443 Matching Annotations
  1. Sep 2023
  2. Aug 2023
    1. In finance, the greater fool theory suggests that one can sometimes make money through the purchase of overvalued assets — items with a purchase price drastically exceeding the intrinsic value — if those assets can later be resold at an even higher price.
    1. The participants in both the 2018 and the retracted 2023 studies were recruited from online communities that were explicitly critical about many aspects of gender-affirming care for transgender kids.
    1. The big tech companies, left to their own devices (so to speak), have already had a net negative effect on societies worldwide. At the moment, the three big threats these companies pose – aggressive surveillance, arbitrary suppression of content (the censorship problem), and the subtle manipulation of thoughts, behaviors, votes, purchases, attitudes and beliefs – are unchecked worldwide
      • for: quote, quote - Robert Epstein, quote - search engine bias,quote - future of democracy, quote - tilting elections, quote - progress trap, progress trap, cultural evolution, technology - futures, futures - technology, progress trap, indyweb - support, future - education
      • quote
        • The big tech companies, left to their own devices , have already had a net negative effect on societies worldwide.
        • At the moment, the three big threats these companies pose
          • aggressive surveillance,
          • arbitrary suppression of content,
            • the censorship problem, and
          • the subtle manipulation of
            • thoughts,
            • behaviors,
            • votes,
            • purchases,
            • attitudes and
            • beliefs
          • are unchecked worldwide
      • author: Robert Epstein
        • senior research psychologist at American Institute for Behavioral Research and Technology
      • paraphrase
        • Epstein's organization is building two technologies that assist in combating these problems:
          • passively monitor what big tech companies are showing people online,
          • smart algorithms that will ultimately be able to identify online manipulations in realtime:
            • biased search results,
            • biased search suggestions,
            • biased newsfeeds,
            • platform-generated targeted messages,
            • platform-engineered virality,
            • shadow-banning,
            • email suppression, etc.
        • Tech evolves too quickly to be managed by laws and regulations,
          • but monitoring systems are tech, and they can and will be used to curtail the destructive and dangerous powers of companies like Google and Facebook on an ongoing basis.
      • reference
      • for: titling elections, voting - social media, voting - search engine bias, SEME, search engine manipulation effect, Robert Epstein
      • summary
        • research that shows how search engines can actually bias towards a political candidate in an election and tilt the election in favor of a particular party.
    1. In our early experiments, reported by The Washington Post in March 2013, we discovered that Google’s search engine had the power to shift the percentage of undecided voters supporting a political candidate by a substantial margin without anyone knowing.
      • for: search engine manipulation effect, SEME, voting, voting - bias, voting - manipulation, voting - search engine bias, democracy - search engine bias, quote, quote - Robert Epstein, quote - search engine bias, stats, stats - tilting elections
      • paraphrase
      • quote
        • In our early experiments, reported by The Washington Post in March 2013,
        • we discovered that Google’s search engine had the power to shift the percentage of undecided voters supporting a political candidate by a substantial margin without anyone knowing.
        • 2015 PNAS research on SEME
          • http://www.pnas.org/content/112/33/E4512.full.pdf?with-ds=yes&ref=hackernoon.com
          • stats begin
          • search results favoring one candidate
          • could easily shift the opinions and voting preferences of real voters in real elections by up to 80 percent in some demographic groups
          • with virtually no one knowing they had been manipulated.
          • stats end
          • Worse still, the few people who had noticed that we were showing them biased search results
          • generally shifted even farther in the direction of the bias,
          • so being able to spot favoritism in search results is no protection against it.
          • stats begin
          • Google’s search engine 
            • with or without any deliberate planning by Google employees 
          • was currently determining the outcomes of upwards of 25 percent of the world’s national elections.
          • This is because Google’s search engine lacks an equal-time rule,
            • so it virtually always favors one candidate over another, and that in turn shifts the preferences of undecided voters.
          • Because many elections are very close, shifting the preferences of undecided voters can easily tip the outcome.
          • stats end
    2. Early in 2013, Ronald Robertson, now a doctoral candidate at the Network Science Institute at Northeastern University in Boston, and I discovered that Google isn’t just spying on us; it also has the power to exert an enormous impact on our opinions, purchases and votes.
      • for: big tech - bias, big tech - manipulation, big tech - mind control, big tech - influence
      • paraphrase
        • Early in 2013, Ronald Robertson,
          • now a doctoral candidate at the Network Science Institute at Northeastern University in Boston,
        • and I discovered that Google isn’t just spying on us;
          • it also has the power to exert an enormous impact on our opinions, purchases and votes.
    3. he Search Suggestion Effect (SSE), the Answer Bot Effect (ABE), the Targeted Messaging Effect (TME), and the Opinion Matching Effect (OME), among others. Effects like these might now be impacting the opinions, beliefs, attitudes, decisions, purchases and voting preferences of more than two billion people every day.
      • for: search engine bias, google privacy, orwellian, privacy protection, mind control, google bias
      • title: Taming Big Tech: The Case for Monitoring
      • date: May 14th 2018
      • author: Robert Epstein

