faith in small samples is only one example of a more general illusion—we pay more attention to the content of messages than to information about their reliability, and as a result end up with a view of the world around us that is simpler and more coherent than the data justify. Jumping to conclusions is a safer sport in the world of our imagination than it is in reality.
    The phenomenon we were studying is so common and so important in the everyday world that you should know its name: it is an anchoring effect. It occurs when people consider a particular value for an unknown quantity before estimating that quantity.

    Any number that you are asked to consider as a possible solution to an estimation problem will induce an anchoring effect.
    Amos liked the idea of an adjust-and-anchor heuristic as a strategy for estimating uncertain quantities: start from an anchoring number, assess whether it is too high or too low, and gradually adjust your estimate by mentally “moving” from the anchor. The adjustment typically ends prematurely, because people stop when they are no longer certain that they should move farther.
    A process that
    resembles suggestion is indeed at work in many situations: System 1 tries its best to construct a world in which the anchor is the true number.

    The researchers found that 68°F made it easier to recognize summer words (like sun and beach), and 40°F facilitated winter words (like frost and ski). The selective activation of compatible memories explains anchoring: the high and the low numbers activate different sets of ideas in memory. The estimates of annual temperature draw on these biased samples of ideas and are therefore biased as well.
    Anchoring effects have always been studied in tasks of judgment and choice that are ultimately completed by System 2. However, System 2 works on data that is retrieved from memory, in an automatic and involuntary operation of System 1. System 2 is therefore susceptible to the biasing influence of anchors that make some information easier to retrieve. Furthermore, System 2 has no control over the effect and no knowledge of it.

    We saw in the discussion of the law of small numbers that a message, unless it is immediately rejected as a lie, will have the same effect on the associative system regardless of its reliability. The gist of the message is the story, which is based on whatever information is available, even if the quantity of the information is slight and its quality is poor: WYSIATI. When you read a story about the heroic rescue of a wounded mountain climber, its effect on your associative memory is much the same if it is a news report or the synopsis of a film. Anchoring results from this associative activation. Whether the story is true, or believable, matters little, if at all.
    (Дали ова не е претажно :D)

    Earlier I discussed the bewildering variety of priming effects, in which your thoughts and behavior may be influenced by stimuli to which you pay no attention at all, and even by stimuli of which you are completely unaware. The main moral of priming research is that our thoughts and our behavior are influenced, much more than we know or want, by the environment of the moment. Many people find the priming results unbelievable, because they do not correspond to subjective experience. Many others find the results upsetting, because they threaten the subjective sense of agency and autonomy. If the content of a screen saver on an irrelevant computer can affect your willingness to help strangers without your being aware of it, how free are you? Anchoring effects are threatening in a similar way. You are always aware of the anchor and even pay attention to it, but you do not know how it guides and constrains your thinking, because you cannot imagine how you would have thought if the
    anchor had been different (or absent). However, you should assume that any number that is on the table has had an anchoring effect on you, and if the stakes are high you should mobilize yourself (your System 2) to combat the effect.
    We defined the availability heuristic as the process of judging frequency by “the ease with which instances come to mind.”

    A question we considered early was how many instances must be retrieved to get an impression of the ease with which they come to mind. We now know the answer: none.

    The availability heuristic, like other heuristics of judgment, substitutes one question for another: you wish to estimate the size of a category or the frequency of an event, but you report an impression of the ease with which instances come to mind. Substitution of questions inevitably produces systematic errors.

    Personal experiences, pictures, and vivid examples are more available than incidents that happened to others, or mere words, or statistics.

    Resisting this large collection of potential availability biases is possible, but tiresome. You must make the effort to reconsider your impressions and intuitions by asking such questions as, “Is our belief that thefts by teenagers are a major problem due to a few recent instances in our neighborhood?” or “Could it be that I feel no need to get a flu shot because none of my acquaintances got the flu last year?” Maintaining one’s vigilance against biases is a chore—but the chance to avoid a costly mistake is sometimes worth the effort.
    The ease with which instances of assertiveness come to the subject’s mind changes during the task. The first few instances are easy, but retrieval soon becomes much harder. Of course, the subject also expects fluency to drop gradually, but the drop of fluency between six and twelve instances appears to be steeper than the participant expected. The results suggest that the participants make an inference: if I am having so much more trouble than expected coming up with instances of my assertiveness, then I can’t be very assertive. Note that this inference rests on a surprise—fluency being worse than expected. The availability heuristic that the subjects apply is better described as an “unexplained unavailability” heuristic.

    As I have described it, the process that leads to judgment by availability appears to involve a complex chain of reasoning. The subjects have an experience of diminishing fluency as they produce instances. They evidently have expectations about the rate at which fluency decreases, and those expectations are wrong: the difficulty of coming up with new instances increases more rapidly than they expect. It is the unexpectedly low fluency that causes people who were asked for twelve instances to describe themselves as unassertive. When the surprise is eliminated, low fluency no longer influences the judgment. The process appears to consist of a sophisticated set of inferences. Is the automatic System 1 capable of it?
    The answer is that in fact no complex reasoning is needed. Among the basic features of System 1 is its ability to set expectations and to be surprised when these expectations are violated. The system also retrieves possible causes of a surprise, usually by finding a possible cause among recent surprises. Furthermore, System 2 can reset the expectations of System 1 on the fly, so that an event that would normally be surprising is now almost normal.

    The conclusion is that the ease with which instances come to mind is a System 1 heuristic, which is replaced by a focus on content when System 2 is more engaged. Multiple lines of evidence converge on the conclusion that people who let themselves be guided by System 1 are more strongly susceptible to availability biases than others who are in a state of higher vigilance.
     
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    The lesson is clear: estimates of causes of death are warped by media coverage. The coverage is itself biased toward novelty and poignancy. The media do not just shape what the public is interested in, but also are shaped by it. Editors cannot ignore the public’s demands that certain topics and viewpoints receive extensive coverage. Unusual events (such as botulism) attract disproportionate attention and are consequently perceived as less unusual than they really are. The world in our heads is not a precise replica of reality; our expectations about the frequency of events are distorted by the prevalence and emotional intensity of the messages to which we are exposed.

    As mentioned earlier, Slovic eventually developed the notion of an affect heuristic, in which people make judgments and decisions by consulting their emotions: Do I like it? Do I hate it? How strongly do I feel about it? In
    many domains of life, Slovic said, people form opinions and make choices that directly express their feelings and their basic tendency to approach or avoid, often without knowing that they are doing so. The affect heuristic is
    an instance of substitution, in which the answer to an easy question (How do I feel about it?) serves as an answer to a much harder question (What do I think about it?)... [ ] Damasio and his colleagues have observed that people who do not display the appropriate emotions before they decide, sometimes because of brain damage, also have an impaired ability to make good decisions. An inability to be guided by a “healthy fear” of bad consequences is a disastrous flaw.
    He points out that experts often measure risks by the number of lives (or life-years) lost, while the public draws finer distinctions, for example between “good deaths” and “bad deaths,” or between random accidental fatalities and deaths that occur in the course of voluntary activities such as skiing. These legitimate distinctions are often ignored in statistics that merely count cases. Slovic argues from such observations that the public has a richer conception of risks than the experts do. Consequently, he strongly resists the view that the experts should rule, and that their opinions should be accepted without question when they conflict with the opinions and wishes of other citizens. When experts and the public disagree on their priorities, he says, “Each side must respect the insights and intelligence of the other.” In his desire to wrest sole control of risk policy from experts, Slovic has challenged the foundation of their expertise: the idea that risk is objective.
    “Risk” does not exist “out there,” independent of our minds and culture, waiting to be measured. Human beings have invented the concept of “risk” to help them understand and cope with the dangers and uncertainties of life. Although these dangers are real, there is no such thing as “real risk” or “objective risk.”
    (Ова ми беше интригантна поента, првпат се соочувам со мислење дека не треба да се водиме според експертски мислења.)

    His point is that the evaluation of the risk depends on the choice of a measure—with the obvious possibility that the choice may have been guided by a preference for one outcome or another. He goes on to conclude that “defining risk is thus an exercise in power.”

    (Спротивното мислење на Sunstein:)
    His view is that the existing system of regulation in the United States displays a very poor setting of priorities, which reflects reaction to public pressures more than careful objective analysis. He starts from the position that risk regulation and government intervention to reduce risks should be guided by rational weighting of costs and benefits, and that the natural units for this analysis are the number of lives saved (or perhaps the number of life-years saved, which gives more weight to saving the young) and the dollar cost to the economy. Poor regulation is wasteful of lives and money, both of which can be measured objectively. Sunstein has not been persuaded by Slovic’s argument that risk and its measurement is subjective. Many aspects of risk assessment are debatable, but he has faith in the objectivity that may be achieved by science, expertise, and careful deliberation.
    Sunstein came to believe that biased reactions to risks are an important source of erratic and misplaced priorities in public policy. Lawmakers and regulators may be overly responsive to the irrational concerns of citizens, both because of political sensitivity and because they are prone to the same cognitive biases as other citizens. Sunstein and a collaborator, the jurist Timur Kuran, invented a name for the mechanism through which biases flow into policy: the availability cascade. They comment that in the social context, “all heuristics are equal, but availability is more equal than the others.” They have in mind an expanded notion of the heuristic, in which availability provides a heuristic for judgments other than frequency. In particular, the importance of an idea is
    often judged by the fluency (and emotional charge) with which that idea comes to mind.
    An availability cascade is a self-sustaining chain of events, which may start from media reports of a relatively minor event and lead up to public panic and large-scale government action. On some occasions, a media story about a risk catches the attention of a segment of the public, which becomes aroused and worried. This emotional reaction becomes a story in itself, prompting additional coverage in the media, which in turn produces greater concern and involvement. The cycle is sometimes sped along deliberately by “availability entrepreneurs,” individuals or organizations who work to ensure a continuous flow of worrying news. The danger is increasingly exaggerated as the media compete for attention-grabbing headlines. Scientists and others who try to dampen the
    increasing fear and revulsion attract little attention, most of it hostile: anyone who claims that the danger is overstated is suspected of association with a “heinous cover-up.” The issue becomes politically important because it is on everyone’s mind, and the response of the political system is guided by the intensity of public sentiment. The availability cascade has now reset priorities. Other risks, and other ways that resources could be applied for the public good, all have faded into the background.

    Where do I come down in the debate between my friends? Availability cascades are real and they undoubtedly distort priorities in the allocation of public resources. Cass Sunstein would seek mechanisms that insulate decision makers from public pressures, letting the allocation of resources be determined by impartial experts who have a broad view of all risks and of the resources available to reduce them. Paul Slovic trusts the experts much less and the public somewhat more than Sunstein does, and he points out that insulating the experts from the emotions of the public produces policies that the public will reject—an impossible situation in a democracy. Both are eminently sensible, and I agree with both.
    Bayes’s rule specifies how prior beliefs (in the examples of this chapter, base rates) should be combined with the diagnosticity of the evidence, the degree to which it favors the hypothesis over the alternative.

    There are two ideas to keep in mind about Bayesian reasoning and how we tend to mess it up. The first is that base rates matter, even in the presence of evidence about the case at hand. This is often not intuitively obvious. The second is that intuitive impressions of the diagnosticity of evidence are often exaggerated. The combination of WYSIATI and associative coherence tends to make us believe in the stories we spin for ourselves. The essential
    keys to disciplined Bayesian reasoning can be simply summarized:
    - Anchor your judgment of the probability of an outcome on a plausible base rate.
    - Question the diagnosticity of your evidence.
    The word fallacy is used, in general, when people fail to apply a logical rule that is obviously relevant. Amos and I introduced the idea of a conjunction fallacy, which people commit when they judge a conjunction of two events (here, bank teller and feminist) to be more probable than one of the events (bank teller) in a direct comparison.
    As in the Müller-Lyer illusion, the fallacy remains attractive even when you recognize it for what it is.

    Representativeness belongs to a cluster of closely related basic assessments that are likely to be generated together. The most representative outcomes combine with the personality description to produce the most coherent stories. The most coherent stories are not necessarily the most probable, but they are plausible, and the notions of coherence, plausibility, and probability are easily confused by the unwary.
    Statistical base
    rates are facts about a population to which a case belongs, but they are not relevant to the individual case. Causal base rates change your view of how the individual case came to be. The two types of base-rate information are treated differently:
    - Statistical base rates are generally underweighted, and sometimes neglected altogether, when specific information about the case at hand is available.
    - Causal base rates are treated as information about the individual case and are easily combined with other case-specific information.

    Stereotyping is a bad word in our culture, but in my usage it is neutral. One of the basic characteristics of System 1 is that it represents categories as norms and prototypical exemplars. This is how we think of horses, refrigerators, and New York police officers; we hold in memory a representation of one or more “normal” members of each of these categories. When the categories are social, these representations are called stereotypes. Some stereotypes are perniciously wrong, and hostile stereotyping can have dreadful consequences, but the psychological facts cannot be avoided: stereotypes, both correct and false, are how we think of categories.

    Resistance to stereotyping is a laudable moral position, but the simplistic idea that the resistance is costless is wrong.
    Did students learn from the results of the helping experiment anything that significantly changed their way of thinking? The answer is straightforward: they learned nothing at all.
    (Овде ме фати многу смеа :rofl::rofl:)

    To teach students any psychology they did not know before, you must surprise them. But which surprise will do? Nisbett and Borgida found that when they presented their students with a surprising statistical fact, the students managed to learn nothing at all. But when the students were surprised by individual cases—two nice people who had not helped—they immediately made the generalization and inferred that helping is more difficult than they had thought. Nisbett and Borgida summarize the results in a memorable sentence:
    Subjects’ unwillingness to deduce the particular from the general was matched only by their willingness to infer the general from the particular.
    This is a profoundly important conclusion. People who are taught surprising statistical facts about human behavior may be impressed to the point of telling their friends about what they have heard, but this does not mean that their understanding of the world has really changed. The test of learning psychology is whether your understanding of situations you encounter has changed, not whether you have learned a new fact. There is a deep gap between our thinking about statistics and our thinking about individual cases. Statistical results with a causal interpretation have a stronger effect on our thinking than noncausal information. But even compelling causal statistics will not change long-held beliefs or beliefs rooted in personal experience. On the other hand, surprising individual cases have a powerful impact and are a more effective tool for teaching psychology because the incongruity must be resolved and embedded in a causal story.
    (Ова ми беше многу интересна поента, можеш да студираш психологија, а сепак да не ја сфаќаш суштината на појавите.)
    Our difficulties with the concept of regression originate with both System 1 and System 2. Without special instruction, and in quite a few cases even after some statistical instruction, the relationship between correlation and regression remains obscure. System 2 finds it difficult to understand and learn. This is due in part to the insistent demand for causal interpretations, which is a feature of System 1.
     
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  15. pdb123

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    Correcting your intuitive predictions is a task for System 2. Significant effort is required to find the relevant reference category, estimate the baseline prediction, and evaluate the quality of the evidence. The effort is justified only when the stakes are high and when you are particularly keen not to make mistakes. Furthermore, you should know that correcting your intuitions may complicate your life. A characteristic of unbiased predictions is that they permit the prediction of rare or extreme events only when the information is very good. If you expect your predictions to be of modest validity, you will never guess an outcome that is either rare or far from the mean. If your predictions are unbiased, you will never have the satisfying experience of correctly calling an extreme case.