      • quote

      • paraphrase:
        • types of search engine bias
          • the Search Suggestion Effect (SSE),
          • the Answer Bot Effect (ABE),
          • the Targeted Messaging Effect (TME), and
          • the Opinion Matching Effect (OME), among others. -
        • Effects like these might now be impacting the
          • opinions,
          • beliefs,
          • attitudes,
          • decisions,
          • purchases and
          • voting preferences
        • of more than two billion people every day.
    1. Everything I'm saying to you right now is literally meaningless. (Laughter) 00:03:11 You're creating the meaning and projecting it onto me. And what's true for objects is true for other people. While you can measure their "what" and their "when," you can never measure their "why." So we color other people. We project a meaning onto them based on our biases and our experience.
      • for: projection, biases, bias, perspectival knowing, indyweb, tacit to explicit, explication, misunderstanding
      • comment
        • The "why" is invisible.
        • It is the thoughts in the private worlds of the other.
        • It is only our explication through language or other means that makes public our private world
        • We construct meaning in the world.
        • Our meaningverse is our construction. BUT it is a cultural construction,
          • it was constructed by all the meaning learned from others, especially beginning with the most significant other, our mother.
  3. Jul 2023
    1. we have all sorts of stupid biases when it comes to leadership selection.
      • facial bias
        • experiments show that children and adults alike who didn't know any of the faces shown, chose actual election leaders and runner ups of elections to be their leaders
        • China exploits the "white-guy-in- a-tie" problem to win deals.
          • Companies hire a white person with zero experience to wear a nice suit and tie and pose as a businessman who has just flown in from Silicon Valley.
    2. Why are we drawn to people who are clearly not 00:20:59 in the business of public service but want to abuse us and often show us that they are strong men who are oriented towards conquering and dominating rather than serving us? And that puts the mirror back on us. And the answer, I think, is partly to do with evolutionary psychology.
      • key observation
        • we often vote for "strong men" who are not in the business of public service but are oriented towards conquering and dominating due to a cognitive bias developed from tens of thousands of years of evolution.
        • in ancient times, a physically strong man to lead us often increased our chances of survival.
        • This is no longer true today, but that cognitive bias is still with us because evolution takes a long time.
        • Hence, this cognitive bias to select strong men is maladaptive today.
    3. when we think about self-selection bias and survivorship bias in tandem, we have a really important understanding of how power actually operates
      • key observation
        • the dynamics and relationship between
          • self-selection bias and
          • survivorship bias
        • gives us insight of how power operates
        • The wrong kinds of people who are power-hungry, seek power more in the first place.
        • Then they're better at obtaining it.
        • They show up in our ordinary lives because they've survived,
          • they've made it.
        • So when we think about who is powerful,
          • we have to think about
            • the people who didn't seek power in the first place and
            • the people who didn't obtain power in the first place.
            • the people who didn't survive in power for very long, and therefore they dropped out.
          • The presidents and prime ministers,
          • the generals,
          • the cult leaders,
          • the business leaders,
        • those people are basically people who have survived and who self-selected.
    4. Abraham Wald
      • example
        • survivorship bias
          • Abraham Wald was a statistican who was tasked by the Allied war effort with understanding how to make the Allied war planes function better.
          • And he was presented with a series of airplanes that had bullet holes throughout them as they had gone from bombing runs over Nazi Germany.
          • And he looked at them, and he saw that there were
            • holes in the wings,
            • holes in the tail,
            • holes in the nose of the plane.
          • And the general said to him, you know, "Based on your statistical expertise, where should we put extra armor?
          • Where should we reinforce the plane?"
          • And most of the people thought they should put them where the bullet holes were.
          • Abraham Wald took one look at this, and he said, "If you put armor over the places where the holes are,
            • you're going to make the planes get shot down more."
          • Because the reality was the places that didn't have bullet holes were the most crucial.
          • The places that had been shot in
            • the fuselage,
            • the middle of the plane where the engine was,
          • those were in Germany, they didn't survive,
            • they were wrecks.
          • So they never made it back to be analyzed.
          • So survivorship bias is a bias where we look at the wrong kinds of data because we only look at what survived.
    5. What is survivorship bias?
      • There's two forms of bias around power that are really important to understand.
        • The first is self-selection bias, but then there's another bias called
        • survivorship bias.
      • And this is where we only see people who make it into power.
      • When you think about the people you know who are powerful, those are people who have survived,
        • they've sought power, and
        • they've obtained it, and
        • they've maintained it.
      • The people who didn't seek power in the first place,
        • weren't successful in achieving it, or
        • only lasted for a short time,
      • those don't show up when we think about powerful people.
    6. The same is true for power. People who are power-hungry, people who are psychopaths tend to self-select into positions of power more than the rest of us. And as a result, we have this skew, this bias in positions of power where certain types of people, often the wrong kinds of people, 00:14:51 are more likely to put themselves forward to rule over the rest of us
      • key observation
        • People who are power-hungry, people who are psychopaths
          • tend to self-select into positions of power more than the rest of us.
        • And as a result, we have this skew, this bias in positions of power
          • where certain types of people, often the wrong kinds of people,
          • are more likely to put themselves forward to rule over the rest of us
    1. https://www.youtube.com/watch?v=b1_RKu-ESCY

      Lots of controversy over this music video this past week or so.

      In addition to some of the double entendre meanings of "we take care of our own", I'm most appalled about the tacit support of the mythology that small towns are "good" and large cities are "bad" (or otherwise scary, crime-ridden, or dangerous).

      What are the crime statistics per capita about the safety of small versus large?

      Availability bias of violence and crime in the big cities are overly sampled by most media (newspapers, radio, and television). This video plays heavily into this bias.

      There's also an opposing availability bias going on with respect to the positive aspects of small communities "taking care of their own" when in general, from an institutional perspective small towns are patently not taking care of each other or when they do its very selective and/or in-crowd based rather than across the board.