    The objections to the principle of moderating intuitive predictions must be taken seriously, because absence of bias is not always what matters most. A preference for unbiased predictions is justified if all errors of prediction are treated alike, regardless of their direction. But there are situations in which one type of error is much worse than another. When a venture capitalist looks for “the next big thing,” the risk of missing the next Google or Facebook is far more important than the risk of making a modest investment in a start-up that ultimately fails. The goal of venture capitalists is to call the extreme cases correctly, even at the cost of overestimating the prospects of many other ventures. For a conservative banker making large loans, the risk of a single borrower going bankrupt may outweigh the risk of turning down several would-be clients who would fulfill their obligations. In such cases, the use of extreme language (“very good prospect,” “serious risk of default”) may have some justification for the comfort it provides, even if the information on which these judgments are based is of only modest validity.
    (Ова е интересна поента; цело време зборуваме за предрасуди и како поради нив правиме грешки, и сега тука се дискутира дека океј е некогаш да дозволиме предрасудите да ... пресудат (pun intended :smirk:))
    Extreme predictions and a willingness to predict rare events from weak evidence are both manifestations of System 1. It is natural for the associative machinery to match the extremeness of predictions to the perceived extremeness of evidence on which it is based—this is how substitution works. And it is natural for System 1 to generate overconfident judgments, because confidence, as we have seen, is determined by the coherence of the best story you can tell from the evidence at hand. Be warned: your intuitions will deliver predictions that are too extreme and you will be inclined to put far too much faith in them.
    Regression is also a problem for System 2. The very idea of regression to the mean is alien and difficult to communicate and comprehend. Galton had a hard time before he understood it. Many statistics teachers dread the class in which the topic comes up, and their students often end up with only a vague understanding of this crucial concept. This is a case where System 2 requires special training. Matching predictions to the evidence is not only something we do intuitively; it also seems a reasonable thing to do. We will not learn to understand regression from experience. Even when a regression is identified, as we saw in the story of the flight instructors, it
    will be given a causal interpretation that is almost always wrong.
    The trader-philosopher-statistician Nassim Taleb could also be considered a psychologist. In The Black Swan, Taleb introduced the notion of a narrative fallacy to describe how flawed stories of the past shape our views of the world and our expectations for the future. Narrative fallacies arise inevitably from our continuous attempt to make sense of the world. The explanatory stories that people find compelling are simple; are concrete rather than abstract; assign a larger role to talent, stupidity, and intentions than to luck; and focus on a few striking events that happened rather than on the countless events that failed to happen. Any recent salient event is a candidate to become the kernel of a causal narrative. Taleb suggests that we humans constantly fool ourselves by constructing flimsy accounts of the past and believing they are true.

    The ultimate test of an explanation is whether it would have made the event predictable in advance. No story of Google’s unlikely success will meet that test, because no story can include the myriad of events that would have caused a different outcome. The human mind does not deal well with nonevents. The fact that many of the important events that did occur involve choices further tempts you to exaggerate the role of skill and underestimate the part that luck played in the outcome. Because every critical decision turned out well, the record suggests almost flawless prescience—but bad luck could have disrupted any one of the successful steps. The halo effect adds the final touches, lending an aura of invincibility to the heroes of the story.

    You build the best possible story from the information available to you, and if it is a good story, you believe it. Paradoxically, it is easier to construct a coherent story when you know little, when there are fewer pieces to fit into the puzzle. Our comforting conviction that the world makes sense rests on a secure foundation: our almost unlimited ability to ignore our ignorance.

    We can know something only if it is both true and knowable.

    The core of the illusion is that we believe we understand the past, which implies that the future also should be knowable, but in fact we understand the past less than we believe we do. Know is not the only word that fosters this illusion. In common usage, the words intuition and premonition also are reserved for past thoughts that turned out to be true.
    A general limitation of the human mind is its imperfect ability to reconstruct past states of knowledge, or beliefs that have changed. Once you adopt a new view of the world (or of any part of it), you immediately lose much of your ability to recall what you used to believe before your mind changed.

    Your inability to reconstruct past beliefs will inevitably cause you to underestimate the extent to which you were surprised by past events. Baruch Fischh off first demonstrated this “I-knew-it-all-along” effect, or hindsight bias, when he was a student in Jerusalem.

    Hindsight bias has pernicious effects on the evaluations of decision makers. It leads observers to assess the quality of a decision not by whether the process was sound but by whether its outcome was good or bad... [ ] This outcome bias makes it almost impossible to evaluate a decision properly—in terms of the beliefs that were reasonable when the decision was made.
    Hindsight is especially unkind to decision makers who act as agents for others—physicians, financial advisers, third-base coaches, CEOs, social workers, diplomats, politicians. We are prone to blame decision makers for good decisions that worked out badly and to give them too little credit for successful movesecaр that appear obvious only after the fact. There is a clear outcome bias. When the outcomes are bad, the clients often blame their agents for not seeing the handwriting on the wall—forgetting that it was written in invisible ink that became legible only afterward. Actions that seemed prudent in foresight can look irresponsibly negligent in hindsight.

    The worse the consequence, the greater the hindsight bias.
    The sense-making machinery of System 1 makes us see the world as more tidy, simple, predictable, and coherent than it really is. The illusion that one has understood the past feeds the further illusion that one can predict and control the future. These illusions are comforting. They reduce the anxiety that we would experience if we allowed ourselves to fully acknowledge the uncertainties of existence.
    (само што сфатив дека погоре сум ја опишала оваа анксиозност :D)
    System 1 is designed to jump to conclusions from little evidence—and it is not designed to know the size of its jumps. Because of WYSIATI, only the evidence at hand counts. Because of confidence by coherence, the subjective confidence we have in our opinions reflects the coherence of the story that System 1 and System 2 have constructed. The amount of evidence and its quality do not count for much, because poor evidence can make a very good story. For some of our most important beliefs we have no evidence at all, except that people we love and trust hold these beliefs. Considering how little we know, the confidence we have in our beliefs is preposterous—and it is also essential.
    The illusion of skill is not only an individual aberration; it is deeply ingrained in the culture of the industry. Facts that challenge such basic assumptions—and thereby threaten people’s livelihood and self-esteem—are simply not absorbed. The mind does not digest them. This is particularly true of statistical studies of performance, which provide base-rate information that people generally ignore when it clashes with their personal impressions from experience.
    The idea that large historical events are determined by luck is profoundly shocking, although it is demonstrably
    true.
    (Shocking to finally realize it, indeed :nod:)

    But those with the most knowledge are often less reliable. The reason is that the person who acquires more knowledge develops an enhanced illusion of her skill and becomes unrealistically overconfident.
    (Ова 100 пати сум го помислила кога комуницирам со „поакадемски успешни“ луѓе, и многу ме нервира :))

    The more famous the forecaster, Tetlock discovered, the more flamboyant the forecasts. “Experts in demand,” he writes, “were more overconfident than their colleagues who eked out existences far from the limelight.”
    Tetlock also found that experts resisted admitting that they had been wrong, and when they were compelled to admit error, they had a large collection of excuses: they had been wrong only in their timing, an unforeseeable event had intervened, or they had been wrong but for the right reasons. Experts are just human in the end. They are dazzled by their own brilliance and hate to be wrong. Experts are led astray not by what they believe, but by how they think, says Tetlock. He uses the terminology from Isaiah Berlin’s essay on Tolstoy, “The Hedgehog and the Fox.” Hedgehogs “know one big thing” and have a theory about the world; they account for particular events within a coherent framework, bristle with impatience toward those who don’t see things their way, and are confident in their forecasts. They are also especially reluctant to admit error. For hedgehogs, a failed prediction is almost always “off only on timing” or “very nearly right.” They are opinionated and clear, which is exactly what television producers love to see on programs. Two hedgehogs on different sides of an issue, each attacking the idiotic ideas of the adversary, make for a good show.
    Foxes, by contrast, are complex thinkers. They don’t believe that one big thing drives the march of history (for example, they are unlikely to accept the view that Ronald Reagan single-handedly ended the cold war by standing tall against the Soviet Union). Instead the foxes recognize that reality emerges from the interactions of many different agents and forces, including blind luck, often producing large and unpredictable outcomes. It was the foxes who scored best in Tetlock’s study, although their performance was still very poor. They are less likely than hedgehogs to be invited to participate in television debates.
    The main point of this chapter is not that people who attempt to predict the future make many errors; that goes without saying. The first lesson is that errors of prediction are inevitable because the world is unpredictable. The second is that high subjective confidence is not to be trusted as an indicator of accuracy (low confidence could be more informative). Short-term trends can be forecast, and behavior and achievements can be predicted with fair accuracy from previous behaviors and achievements.
    Why are experts inferior to algorithms? One reason, which Meehl suspected, is that experts try to be clever, think outside the box, and consider complex combinations of features in making their predictions. Complexity may work in the odd case, but more often than not it reduces validity. Simple combinations of features are better.

    Another reason for the inferiority of expert judgment is that humans are incorrigibly inconsistent in making summary judgments of complex information. When asked to evaluate the same information twice, they frequently give different answers. The extent of the inconsistency is often a matter of real concern.
    (Читајќи го ова, имав чувство како некој друг да нè испитува и анализира - колку чудна сорта се овие луѓето, еднаш даваат еден, а друг пат друг одговор за иста работа, како златни рипки што забораваат на секои 5 секунди, за грев :rofl:)

    The widespread inconsistency is probably due to the extreme context dependency of System 1. We know from studies of priming that unnoticed stimuli in our environment have a substantial influence on our thoughts and actions. These influences fluctuate from moment to moment.
     
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    The prejudice against algorithms is magnified when the decisions are consequential. Meehl remarked, “I do not quite know how to alleviate the horror some clinicians seem to experience when they envisage a treatable case being denied treatment because a ‘blind, mechanical’ equation misclassifies him.” In contrast, Meehl and other proponents of algorithms have argued strongly that it is unethical to rely on intuitive judgments for important decisions if an algorithm is available that will make fewer mistakes. Their rational argument is compelling, but it runs against a stubborn psychological reality: for most people, the cause of a mistake matters. The story of a child dying because an algorithm made a mistake is more poignant than the story of the same tragedy occurring as a result of human error, and the difference in emotional intensity is readily translated into a moral preference.
    (Навистина е нелогично да сме вакви, а сепак го разбирам и се поистоветувам со овој ефект.)
    The big surprise to me was that the intuitive judgment that the interviewers summoned up in the “close your eyes” exercise also did very well, indeed just as well as the sum of the six specific ratings. I learned from this finding a lesson that I have never forgotten: intuition adds value even in the justly derided selection interview, but only after a disciplined collection of objective information and disciplined scoring of separate traits. I set a formula that gave the “close your eyes” evaluation the same weight as the sum of the six trait ratings. A more general lesson that I learned from this episode was do not simply trust intuitive judgment—your own or that of others—but do not dismiss it, either.
    I quoted Herbert Simon’s definition of intuition in the introduction, but it will make more sense when I repeat it now: “The situation has provided a cue; this cue has given the expert access to information stored in memory, and the information provides the answer. Intuition is nothing more and nothing less than recognition.”
    Earlier I traced people’s confidence in a belief to two related impressions: cognitive ease and coherence. We are confident when the story we tell ourselves comes easily to mind, with no contradiction and no competing scenario. But ease and coherence do not guarantee that a belief held with confidence is true. The associative machine is set to suppress doubt and to evoke ideas and information that are compatible with the currently dominant story. A mind that follows WYSIATI will achieve high confidence much too easily by ignoring what it does not know. It is therefore not surprising that many of us are prone to have high confidence in unfounded intuitions.

    If subjective confidence is not to be trusted, how can we evaluate the probable validity of an intuitive judgment? When do judgments reflect true expertise? When do they display an illusion of validity? The answer comes from the two basic conditions for acquiring a skill:
    - an environment that is sufficiently regular to be predictable
    - an opportunity to learn these regularities through prolonged practice
    When both these conditions are satisfied, intuitions are likely to be skilled.

    Physicians, nurses, athletes, and firefighters also face complex but fundamentally orderly situations. The accurate intuitions that Gary Klein has described are due to highly valid cues that es the expert’s System 1 has learned to use, even if System 2 has not learned to name them. In contrast, stock pickers and political scientists who make long-term forecasts operate in a zero-validity environment. Their failures reflect the basic unpredictability of the events that they try to forecast.
    Some environments are worse than irregular. Robin Hogarth described “wicked” environments, in which professionals are likely to learn the wrong lessons from experience.

    Statistical algorithms greatly outdo humans in noisy environments for two reasons: they are more likely than human judges to detect weakly valid cues and much more likely to maintain a modest level of accuracy by using
    such cues consistently.
    Expertise is not a single skill; it is a collection of skills, and the same professional may be highly expert in some of the tasks in her domain while remaining a novice in others.
    “Pallid” statistical information is routinely discarded when it is incompatible with one’s personal impressions of a case. In the competition with the inside view, the outside view doesn’t stand a chance.
    The preference for the inside view sometimes carries moral overtones.
    The prevalent tendency to underweight or ignore distributional information is perhaps the major source of error in forecasting. Planners should therefore make every effort to frame the forecasting problem so as to facilitate utilizing all the distributional information that is available.
    Psychologists have confirmed that most people genuinely believe that they are superior to most others on most desirable traits—they are willing to bet small amounts of money on these beliefs in the laboratory.
    (Не мислам дека ова некого го изненади, но добро е да го видиш „официјално“ потврдено :D)
    - We focus on our goal, anchor on our plan, and neglect relevant base rates, exposing ourselves to the planning fallacy.
    - We focus on what we want to do and can do, neglecting the plans and skills of others.
    - Both in explaining the past and in predicting the future, we focus on the causal role of skill and neglect the role of luck. We are therefore prone to an illusion of control.
    - We focus on what we know and neglect what we do not know, which makes us overly confident in our beliefs.
    Overconfidence is another manifestation of WYSIATI: when we estimate a quantity, we rely on information that comes to mind and construct a coherent story in which the estimate makes sense. Allowing for the information that does not come to mind—perhaps because one never knew it—is impossible.

    Experts who acknowledge the full extent of their ignorance may expect to be replaced by more confident competitors, who are better able to gain the trust of clients. An unbiased appreciation of uncertainty is a cornerstone of rationality—but it is not what people and organizations want. Extreme uncertainty is paralyzing under dangerous circumstances, and the admission that one is merely guessing is especially unacceptable when
    the stakes are high. Acting on pretended knowledge is often the preferred solution.
    (Еден од начините на кој животот е нефер (lalala))

    The effects of high optimism on decision making are, at best, a mixed blessing, but the contribution of optimism to good implementation is certainly positive. The main benefit of optimism is resilience in the face of setbacks. According to Martin Seligman, the founder of positive psychology, an “optimistic explanation style” contributes to resilience by defending one’s self-image. In essence, the optimistic style involves taking credit for successes but little blame for failures.
    (How convenient :D)
    Can overconfident optimism be overcome by training? I am not optimistic. There have been numerous attempts to train people to state confidence intervals that reflect the imprecision of their judgments, with only a few reports of modest success... [ ] overconfidence is a direct consequence of features of System 1 that can be tamed—but not vanquished. The main obstacle is that subjective confidence is determined by the coherence of the story one has constructed, not by the quality and amount of the information that supports it.
    Economists adopted expected utility theory in a dual role: as a logic that prescribes how decisions should be made, and as a description of how Econs make choices.
    The psychological value of a gamble is therefore not the weighted average of its possible dollar outcomes; it is the average of the utilities of these outcomes, each weighted by its probability.
    (Морам да признаам дека зборот utility ми правеше потешкотии во разбирањето на смислата на останатите поенти, некако како тежина да им даваше и ми правеше да звучи покомплицирана отколку што е)

    The mystery is how a conception of the utility of outcomes that is vulnerable to such obvious counterexamples survived for so long. I can explain it only by a weakness of the scholarly mind that I have often observed in myself. I call it theory-induced blindness: once you have accepted a theory and used it as a tool in your thinking, it is extraordinarily difficult to notice its flaws. If you come upon an observation that does not seem to fit the model, you assume that there must be a perfectly good explanation that you are somehow missing. You give the theory the benefit of the doubt, trusting the community of experts who have accepted it.
    The reason you like the idea of gaining $100 and dislike the idea of losing $100 is not that these amounts change your wealth. You just like winning and dislike losing —and you almost certainly dislike losing more than you like winning.
    The four problems highlight the weakness of Bernoulli’s model. His theory is too simple and lacks a moving part. The missing variable is the reference point, the earlier state relative to which gains and losses are evaluated. In Bernoulli’s theory you need to know only the state of wealth to determine its utility, but in prospect theory you also need to know the reference state. Prospect theory is therefore more complex than utility theory. In science complexity is considered a cost, which must be justified by a sufficiently rich set of new and (preferably) interesting predictions of facts that the existing theory cannot explain. This was the challenge we had to meet.
    Although Amos and I were not working with the two-systems model of the mind, it’s clear now that there are three cognitive features at the heart of prospect theory. They play an essential role in the evaluation of financial outcomes and are common to many automatic processes of perception, judgment, and emotion. They should be seen as operating characteristics of System 1.
    - Evaluation is relative to a neutral reference point, which is sometimes referred to as an “adaptation level.”... [ ]
    Outcomes that are better than the reference points are gains. Below the reference point they are losses.
    - A principle of diminishing sensitivity applies to both sensory dimensions and the evaluation of changes of wealth. Turning on a weak light has a large effect in a dark room. The same increment of light may be undetectable in a brightly illuminated room. Similarly, the subjective difference between $900 and $1,000 is much smaller than the difference between $100 and $200.
    - The third principle is loss aversion. When directly compared or weighted against each other, losses loom larger than gains. This asymmetry between the power of positive and negative expectations or experiences has an evolutionary history. Organisms that treat threats as more urgent than opportunities have a better chance to survive and reproduce.
    The “loss aversion ratio” has been estimated in several experiments and is usually in the range of 1.5 to 2.5.