      Note also that all the news clips and chyrons are from Fox News in this piece.

      Alternately where are the musicians singing about and focusing on the positive aspects of cities and their cultures.

    1. In traditional artforms characterized by direct manipulation [32]of a material (e.g., painting, tattoo, or sculpture), the creator has a direct hand in creating thefinal output, and therefore it is relatively straightforward to identify the creator’s intentions andstyle in the output. Indeed, previous research has shown the relative importance of “intentionguessing” in the artistic viewing experience [33, 34], as well as the increased creative valueafforded to an artwork if elements of the human process (e.g., brushstrokes) are visible [35].However, generative techniques have strong aesthetics themselves [36]; for instance, it hasbecome apparent that certain generative tools are built to be as “realistic” as possible, resultingin a hyperrealistic aesthetic style. As these aesthetics propagate through visual culture, it can bedifficult for a casual viewer to identify the creator’s intention and individuality within the out-puts. Indeed, some creators have spoken about the challenges of getting generative AI modelsto produce images in new, different, or unique aesthetic styles [36, 37].

      Traditional artforms (direct manipulation) versus AI (tools have a built-in aesthetic)

      Some authors speak of having to wrestle control of the AI output from its trained style, making it challenging to create unique aesthetic styles. The artist indirectly influences the output by selecting training data and manipulating prompts.

      As use of the technology becomes more diverse—as consumer photography did over the last century, the authors point out—how will biases and decisions by the owners of the AI tools influence what creators are able to make?

      To a limited extent, this is already happening in photography. The smartphones are running algorithms on image sensor data to construct the picture. This is the source of controversy; see Why Dark and Light is Complicated in Photographs | Aaron Hertzmann’s blog and Putting Google Pixel's Real Tone to the test against other phone cameras - The Washington Post.

    1. One federal judge in the Northern District of Texas issued a standing order in late May after Schwartz’s situation was in headlines that anyone appearing before the court must either attest that “no portion of any filing will be drafted by generative artificial intelligence” or flag any language that was drafted by AI to be checked for accuracy. He wrote that while these “platforms are incredibly powerful and have many uses in the law,” briefings are not one of them as the platforms are “prone to hallucinations and bias” in their current states.

      Seems like this judge has a strong bias against the use of AI. I think this broad ban is too broad and unfair. Maybe they should ban spell check and every other tool that could make mistakes too? Ultimately, the humans using the tool shoudl be the ones responsible for checking the generaetd draft for accuracy and the ones to hold responsible for any mistakes; they shouldn't simply be forbidden from using the tool.

    1. Found this while looking for gamified ways to teach people how to spot/identify bias.

      Seems to be primarily targeted toward educators. Checkology does routine maintenance during July to delete all student accounts, and I was unable to create an account to see what this is like.

    1. A website I found while trying to look for gamified ways for people to learn how to spot/identify bias.

    1. Uber promising implausibly cheap rides, courtesy of a future with self-driving cars
      • Case study of market bias
        • Uber self-driving cars
  4. Jun 2023
    1. Think of branches not as collections, but rather as conversations

      When a branch starts to build, or prove itself, then ask the question (before indexing): "What is the conversation that is building here?"

      Also related to Sönke Ahrens' maxim of seeking Disconfirming Information to counter Confirmation Bias. By thinking of branches as conversations instead of collectives, you are also more inclined to put disconfirming information within the branch.

    1. Growing literature has shown that powerful NLP systems may encode social biases; however, the political bias of summarization models remains relatively unknown.

      NLP systems, language (use) itself, encodes/holds bias.

      Summarization apparently also.is not bias free.

      Goals: Our systematic characterization provides a framework for future studies of bias in summarization.

  5. May 2023
    1. An AI model taught to view racist language as normal is obviously bad. The researchers, though, point out a couple of more subtle problems. One is that shifts in language play an important role in social change; the MeToo and Black Lives Matter movements, for example, have tried to establish a new anti-sexist and anti-racist vocabulary. An AI model trained on vast swaths of the internet won’t be attuned to the nuances of this vocabulary and won’t produce or interpret language in line with these new cultural norms. It will also fail to capture the language and the norms of countries and peoples that have less access to the internet and thus a smaller linguistic footprint online. The result is that AI-generated language will be homogenized, reflecting the practices of the richest countries and communities.

      [21] AI Nuances

    1. This clearly does not represent all human cultures and languages and ways of being.We are taking an already dominant way of seeing the world and generating even more content reinforcing that dominance

      Amplifying dominant perspectives, a feedback loop that ignores all of humanity falling outside the original trainingset, which is impovering itself, while likely also extending the societal inequality that the data represents. Given how such early weaving errors determine the future (see fridges), I don't expect that to change even with more data in the future. The first discrepancy will not be overcome.

    2. This means they primarily represent the generalised views of a majority English-speaking, western population who have written a lot on Reddit and lived between about 1900 and 2023.Which in the grand scheme of history and geography, is an incredibly narrow slice of humanity.

      Appleton points to the inherent severely limited trainingset and hence perspective that is embedded in LLMs. Most of current human society, of history and future is excluded. This goes back to my take on data and blind faith in using it: [[Data geeft klein deel werkelijkheid slecht weer 20201219122618]] en [[Check data against reality 20201219145507]]

  6. Apr 2023
  7. Mar 2023
    1. This example illustrates the potential for an unintended consequence to move between categories and demonstrates that there are times when it is necessary to review and reflect. What is considered known and knowable changes over time: has the state of knowledge developed or an unintended consequence been identified?