    As you carried out this exercise, you probably found that your loss aversion coefficient tends to increase when the stakes rise, but not dramatically. All bets are off, of course, if the possible loss is potentially ruinous, or if your lifestyle is threatened. The loss aversion coefficient is very large in such cases and may even be infinite—there are risks that you will not accept, regardless of how many millions you might stand to win if you are lucky.
    It is fair to say that these models have had less influence than prospect theory, and the reason is instructive. The emotions of regret and disappointment are real, and decision makers surely anticipate these emotions when making their choices. The problem is that regret theories make few striking predictions that would distinguish them from prospect theory, which has the advantage of being simpler. The complexity of prospect theory was more acceptable in the competition with expected utility theory because it did predict observations that expected utility theory could not explain.
    Richer and more realistic assumptions do not suffice to make a theory successful. Scientists use theories as a bag of working tools, and they will not take on the burden of a heavier bag unless the new tools are very useful. Prospect theory was accepted by many scholars not because it is “true” but because the concepts that it added to utility theory, notably the reference point and loss aversion, were worth the trouble; they yielded new predictions that turned out to be true. We were lucky.
    What distinguishes these market transactions from Professor R’s reluctance to sell his wine, or the reluctance of Super Bowl ticket holders to sell even at a very high price? The distinctive feature is that both the shoes the merchant sells you and the money you spend from your budget for shoes are held “for exchange.” They are intended to be traded for other goods. Other goods, such as wine and Super Bowl tickets, are held “for use,” to be consumed or otherwise enjoyed. Your leisure time and the standard of living that your income supports are also not intended for sale or exchange.

    Loss aversion is built into the automatic evaluations of System 1.

    Selling goods that one would normally use activates regions of the brain that are associated with disgust and pain. Buying also activates these areas, but only when the prices are perceived as too high—when you feel that a seller is taking money that exceeds the exchange value. Brain recordings also indicate that buying at especially low prices is a pleasurable event.
     
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  17. pdb123

    pdb123 Популарен член

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    The experimental economist John List, who has studied trading at baseball card conventions, found that novice traders were reluctant to part with the cards they owned, but that this reluctance eventually disappeared with trading experience.

    Recent studies of the psychology of “decision making under poverty” suggest that the poor are another group in which we do not expect to find the endowment effect. Being poor, in prospect theory, is living below one’s reference point. There are goods that the poor need and cannot afford, so they are always “in the losses.” Small amounts of money that they receive are therefore perceived as a reduced loss, not as a gain. The money helps
    one climb a little toward the reference point, but the poor always remain on the steep limb of the value function.
    People who are poor think like traders, but the dynamics are quite different. Unlike traders, the poor are not indifferent to the differences between gaining and giving up. Their problem is that all their choices are between losses. Money that is spent on one good is the loss of another good that could have been purchased instead. For the poor, costs are losses.
    The same circuit also causes schematic angry faces (a potential threat) to be processed faster and more efficiently than schematic happy faces. Some experimenters have reported that an angry face “pops out” of a crowd of happy faces, but a single happy face does not stand out in an angry crowd. The brains of humans and other animals contain a mechanism that is designed to give priority to bad news. By shaving a few hundredths of a second from the time needed to detect a predator, this circuit improves the animal’s odds of living long enough to reproduce. The automatic operations of System 1 reflect this evolutionary history. No comparably rapid mechanism for recognizing good news has been detected. Of course, we and our animal cousins are quickly alerted to signs of opportunities to mate or to feed, and advertisers design billboards accordingly. Still, threats are privileged above opportunities, as they should be.

    Other scholars, in a paper titled “Bad Is Stronger Than Good,” summarized the evidence as follows: “Bad emotions, bad parents, and bad feedback have more impact than good ones, and bad information is processed more thoroughly than good. The self is more motivated to avoid bad self-definitions than to pursue good ones. Bad impressions and bad stereotypes are quicker to form and more resistant to disconfirmation than good ones.”
    Loss aversion refers to the relative strength of two motives: we are driven more strongly to avoid losses than to achieve gains. A reference point is sometimes the status quo, but it can also be a goal in the future: not achieving a goal is a loss, exceeding the goal is a gain. As we might expect from negativity dominance, the two motives are not equally powerful. The aversion to the failure of not reaching the goal is much stronger than the desire to exceed it.
    The firm has its own entitlement, which is to retain its current profit. If it faces a threat of a loss, it is allowed to transfer the loss to others. A substantial majority of respondents believed that it is not unfair for a firm to reduce its workers’ wages when its profitability is falling. We described the rules as defining dual entitlements to the firm and to individuals with whom it interacts. When threatened, it is not unfair for the firm to be selfish. It is not even expected to take on part of the losses; it can pass them on.
    Different rules governed what the firm could do to improve its profits or to avoid reduced profits. When a firm faced lower production costs, the rules of fairness did not require it to share the bonanza with either its customers or its workers. Of course, our respondents liked a firm better and described it as more fair if it was generous when its profits increased, but they did not brand as unfair a firm that did not share.

    Unfairly imposing losses on people can be risky if the victims are in a position to retaliate. Furthermore, experiments have shown that strangers who observe unfair behavior often join in the punishment.

    The influence of loss aversion and entitlements extends far beyond the realm of financial transactions. Jurists were quick to recognize their impact on the law and in the administration of justice. In one study, David Cohen and Jack Knetsch found many examples of a sharp distinction between actual losses and foregone gains in legal decisions. For example, a merchant whose goods were lost in transit may be compensated for costs he actually incurred, but is unlikely to be compensated for lost profits.
    Possibility and certainty have similarly powerful effects in the domain of losses. When a loved one is wheeled into surgery, a 5% risk that an amputation will be necessary is very bad—much more than half as bad as a 10% risk. Because of the possibility effect, we tend to overweight small risks and are willing to pay far more than expected value to eliminate them altogether. The psychological difference between a 95% risk of disaster and the certainty of disaster appears to be even greater; the sliver of hope that everything could still be okay looms very large. Overweighting of small probabilities increases the attractiveness of both gambles and insurance policies.
    The conclusion is straightforward: the decision weights that people assign to outcomes are not identical to the probabilities of these outcomes, contrary to the expectation principle. Improbable outcomes are overweighted—this is the possibility effect. Outcomes that are almost certain are underweighted relative to actual certainty. The expectation principle, by which values are weighted by their probability, is poor psychology.
    The combination of the certainty effect and possibility effects at the two ends of the probability scale is inevitably accompanied by inadequate sensitivity to intermediate probabilities.

    Probabilities that are extremely low or high (below 1% or above 99%) are a special case. It is difficult to assign a unique decision weight to very rare events, because they are sometimes ignored altogether, effectively assigned a decision weight of zero. On the other hand, when you do not ignore the very rare events, you will certainly overweight them.

    When you pay attention to a threat, you worry—and the decision weights reflect how much you worry. Because of the possibility effect, the worry is not proportional to the probability of the threat. Reducing or mitigating the risk is not adequate; to eliminate the worry the probability must be brought down to zero.
    When Amos and I began our work on prospect theory, we quickly reached two conclusions: people attach values to gains and losses rather than to wealth, and the decision weights that they assign to outcomes are different from probabilities.

    First, there is diminishing sensitivity. The sure loss is very aversive because the reaction to a loss of $900 is more than 90% as intense as the reaction to a loss of $1,000. The second factor may be even more powerful: the decision weight that corresponds to a probability of 90% is only about 71, much lower than the probability. The result is that when you consider a choice between a sure loss and a gamble with a high probability of a larger loss, diminishing sensitivity makes the sure loss more aversive, and the certainty effect reduces the aversiveness of the gamble. The same two factors enhance the attractiveness of the sure thing and reduce the attractiveness of the
    gamble when the outcomes are positive.
    My experience illustrates how terrorism works and why it is so effective: it induces an availability cascade. An extremely vivid image of death and damage, constantly reinforced by media attention and frequent conversations, becomes highly accessible, especially if it is associated with a specific situation such as the sight of a bus. The emotional arousal is associative, automatic, and uncontrolled, and it produces an impulse for protective action. System 2 may “know” that the probability is low, but this knowledge does not eliminate the self-generated discomfort and the wish to avoid it. System 1 cannot be turned off. The emotion is not only disproportionate to the probability, it is also insensitive to the exact level of probability.