      // - This is the critical question - Looking at history, can we see predictive patterns - when it makes sense to stop and take questions of the unknown seriously - rather than steaming ahead into uncharted territory? - We might find that society did not follow science's call - for applying the precautionary principle - because profits were just too great - the profit bias at play - profit overrides safety, health and wellbeing

    1. Whose values do we put through the A.G.I.? Who decides what it will do and not do? These will be some of the highest-stakes decisions that we’ve had to make collectively as a society.’’

      A similar set of questions might be asked of our political system. At present, the oligopolic nature of our electoral system is heavily biasing our direction as a country.

      We're heavily underrepresented on a huge number of axes.

      How would we change our voting and representation systems to better represent us?

    1. we have turned to machine learning, an ingenious way of disclaiming responsibility for anything. Machine learning is like money laundering for bias. It's a clean, mathematical apparatus that gives the status quo the aura of logical inevitability. The numbers don't lie.

      Machine learning like money laundering for bias

    1. Tech-makers assuming their reality accurately represents the world create many different kinds of problems. The training data for ChatGPT is believed to include most or all of Wikipedia, pages linked from Reddit, a billion words grabbed off the internet

      LLMs as a model of reality, but not reality

      There are limits to any model. In this case, the training data. What biases are implicitly in that model based on how it was selected and what it contained?

      The paragraph goes on to list some biases: race, wealth, and “vast swamps”

  8. Feb 2023
    1. belief perseverance
      • belief perseverance
      • definition
        • a cognitive bias in which people encountering evidence that runs counter to their beliefs will, instead of reevaluating what they’ve believed up until now, tend to reject the incompatible evidence
    1. we describe a conceptual framework for understanding adaptive sources of dysfunction – for identifying and combating “adaptations gone awry.”
      • we describe a conceptual framework
      • for understanding adaptive sources of dysfunction
      • for identifying and combating “adaptations gone awry.”
    2. Each reflects the operation of psychological mechanisms that were designed through evolution to serve important adaptive functions, but that nevertheless can produce harmful consequences.
      • Each of these 4 problems
        • anxiety disorder
        • domestic violence
        • racial prejudice
        • obesity
      • reflects the operation of psychological mechanisms
      • that were designed through evolution
      • to serve important adaptive functions, - but that nevertheless can produce harmful consequences.
    3. What do anxiety disorders, domestic violence, racial prejudice, and obesity all have in common?
      • question
        • What do
          • anxiety disorders,
          • domestic violence,
          • racial prejudice, and
          • obesity
      • all have in common?
      • answer
        • maladaptive cognitive biases!
    4. mismatches between current environments and ancestral environments
      • cognitive biases may cause dysfunction due to mismatches between:
        • current environments and
        • ancestral environments
    5. from aggression and international conflict to overpopulation and the destruction of the environment, people display a capacity for great selfishness and antisocial behavior. Can an evolutionary perspective – with its inherent focus on the functionality of human behavior – help explain the occasionally self-destructive and maladaptive side of human nature?
      • from aggression and international conflict to overpopulation and the destruction of the environment,
      • people display a capacity for great selfishness and antisocial behavior.
      • Can an evolutionary perspective
      • with its inherent focus on the functionality of human behavior
      • help explain the occasionally self-destructive and maladaptive side of human nature?
    6. Relative to the evolutionary past, social relationships in modernized western societies tend to involve a much wider variety of relationships, along with relatively less immediate connection with close, kin-based support networks
      • Relative to the evolutionary past,
      • social relationships
      • in modernized western societies
      • tend to involve
      • a much wider variety of relationships,
      • along with relatively less immediate connection
      • with close, kin-based support networks
    7. From an evolutionary perspective, social anxiety is designed primarily to help people ensure an adequate level of social acceptance and, throughout most of human history, this meant acceptance in a tightly-knit group based primarily of biological kin
      • From an evolutionary perspective, - social anxiety is designed primarily
      • to help people ensure
      • an adequate level of social acceptance and,
      • throughout most of human history,
      • this meant acceptance
      • in a tightly-knit group
      • based primarily of biological kin
    8. Although social anxiety can serve useful functions, it can also involve excessive worry, negative affect, and exaggerated avoidance of social situations. Understanding the root causes of anxiety-related problems is an essential step in the development of interventions and policies to reduce dysfunction.
      • Although social anxiety can serve useful functions,
      • it can also involve excessive worry, negative affect, and exaggerated avoidance of social situations.
      • Understanding the root causes of anxiety-related problems
      • is an essential step
      • in the development of
      • interventions and policies
      • to reduce dysfunction.
    1. Many authors noted that generations tended to fall into clichés, especially when the system was confronted with scenarios less likely to be found in the model's training data. For example, Nelly Garcia noted the difficulty in writing about a lesbian romance — the model kept suggesting that she insert a male character or that she have the female protagonists talk about friendship. Yudhanjaya Wijeratne attempted to deviate from standard fantasy tropes (e.g. heroes as cartographers and builders, not warriors), but Wordcraft insisted on pushing the story toward the well-worn trope of a warrior hero fighting back enemy invaders.

      Examples of artificial intelligence pushing toward pre-existing biases based on training data sets.

  9. Jan 2023
    1. Nature knows that, in the long run, established species are expendable and new species are essential. That is why Nature is ruthless to the individual parent and generous to the emerging species. Risk-taking is the key to long-term survival and is also the mother of diversity.

      !- nature is designed with a natural bias : it favours new emerging species over established ones

    1. NYT and NYT online are well-respected left-center publications. They are known for their factual reporting and variety of topics. The NYT op-eds are known to lean a little more left than NYT news, mostly due to editorial topic selection. This leads me to believe that the intended audience is the average American, particularly those with a left lean. The author writes in relatively simple terms that are easily read by the audience.

    1. Who falls for fake news? Psychological and clinical profiling evidence of fake news consumers

      Participants with a schizotypal, paranoid, and histrionic personality were ineffective at detecting fake news. They were also more vulnerable to suffer its negative effects. Specifically, they displayed higher levels of anxiety and committed more cognitive biases based on suggestibility and the Barnum Effect. No significant effects on psychotic symptomatology or affective mood states were observed. Corresponding to these outcomes, two clinical and therapeutic recommendations related to the reduction of the Barnum Effect and the reinterpretation of digital media sensationalism were made. The impact of fake news and possible ways of prevention are discussed.

      Fake news and personality disorders

      The observed relationship between fake news and levels of schizotypy was consistent with previous scientific evidence on pseudoscientific beliefs and magical ideation (see Bronstein et al., 2019; Escolà-Gascón, Marín, et al., 2021). Following the dual process theory model (e.g., Pennycook & Rand, 2019), when a person does not correctly distinguish between information with scientific arguments and information without scientific grounds it is because they predominantly use cognitive reasoning characterized by intuition (e.g., Dagnall, Drinkwater, et al., 2010; Swami et al., 2014; Dagnall et al., 2017b; Williams et al., 2021).

      Concomitantly, intuitive thinking correlates positively with magical beliefs (see Šrol, 2021). Psychopathological classifications include magical beliefs as a dimension of schizotypal personality (e.g., Escolà-Gascón, 2020a). Therefore, it is possible that the high schizotypy scores in this study can be explained from the perspective of dual process theory (Denovan et al., 2018; Denovan et al., 2020; Drinkwater, Dagnall, Denovan, & Williams, 2021). Intuitive thinking could be the moderating variable that explains why participants who scored higher in schizotypy did not effectively detect fake news.

      Something similar happened with the subclinical trait of paranoia. This variable scored the highest in both group 1 and group 2 (see Fig. 1). Intuition is also positively related to conspiratorial ideation (see Drinkwater et al., 2020; Gligorić et al., 2021). Similarly, psychopathology tends to classify conspiracy ideation as a frequent belief system in paranoid personality (see Escolà-Gascón, 2022). This is because conspiracy beliefs are based on systematic distrust of the systems that structure society (political system), knowledge (science) and economy (capitalism) (Dagnall et al., 2015; Swami et al., 2014). Likewise, it is known that distrust is the transversal characteristic of paranoid personality (So et al., 2022). Then, in this case the use of intuitive thinking and dual process theory could also justify the obtained paranoia scores. The same is not true for the histrionic personality.

      The Barnum Effect

      The Barnum Effect consists of accepting as exclusive a verbal description of an individual's personality, when, the description employs contents applicable or generalizable to any profile or personality that one wishes to describe (see Boyce & Geller, 2002; O’Keeffe & Wiseman, 2005). The error of this bias is to assume as exclusive or unique information that is not. This error can occur in other contexts not limited to personality descriptions. Originally, this bias was studied in the field of horoscopes and pseudoscience's (see Matute et al., 2011). Research results suggest that people who do not effectively detect fake news regularly commit the Barnum Effect. So, one way to prevent fake news may be to educate about what the Barnum Effect is and how to avoid it.


      The conclusions of this research can be summarized as follows: (1) The evidence obtained proposes that profiles with high scores in schizotypy, paranoia and histrionism are more vulnerable to the negative effects of fake news. In clinical practice, special caution is recommended for patients who meet the symptomatic characteristics of these personality traits.

      (2) In psychiatry and clinical psychology, it is proposed to combat fake news by reducing or recoding the Barnum effect, reinterpreting sensationalism in the media and promoting critical thinking in social network users. These suggestions can be applied from intervention programs but can also be implemented as psychoeducational programs for massive users of social networks.

      (3) Individuals who do not effectively detect fake news tend to have higher levels of anxiety, both state and trait anxiety. These individuals are also highly suggestible and tend to seek strong emotions. Profiles of this type may inappropriately employ intuitive thinking, which could be the psychological mechanism that.

      (4) Positive psychotic symptomatology, affective mood states and substance use (addiction risks) were not affected by fake news. In the field of psychosis, it should be analyzed whether fake news influences negative psychotic symptomatology.

  10. Dec 2022
    1. As a result, these Freedom Schools made citizens.

      I think the Author may be committing a begging the question fallacy here. Each type of school creates citizens, but the difference is the quality of awareness within the children entering society post education. This statement is circular within the argument.

    2. According to PEN America, a nonprofit dedicated to protecting free expression, legislatures in 36 states have proposed 137 bills that would limit teaching about race, gender and American history.

      I would argue that there is a fair amount of cognitive dissonance present on the side introducing these bills. Their lived experience and perception of themselves conflicts with the reality that they are white supremacists and are actively suppressing BIPOC history in an effort to reconcile their perceptions of how they live.