    Emotion and vividness influence fluency, availability, and judgments of probability—and thus account for our excessive response to the few rare events that we do not ignore.
    - People overestimate the probabilities of unlikely events.
    - People overweight unlikely events in their decisions.
    As predicted by denominator neglect, low-probability events are much more heavily weighted when described in terms of relative frequencies (how many) than when stated in more abstract terms of “chances,” “risk,” or “probability” (how likely). As we have seen, System 1 is much better at dealing with individuals than categories.
    The evidence suggests the hypothesis that focal attention and salience contribute to both the overestimation of unlikely events and the overweighting of unlikely outcomes. Salience is enhanced by mere mention of an event, by its vividness, and by the format in which probability is described. There are exceptions, of course, in which focusing on an event does not raise its probability: cases in which an erroneous theory makes an event appear impossible even when you think about it, or cases in which an inability to imagine how an outcome might come about leaves you convinced that it will not happen. The bias toward overestimation and overweighting of salient events is not an absolute rule, but it is large and robust.

    In sharp contrast, overweighting is never observed in choice from experience, and underweighting is common.
    The experimental situation of choice by experience is intended to represent many situations in which we are exposed to variable outcomes from the same source. A restaurant that is usually good may occasionally serve a brilliant or an awful meal. Your friend is usually good company, but he sometimes turns moody and aggressive. California is prone to earthquakes, but they happen rarely. The results of many experiments suggest that rare events are not overweighted when we make decisions such as choosing a restaurant or tying down the boiler to reduce earthquake damage.

    The conditions under which rare events are ignored or overweighted are better understood now than they were when prospect theory was formulated. The probability of a rare event will (often, not always) be overestimated, because of the confirmatory bias of memory. Thinking about that event, you try to make it true in your mind. A rare event will be overweighted if it specifically attracts attention. Separate attention is effectively guaranteed when prospects are described explicitly (“99% chance to win $1,000, and 1% chance to win nothing”). Obsessive concerns (the bus in Jerusalem), vivid images (the roses), concrete representations (1 of 1,000), and explicit reminders (as in choice from description) all contribute to overweighting. And when there is no overweighting, there will be neglect. When it comes to rare probabilities, our mind is not designed to get things quite right.
    The ideal of logical consistency, as this example shows, is not achievable by our limited mind. Because we are susceptible to WYSIATI and averse to mental effort, we tend to make decisions as problems arise, even when we are specifically instructed to consider them jointly. We have neither the inclination nor the mental resources to enforce consistency on our preferences, and our preferences are not magically set to be coherent, as they are in the rational-agent model.
    The outside view and the risk policy are remedies against two distinct biases that affect many decisions: the exaggerated optimism of the planning fallacy and the exaggerated caution induced by loss aversion.
    You need money to cover the costs of your daughter’s wedding and will have to sell some stock. You remember the price at which you bought each stock and can identify it as a “winner,” currently worth more than you paid for it, or as a loser. Among the stocks you own, Blueberry Tiles is a winner; if you sell it today you will have achieved a gain of $5,000. You hold an equal investment in Tiffany Motors, which is currently worth $5,000 less than you paid for it. The value of both stocks has been stable in recent weeks. Which are you more likely to sell?
    A plausible way to formulate the choice is this: “I could close the Blueberry Tiles account and score a success for my record as an investor. Alternatively, I could close the Tiffany Motors account and add a failure to my record. Which would I rather do?” If the problem is framed as a choice between giving yourself pleasure and causing yourself pain, you will certainly sell Blueberry Tiles and enjoy your investment prowess. As might be expected, finance research has documented a massive preference for selling winners rather than losers—a bias that has been given an opaque label: the disposition effect.

    The decision to invest additional resources in a losing account, when better investments are available, is known as the sunk-cost fallacy, a costly mistake that is observed in decisions large and small. Driving into the blizzard because one paid for tickets is a sunk-cost error.
    The emotional state has been well described by two Dutch psychologists, who noted that regret is “accompanied by feelings that one should have known better, by a sinking feeling, by thoughts about the mistake one has made and the opportunities lost, by a tendency to kick oneself and to correct one’s mistake, and by wanting to undo the event and to get a second chance.” Intense regret is what you experience when you can most easily imagine yourself doing something other than what you did.
    (Преубав опис :D)

    ...people expect to have stronger emotional reactions (including regret) to an outcome that is produced by action than to the same outcome when it is produced by inaction.
     
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  18. pdb123

    pdb123 Популарен член

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    The intense aversion to trading increased risk for some other advantage plays out on a grand scale in the laws and regulations governing risk. This trend is especially strong in Europe, where the precautionary principle, which prohibits any action that might cause harm, is a widely accepted doctrine. In the regulatory context, the precautionary principle imposes the entire burden of proving safety on anyone who undertakes actions that might harm people or the environment. Multiple international bodies have specified that the absence of scientific evidence of potential damage is not sufficient justification for taking risks. As the jurist Cass Sunstein points out, the precautionary principle is costly, and when interpreted strictly it can be paralyzing. He mentions an impressive list of innovations that would not have passed the test, including “airplanes, air conditioning, antibiotics, automobiles, chlorine, the measles vaccine, open-heart surgery, radio, refrigeration, smallpox vaccine, and X-rays.” The strong version of the precautionary principle is obviously untenable. But enhanced loss aversion is embedded in a strong and widely shared moral intuition; it originates in System 1. The dilemma between intensely loss-averse moral attitudes and efficient risk management does not have a simple and compelling solution.
    (Од неодамна се запознав со оваа „философија“ на Европа, па ми беше мило уште еднаш да си го потврдам :D)

    Daniel Gilbert and his colleagues provocatively claim that people generally anticipate more regret than they will actually experience, because they underestimate the efficacy of the psychological defenses they will deploy—which they label the “psychological immune system.” Their recommendation is that you should not put too much weight on regret; even if you have some, it will hurt less than you now think.
    (Уште да успеам да ја вградам оваа поента во мозокот и топ ќе сум :D)
    The features that caused the difference between the judgments of the options in single evaluation—the poignancy of the victim being in the wrong grocery store and the anchoring on the prize—are suppressed or irrelevant when the options are evaluated jointly. The emotional reactions of System 1 are much more likely to determine single evaluation; the comparison that occurs in joint evaluation always involves a more careful and effortful assessment, which calls for System 2.
    Christopher Hsee, of the University of Chicago, has contributed the following example of preference reversal, among many others of the same type. The objects to be evaluated are secondhand music dictionaries.
    Dictionary A Dictionary B
    Year of publication 1993 1993
    Number of entries 10,000 20,000
    Condition Like new Cover torn, otherwise like new
    When the dictionaries are presented in single evaluation, dictionary A is valued more highly, but of course the preference changes in joint evaluation. The result illustrates Hsee’s evaluability hypothesis: The number of entries is given no weight in single evaluation, because the numbers are not “evaluable” on their own. In joint evaluation, in contrast, it is immediately obvious that dictionary B is superior on this attribute, and it is also apparent that the number of entries is far more important than the condition of the cover.
    As we have seen, rationality is generally served by broader and more comprehensive frames, and joint evaluation is obviously broader than single evaluation. Of course, you should be wary of joint evaluation when someone who controls what you see has a vested interest in what you choose. Salespeople quickly learn that manipulation of the context in which customers see a good can profoundly influence preferences. Except for such cases of deliberate manipulation, there is a presumption that the comparative judgment, which necessarily involves System 2, is more likely to be stable than single evaluations, which often reflect the intensity of emotional responses of System 1.

    The system of administrative penalties is coherent within agencies but incoherent globally.
    A bad outcome is much more acceptable if it is framed as the cost of a lottery ticket that did not win than if it is simply described as losing a gamble. We should not be surprised: losses evokes stronger negative feelings than costs. Choices are not reality-bound because System 1 is not reality-bound.

    Unless there is an obvious reason to do otherwise, most of us passively accept decision problems as they are framed and therefore rarely have an opportunity to discover the extent to which our preferences are frame-bound rather than reality-bound.
    Your moral feelings are attached to frames, to descriptions of reality rather than to reality itself. The message about the nature of framing is stark: framing should not be viewed as an intervention that masks or distorts an underlying preference. At least in this instance—and also in the problems of the Asian disease and of surgery versus radiation for lung cancer—there is no underlying preference that is masked or distorted by the frame. Our preferences are about framed problems, and our moral intuitions are about descriptions, not about substance.
    We noted that:
    - If the objective is to reduce patients’ memory of pain, lowering the peak intensity of pain could be more important than minimizing the duration of the procedure. By the same reasoning, gradual relief may be preferable to abrupt relief if patients retain a better memory when the pain at the end of the procedure is relatively mild.
    - If the objective is to reduce the amount of pain actually experienced, conducting the procedure swiftly may be appropriate even if doing so increases the peak pain intensity and leaves patients with an awful memory.

    What we learn from the past is to maximize the qualities of our future memories, not necessarily of our future experience.
    (Многу добро сумирање на целата поента околу the experiencing и the remembering self. Всушност, и самата поента за постоењето на овие два дела ми е интересна.)
    Decisions that do not produce the best possible experience and erroneous forecasts of future feelings—both are bad news for believers in the rationality of choice. The cold-hand study showed that we cannot fully trust our preferences to reflect our interests, even if they are based on personal experience, and even if the memory of that experience was laid down within the last quarter of an hour! Tastes and decisions are shaped by memories, and the memories can be wrong. The evidence presents a profound challenge to the idea that humans have consistent preferences and know how to maximize them, a cornerstone of the rational-agent model. An inconsistency is built into the design of our minds. We have strong preferences about the duration of our experiences of pain and pleasure. We want pain to be brief and pleasure to last. But our memory, a function of System 1, has evolved to represent the most intense moment of an episode of pain or pleasure (the peak) and the feelings when the episode was at its end. A memory that neglects duration will not serve our preference for long pleasure and short pains.
    It is not only at the opera that we think of life as a story and wish it to end well. When we hear about the death of a woman who had been estranged from her daughter for many years, we want to know whether they were reconciled as death approached. We do not care only about the daughter’s feelings—it is the narrative of the mother’s life that we wish to improve. Caring for people often takes the form of concern for the quality of their stories, not for their feelings. Indeed, we can be deeply moved even by events that change the stories of people who are already dead. We feel pity for a man who died believing in his wife’s love for him, when we hear that she had a lover for many years and stayed with her husband only for his money. We pity the husband although he had lived a happy life. We feel the humiliation of a scientist who made an important discovery that was proved false after she died, although she did not experience the humiliation. Most important, of course, we all care intensely for the narrative of our own life and very much want it to be a good story, with a decent hero.
    (Повторно, колку чудно и логично размислуваме, зарем не? :))

    The pains of labor and the benefits of vacations always come up as objections to the idea of duration neglect: we all share the intuition that it is much worse for labor to last 24 than 6 hours, and that 6 days at a good resort is better than 3. Duration appears to matter in these situations, but this is only because the quality of the end changes with the length of the episode. The mother is more depleted and helpless after 24 hours than after 6, and the vacationer is more refreshed and rested after 6 days than after 3. What truly matters when we intuitively assess such episodes is the progressive deterioration or improvement of the ongoing experience, and how the person feels at the end.
    Odd as it may seem, I am my remembering self, and the experiencing self, who does my living, is like a stranger to me.
    :clap::clap::clap:
    But of course your current mood is not the only thing that comes to mind when you are asked to evaluate your life. You are likely to be reminded of significant events in your recent past or near future; of recurrent concerns, such as the health of a spouse or the bad company that your teenager keeps; of important achievements and painful failures. A few ideas that are relevant to the question will occur to you; many others will not. Even when it is not influenced by completely irrelevant accidents such as the coin on the machine, the score that you quickly assign to your life is determined by a small sample of highly available ideas, not by a careful weighting of the domains of your life.

    One reason for the low correlations between individuals’ circumstances and their satisfaction with life is that both experienced happiness and life satisfaction are largely determined by the genetics of temperament. A disposition for well-being is as heritable as height or intelligence, as demonstrated by studies of twins separated at birth. People who appear equally fortunate vary greatly in how happy they are.

    In part because of these findings I have changed my mind about the definition of well-being. The goals that people set for themselves are so important to what they do and how they feel about it that an exclusive focus on experienced well-being is not tenable. We cannot hold a concept of well-being that ignores what people want. On the other hand, it is also true that a concept of well-being that ignores how people feel as they live and focuses only on how they feel when they think about their life is also untenable. We must accept the complexities of a hybrid view, in which the well-being of both selves is considered.
    This is the essence of the focusing illusion, which can be described in a single sentence:
    Nothing in life is as important as you think it is when you are thinking about it.

    Thoughts of any aspect of life are more likely to be salient if a contrasting alternative is highly available.

    The focusing illusion creates a bias in favor of goods and experiences that are initially exciting, even if they will eventually lose their appeal. Time is neglected, causing experiences that will retain their attention value in the long term to be appreciated less than they deserve to be.
    It is logical to
    describe the life of the experiencing self as a series of moments, each with a value. The value of an episode—I have called it a hedonimeter total—is simply the sum of the values of its moments. But this is not how the mind represents episodes. The remembering self, as I have described it, also tells stories and makes choices, and neither the stories nor the choices properly represent time. In storytelling mode, an episode is represented by a few critical moments, especially the beginning, the peak, and the end. Duration is neglected. We saw this focus on singular moments both in the cold-hand situation and in Violetta’s story.
     
    Последна измена: 11 април 2021
    На Bezimenka90, sweet-cherry и Lella им се допаѓа ова.
  19. pdb123

    pdb123 Популарен член

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    9/9

    The neglect of duration combined with the peak-end rule causes a bias that favors a short period of intense joy over a long period of moderate happiness. The mirror image of the same bias makes us fear a short period of intense but tolerable suffering more than we fear a much longer period of moderate pain. Duration neglect also makes us prone to accept a long period of mild unpleasantness because the end will be better, and it favors giving up an opportunity for a long happy period if it is likely to have a poor ending.

    In contrast, the duration-weighted conception of well-being treats all moments of life alike, memorable or not. Some moments end up weighted more than others, either because they are memorable or because they are important. The time that people spend dwelling on a memorable moment should be included in its duration, adding to its weight. A moment can also gain importance by altering the experience of subsequent moments... [ ] In the duration-weighted perspective, we can determine only after the fact that a moment is memorable or meaningful.

    The logic of duration weighting is compelling, but it cannot be considered a complete theory of well-being because individuals identify with their remembering self and care about their story. A theory of well-being that ignores what people want cannot be sustained. On the other hand, a theory that ignores what actually happens in people’s lives and focuses exclusively on what they think about their life is not tenable either. The remembering self and the experiencing self must both be considered, because their interests do not always coincide. Philosophers could
    struggle with these questions for a long time.
    Intuitive answers come to mind quickly and confidently, whether they originate from skills or from heuristics. There is no simple way for System 2 to distinguish between a skilled and a heuristic response. Its only recourse is to slow down and attempt to construct an answer on its own, which it is reluctant to do because it is indolent.

    Мислев дека никогаш нема да завршам со цитатите, ми требаа саати да ги ставам, и тоа само ги копирав :tmi:.

    Дали ќе продолжуваме со следна книга?
     
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  20. Lella

    Lella Форумски идол

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    Имав чувство дека некој ќе пише во темава деновиве. :D (Или... имам hindsight bias :lol:)

    Книгава стварно беше малце pain in the ass за читање. Ја почнав веднаш по колоквиуми и си реков дали сериозно седнав да читам книга што е lowkey учебник? Сепак, дефинитивно беше интересна, му се допаѓа на мојот remembering self. :D Навистина те тера да си ги преиспитуваш сите одлуки на дневна база. Се сеќавам во деновите додека ја читав постојано се прекинував и пробував да си ги објаснам работите преку логиката на Канеман. Пример и сега скоро додека полагав, гледам дека заглавувам на некое прашање и одма ми текнува на активирањето на Систем 2 и како се препознава преку зениците, и си спомнувам „сигурно зениците не ми се дилатирани, нема надеж за Систем 2 тука“. :D

    Кога ја читав книгава во ноутс додавав сè што ќе ми падне на памет што би било вредно за коментирање, ама сега разгледувајќи што сум пишувала, за пола од тоа немам појма што сум мислела. :?:

    Океј, нешто рандом ми текна кога читав дека Систем 1 е заслужен за контрола на емоциите, однесувањето и сл., и нели додека Систем 2 е зафатен со нешто, Систем 1 потфрла во оваа задача. Сега, не сум сигурна колку ова е валиден пример, ама кога бев во средно и кога требаше да решаваме задачи математика заедно летаа многу повеќе пцовки од обично и многу по-rude бевме едни со други. Има логика да снемаш филтер додека се концентрираш.