    1. At its most tame, Ancient Apocalypse simply reinforces a deeply conservative understanding of human history. Conservative, yes, because despite Hancock’s claim to challenge every orthodoxy going, his ideas—like those of Ignatius Loyola Donnelly, Erich von Däniken, and other so-called “pseudo-archaeologists”—rest on a baseline assumption that technology should always be advancing in linear fashion, from primitive simplicity to modern complexity.

      There is a broad, conservative baseline assumption within much of archaeology that technology always proceeds in a linear fashion from primitive simplicity to modern complexity.

      Archaeologists and historians need to watch carefully for this cognitive bias.

    1. This is especially clear for subjects beyond the three R’s — reading, writing and arithmetic. Fewer than 1 percent of American adults even claim to have learned to speak a foreign language very well in school, even when two years of coursework is standard. Adults’ knowledge of history and civics is negligible. If you test the most elementary facts, like naming the three branches of government, they get about half right. The same goes for questions of basic science, like “Are electrons smaller than atoms?” and “Do antibiotics kill viruses as well as bacteria?”

      In this paragraph the author explains how subjects and information learned in schools are poorly retained, adults not being able to answer 'simple' questions. I believe in this paragraph he's exhibiting Confirmation Bias because there are many other factors as to why adults may not retain information such as interest, other ongoing events personally or socially, or simply just the passage of time.

    1. Motivated Reasoning

      In broad terms, motivated reasoning theory suggests that reasoning processes (information selection and evaluation, memory encoding, attitude formation, judgment, and decision-making) are influenced by motivations or goals. Motivations are desired end-states that individuals want to achieve.

    1. What is the Illusory Truth Effect?

      The illusory truth effect, also known as the illusion of truth, describes how, when we hear the same false information repeated again and again, we often come to believe it is true. Troublingly, this even happens when people should know better—that is, when people initially know that the misinformation is false.

    1. The author of this editorial claims that there is moral value in using the emissions made by a human body over the course of its lifetime in determining if one should be given life. Making a departure from natural selection, and from sexual attraction and ignoring maternal instinct and cultural familial practices and norms. He proposes that the act of being alive can be measured in its impact upon others who will share the future climate them and since the impact is not 0 then there must be an upper limit of "too many". Immorally, he does not include a measure of "too few" and does not make any mention of the problems society has with exponential population decline. Such as Japan currently selling more adult than infant diapers as their population collapses because of too few children. In fact there is no mention of generational replacement or reproduction rate. Just a simplistic measure of a human impact upon the environment with the entirety of positive impact deleted, omitted, ignored completely. There is in fact no moral high ground in maintaining or promoting the idea that human life has no positive value to the earth. Failing to see ones own value or the value of human life as a whole, rejecting the desire to help human kind survive and prosper and reducing human beings to objects with emissions and no positive output potential is morally reprehensible and not a scientifically sound conclusion, given the observable facts. Among them, that every human being alive on the planet today, standing shoulder to shoulder, would not fill the area of los angeles, and setting aside one acre of our best land for every human being on earth would require an area no arger than texas. There is no scientific basis for concluding there are too many people or that the future humans would benefit from lower population. it is a common error, in the media today, where the impact on climate is evaluated out of the context of all other scilences where positive impacts and negative impacts of human life are observable. Such as biological sciences or earth sciences. it is true, that if we lived on a gas giant, where the only element of the planetary ecosystem was the climate, then such an evaluation of our "carbon footprint" would be meaningful. but since we have a planet with oceans dryland and predators and dangerous conditions, it is morrally reprehensible to suggest our population not maximize its potential to survive to see the future so many are trying to protect by literally throwing their babies out with the bathwater. It is impossible to contribute to the well-being of human life in editorial if you do not have a love of human life. My heart goes out to anyone who takes this article seriously. You do not have to limit your fertility to help humankind survive.

    1. the local healer, or wise man or woman, whowould have particular knowledge of local plants and herbalremedies. This knowledge was oral, however, and its practitioners,for the most part, were illiterate.

      Example of an implicit bias against orality out of ignorance



    1. the Arcadians exist now for a reason. But I think a case can be made that this had to happen. We were never, ever, ever going to do this the easy way where we learned for example, we could have seen this back in the early 1900s. We didn't, right? We could have changed at the end of World War II. 00:31:27 We could have changed in 1970. We didn't. Why? We always took the easy way out. It's like a dopamine hit.

      !- insight : progress traps - the dominance of self-interested economic behavior creates a systemic tendency to ignore progress traps, unintended consequences of technology. Profit bias acts to cherry pick explanations that marginalizes rather than addresses progress traps, allowing them to fester and grow to dangerous levels

    1. AI training data is filled with racist stereotypes, pornography, and explicit images of rape, researchers Abeba Birhane, Vinay Uday Prabhu, and Emmanuel Kahembwe found after analyzing a data set similar to the one used to build Stable Diffusion.

      That is horrifying. You'd think that authors would attempt to remove or filter this kind of material. There are, after all models out there that are trained to find it. It makes me wonder what awful stuff is in the GPT-3 dataset too.

    1. I was suspicious—when I ordered Robert B. Stinnett’s book Day of Deceit, that lays out in chapter and verse and proves how FDR deliberately engineered the December 7, 1941 Japanese raid on the U.S. Navy and Army Bases at Pearl Harbor and knew exactly when it was coming—about the fact that it was published by a Jewish publishing house. The publisher, Free Press (the name is a joke) is, after all, a division of Simon & Schuster, a notorious New York Jewhouse.

      Interesting reason to dismiss the evidence presented by the author.