    Најинтересните моменти во книгава ми беа кога детално навлегуваше во работи кои одвреме-навреме ти се вртат in the back of you mind ама никогаш не си знаел дека постои научно објаснување. Пример, прајминг ефектот, анчоринг исто така, а и интуитивната проценка на веројатности (која всушност ја сретнавме во минатата книга). Прашањето беше која од трите низи е најверојатнa (кога се работи за родени машки или женски деца):
    BBBGGG
    GGGGGG
    BGBBGB
    Одоговорот е дека сите се подеднакво веројатни бидејќи сите букви се индивидуални и не зависат од тоа што има пред и по нив. Ама нашиот monkey brain е истрениран да очекува дека рандом низа изгледа како третата, а не како првите две, па затоа ни е тешко да го граспнеме ова.

    Слично нешто за што ми требаше ментална гимнастика за да се разубедам сама себе од моите интуитивни заблуди беше проблемот со тенисерот. Што е поверојатно:
    А. Да го добие натпреварот
    Б. Да го загуби првиот сет
    В. Да го загуби првиот сет, но да го добие натпреварот
    Г. Да го добие првиот сет, но да го загуби натпреварот

    Бидејќи знаеме дека иако го загубил првиот сет, најверојатно пак ќе победи, мислиме опцијата кај што го добива натпреварот е ултимативно поверојатна, ама логиката вели дека не е така. Не може еден настан да е помалку веројатен од неговата комбинација со друг настан.

    Најнеомилена глава ми беше Choices. Особено кога запна за економските делови, ќе се фрлев низ прозор од досада, не знам како ги преживеав тие делови. :D Не дека не е интересна prospect theory. Навистина е intriguing како не сакаме да ризикуваме кога имаме избор меѓу сигурна добивка и gamble, а сакаме да ризикуваме кога се работи за сигурна загуба и gamble. Интересно е, ама ако посветам повеќе од еден пасус на ова ќе си ја искорнам косата. Kudos до секој на светов што се занимава со економија, за мене би било тортура.

    И мене ова за ескпертите ми беше многу интересен дел. Луѓето што се нарекуваат себеси експерти (главно во областите каде се бараат одлуки базирани на предвидувања ((((економија)))) се всушност експерти сами за себе и пробуваат да го навигираат непредвидливиот свет иако во големата слика не прават ништо. И фала богу сите експерти ќе се бунат на ова, ама Канеман просто не може ништо друго да понуди како одговор освен статистиките, што дури и да сака не може да ги смени.

    Сепак, не мислам дека пристапот му беше да им го намали кредибилитетот или нешто такво. Дебатава алгоритам vs. човек не е нова, и факт е дека алгоритмите имаат многу помала шанса за грешка. Дизајнирани се за да ги немаат тие biases кои Канеман преку бројните експерименти одново и одново покажа дека ги имаме. Мислам дека поентата што може да се извлече од ова не е дека не можеме да им веруваме на експертите, туку дека не можеме да им веруваме повеќе отколку на алгоритмите. Дека во битката експерт против алгоритам губат, ама во експерт против обичен смртник секако победуваат. :D

    А и мислам дека на почеток некаде спомна дека искуствата што се повторуваат се „вгнездуваат“ во Систем 1, така што експертите имаат еден вид вградена статистичка интуиција. Ова се спомнуваше во Blink, која ми беше на ред за читање веднаш по оваа, коинцидентно без да знам дека за скоро иста работа зборат. :D Таму се збореше за уметниците што инстинктивно препознале дека извесна скулптура е фејк, без да знаат што точно е тоа што ги натерало така да мислат (хинт: Систем 1). Ама и таму исто така имаше дел каде зборува за најефективниот начин на препознавање срцев удар, кој помалку се темели на експертска проценка, а повеќе на механички, алгоритмиски начин на селектирање кој е под ризик за срцев удар во текот на денот, а кој не. И се базира само на три прашања, а има поголема точност од најголемиот дел доктори.

    Мислам дека Блинк и оваа имаа иста поента, само што првава беше ко :inlove: wow интуиција wow :inlove:, додека втората беше повеќе во стил „најголем дел од времето се водиме по интуитивни проценки, и да, ти не си исклучокот, колку побрзо се помириш со тоа, толку подобро.“ :D

    Друго нешто што приметив беше кога зборуваше за подготовката на учебникот во Израел, и како цел тим мислел дека ќе завршат побрзо и покрај очигледните статистички податоци дека тоа е малку веројатно. Сепак одлучиле да го игнорираат тој факт поради wishful thinking или така нешто. Ме потсети на тоа како лани ова време мислевме дека пандемијата ќе ја снема за некој месец иако од минатите искуства со пандемии е јасно дека не ги снемува така лесно. Ги имавме статистичките податоци, ги имавме и предвидувањата за првите вакцини, и пак мислевме дека нема да стигнеме до оваа точка. Тоа ми беше интересно (и воедно депресивно).

    Anyway, најинтересниот дел за мене беше последниот, Two Selves. Многупати сум помислувала на овој концепт, и имав bittersweet изненадување кога го видов тука. Многу ми е трипи, на филозофски начин и на физички. Најголемиот страв во животот ми е Алцхајмерова болест, а и сите други облици на деменција. Имам спомнувано на другари дека ако некогаш се случи да почнам да губам мемории ќе не знам која би била поентата на животот, бидејќи всушност кој си ти ако не само збир од мемории? Затоа кога го читав истово ова поткрепено со експериментални потврди ми беше језивко. :D Во суштина ништо што периципираме не се одвива во истиот момент, бидејќи пред да стигне информацијата во мозокот за нешто, минуваат неколку милисекунди (или колку и да беше). Без разлика дали е допир, звук или светлина, ништо не патува бесконечно брзо, така што секогаш сме во минатото. :drunk:
    Овој цитат и јас го зачував, затоа што ме фати за коса и ме тресна од земја. И прашањето пред него ми беше многу интересно. Би одел ли на одмор ако не се сеќаваш на него после? Јас не би одела. Не знам, од една страна го сфаќам тој living in the moment crap, ама сепак на крај она што те прави да се осеќаш добро за фактот што си живеел во моментот е сеќавањето дека додека си бил таму ти било убаво. Затоа мислам дека во последно време сме повеќе опседнати со фотографии и видеа. Помагаат мемориите да ни бидат попрецизни отколку што би ни биле без нив.

    Инаку ако и вам ви е интересен концептов на experiencing и remembering self, некои од епизодите на Блек Мирор се фокусираат баш на тоа, и на етиката околу трансфер на мемории. Дали мемориите се само код, или пак се the essence of being human, што само по себе повелкува еден куп морални проблеми. Можеби сте ја гледале серијава, ама во случај да не сте ја гледале, секоја епизода е приказна независна од другите, и овие се епизодите кои се вртат околу оваа тематика:
    Playtest
    USS Callister
    White Christmas (оваа е најголем мајндфак)
    Епизоди генерално за меморија:
    The Entire History of You
    White Bear
    Crocodile

    Како и да е, книгава навистина ми се допадна, нуди еден куп работи за размислување, а и многу информации. Главниот take што сметам дека секој на крај би го извлекол од неа е дека не сме комплетно рационални суштества, колку и да веруваме дека сме, бидејќи еволуциски сме развиле интуиција што како шорткат е поефективна во одредени ситуации. И тоа не е нешто страшно, туку само важно е да сме свесни за тоа и да си правиме риалити чек одвреме навреме. :D

    За следна книга мислам дека дефинитивно треба да одбереме нешто пократко. Во анкетите имаме доста гласови, а ептен малку коментари. :D Еве предлози од мене:
    The Ethics of Ambiguity – Simone de Beauvoir
    (вовед во егзистенцијализам, етичките дилеми во него, апсурдот и како да навигираме низ него)
    Why Your Five-Year-Old Could Not Have Done That: Modern Art Explained – Susie Hodge
    (одбрана на апстрактната уметност која популарно се смета за булшит и претенциозност)
    Ten Arguments For Deleting Your Social Media Accounts Right Now – Jaron Lanier
    (self-explanatory е оваа, напишана е од еден од научниците што се појавува во The Social Dilemma, филмот за дизајнот на социјалните мрежи и како ни влијаат)
     
    На Bezimenka90, pdb123 и sweet-cherry им се допаѓа ова.