    1. Many HRMS providers point to AI approaches for processing unstructured data as the bestcurrently available approach to dealing with validation. Currently these approaches suffer frominsufficient accuracy. Improving them requires development of large and high-quality referencedatasets to better train the models.

      Historical labor data will be full of bias. AI approaches must correct for bias in training sets, lest we build very sophisticated and intelligent systems that excel at perpetuating the bias they were taught.

  11. Nov 2022
    1. "This is a job market that just won't quit. It's challenging the rules of economics," said Becky Frankiewicz,  chief commercial officer of hiring company ManpowerGroup in an email after the data was released. "The economic indicators are signaling caution, yet American employers are signaling confidence."

      This article explains the economic market. Creating 528,000 jobs is an outstanding aspect for the American people. But It also needs to explain the bad parts of creating jobs in this situation. Because challenging the rules of economics should not make a better situation, There are also high risks.

    1. That could create even more burdens for businesses because hiking interest rates tends to create higher rates on consumer and business loans, which slows the economy by forcing employers to cut back on spending.

      This article describes the disadvantages of high-interest rates. Although there are facts and parts that we need to be concerned about, high-interest rates also have advantages. There are more information about advantages about high-interest.

  12. Oct 2022
    1. An adviser should have their students explicitly practice decisions 25 and 26, test their solutions, and try to come up with the ways their decisions could fail, including alternative conclusions that are not the findings that they were hoping for. Thinking of such failure modes is something that even many experienced physicists are not very good at, but our research has shown that it can be readily learned with practice.

      To help fight cognitive bias, one should actively think about potential failure modes of one's decisions and think about alternative conclusions which aren't part of the findings one might have hoped for. Watching out for these can dramatically help increase solution spaces and be on the watch out for innovative alternate or even better solutions.

    2. The third and probably most serious difficulty in making good reflective decisions is confirmation bias.

      Confirmation bias can be detrimental when making solid reflective decisions.

    1. You do not reallyhave to study a topic you are working on; once your areinto it, it is everywhere. You are sensitive to its themes;you see and hear them everywhere in your experience,especially, it always seems to me, in apparently unrelatedareas. Even the mass media, especially bad movies andcheap novels and picture magazines and night radio, aredisclosed in fresh importance to you.
    2. To be able to trustone's own experience, even if it often turns out to beinadequate, is one mark of the mature workman. Suchconfidence in o n e ' s own experience is indispensable tooriginality in any intellectual pursuit, and the file is onetool by which I have tried to develop and justify suchconfidence.

      The function of memory served by having written notes is what allows the serious researcher or thinker to have greater confidence in their work, potentially more free from cognitive bias as one idea can be directly compared and contrasted with another by direct juxtaposition.

    3. whether he knows it or not, the intellec-tual workman forms his own self as he works towards theperfection of his craft.

      Here Mills seems to be defining (in 1952) an "intellectual workman" as an academic, but he doesn't go as broad as a more modern "knowledge worker" (2022) which includes those who broadly do thinking in industry as well as in academia. His older phrase also has a more gendered flavor to it that knowledge worker doesn't have now.

  13. Sep 2022
    1. But most of humanity—not just medieval people—lacked the ability to fight infections or even under-stand how they spread for much of history. England during the Renaissance suffered regular deadly outbreaks of plague, smallpox, syphilis, typhus, malaria, and a mysterious illness called “sweating sickness.” Upon contact with Europeans, upwards of 95 per cent of the Indigenous peoples of the Americas were killed by European diseases. Plagues even rav-aged the twentieth century: from 1918–1920, half a billion 14 / The Devil’s Historianspeople were infected with the Spanish Flu global pandemic, which killed between 50 and 100 million people. And let’s not forget that we are currently living with the global pandemic of HIV/AIDS

      Maybe people in the future will see today as the dark ages becuase of the outbreak of COVID-19 pandemic So it is biased to call the middle ages as "dark ages" when the level of science during the middle ages cannot heal or prevent people from the infection of plagues such as the "black death".

    1. The problem is that if one player finds a way to undermine orcircumvent the rules and gets away with it then the others have no choicebut to follow. If they don’t they’ll lose out.

      !- for : race to the bottom !- for : conformity bias - spiraling destructive entrainment



    1. https://www.scientificamerican.com/article/information-overload-helps-fake-news-spread-and-social-media-knows-it/

      Good overview article of some of the psychology research behind misinformation in social media spaces including bots, AI, and the effects of cognitive bias.

      Probably worth mining the story for the journal articles and collecting/reading them.

    2. n a recent laboratory study, Robert Jagiello, also at Warwick, found that socially shared information not only bolsters our biases but also becomes more resilient to correction.
    3. We confuse popularity with quality and end up copying the behavior we observe.

      Popularity ≠ quality in social media.

    4. Even our ability to detect online manipulation is affected by our political bias, though not symmetrically: Republican users are more likely to mistake bots promoting conservative ideas for humans, whereas Democrats are more likely to mistake conservative human users for bots.
    5. Unable to process all this material, we let our cognitive biases decide what we should pay attention to.

      In a society consumed with information overload, it is easier for our brains to allow our well evolved cognitive biases to decide not only what to pay attention to, but what to believe.

    1. https://thehill.com/homenews/senate/3641225-mcconnell-throws-shade-on-grahams-proposed-national-abortion-ban/

      I've recently run across a few examples of a pattern that should have a name because it would appear to dramatically change the outcomes. I'm going to term it "decisions based on possibilities rather than realities". It's seen frequently in economics and politics and seems to be a form of cognitive bias. People make choices (or votes) about uncertain futures, often when there is a confluence of fear, uncertainty, and doubt, and these choices are dramatically different than when they're presented with the actual circumstances in practice.

      A recent example was a story about a woman who was virulently pro-life who when presented with a situation required her to switch her position to pro-choice.

      Another relates to choices that people want to make about where their children might go to school versus where they actually send them, and the damage this does to public education.

      Let's start collecting examples of these quandaries at all levels of making choices in the real world.

      What is the relationship to this with the mental exercise of "descending into the particular"?

      Does this also potentially cause decision fatigue in cases of voting spaces when constituents are forced to vote for candidates on thousands of axes which they may or may not agree with?

  14. Aug 2022
    1. The point is to write bug-free code.

      With this comment, the anti-JS position is becoming increasingly untenable. The author earlier suggested C as an alternative. So their contention is that it's easier to write bug-free code in C than it is in JS. This is silly.

      C hackers like Fabrice Bellard don't choose C for the things they do because it's easier to write bug-free code in C.

  15. Jul 2022
    1. While Brave Search does not have editorial biases, all search engines have some level of intrinsic bias due to data and algorithmic choices. Goggles allows users to counter any intrinsic biases in the algorithm.
    1. We also tend to preferinformation we have seen more recently to informationwe learned a long time ago.

      Does this effect have a name? references?

      Apparently called the recency bias: https://en.wikipedia.org/wiki/Recency_bias which may be entangled with availability bias or heuristic.

      Are both recency and availability biases the foundations for causing the Baader–Meinhof phenomenon or frequency bias?

    1. Even though human existence in such a bare state may seem inconceivable, it is therenevertheless: every time a baby is born, a new, not yet programmed, prepersonal human is lookinginto somebody’s eyes ([27 ]: p. 133). This undeniable prepersonal presence we already call human leadsus to logically infer that humans do happen to exist prior to their personware [ 20 ,25 ,28 ]. It is thereforeour fundamental point of departure that humans are marvellous, intelligent, living cognitive agents inthemselves that can be said to exist prior to and independently of any particularly determined socialpersona. The point of acknowledging a prior prepersonal platform is not made towards arguing that ahuman can exist without any personware.

      !- for : altricial, feral children, mOTHER as the significant OTHER * The bare state of zero culture, zero social context is what each and every neonate starts with in life * The mOTHER is the most significant OTHER that begins the process of socializing and enculturating the neonate into a social system * Altrciality forces human parent into role of strong socialization * Without culture, the neonate born into the world outside the womb can become a feral child * https://www.zmescience.com/other/feature-post/feral-children/ * The state of human ferality can tell us an enormous amount of the perspective of virtually every modern, encultured person - we have a bias towards a cultural perspective because almost noone has seen from a feral perspective * Language is the gateway into the symbolosphere, where enculturated, modern humans spend a significant portion of their lives immersed in this ubiquitous, constructed, symbolic reality

    1. It feels like « removing spring » is one of those unchallenged truths like « always remove Turbolinks » or « never use fixtures ». It also feels like a confirmation bias when it goes wrong.

      "unchallenged truths" is not really accurate. More like unchallenged assumption.

  16. Jun 2022
    1. If we overlay the four steps of CODE onto the model ofdivergence and convergence, we arrive at a powerful template forthe creative process in our time.

      The way that Tiago Forte overlaps the idea of C.O.D.E. (capture/collect, organize, distill, express) with the divergence/convergence model points out some primary differences of his system and that of some of the more refined methods of maintaining a zettelkasten.

      A flattened diamond shape which grows from a point on the left so as to indicate divergence from a point to the diamond's wide middle which then decreases to the right to indicate convergence  to the opposite point. Overlapping this on the right of the diamond are the words "capture" and "organize" while the converging right side is overlaid with "distill" and "express". <small>Overlapping ideas of C.O.D.E. and divergence/convergence from Tiago Forte's book Building a Second Brain (Atria Books, 2022) </small>

      Forte's focus on organizing is dedicated solely on to putting things into folders, which is a light touch way of indexing them. However it only indexes them on one axis—that of the folder into which they're being placed. This precludes them from being indexed on a variety of other axes from the start to other places where they might also be used in the future. His method requires more additional work and effort to revisit and re-arrange (move them into other folders) or index them later.

      Most historical commonplacing and zettelkasten techniques place a heavier emphasis on indexing pieces as they're collected.

      Commonplacing creates more work on the user between organizing and distilling because they're more dependent on their memory of the user or depending on the regular re-reading and revisiting of pieces one may have a memory of existence. Most commonplacing methods (particularly the older historic forms of collecting and excerpting sententiae) also doesn't focus or rely on one writing out their own ideas in larger form as one goes along, so generally here there is a larger amount of work at the expression stage.

      Zettelkasten techniques as imagined by Luhmann and Ahrens smooth the process between organization and distillation by creating tacit links between ideas. This additional piece of the process makes distillation far easier because the linking work has been done along the way, so one only need edit out ideas that don't add to the overall argument or piece. All that remains is light editing.

      Ahrens' instantiation of the method also focuses on writing out and summarizing other's ideas in one's own words for later convenient reuse. This idea is also seen in Bruce Ballenger's The Curious Researcher as a means of both sensemaking and reuse, though none of the organizational indexing or idea linking seem to be found there.

      This also fits into the diamond shape that Forte provides as the height along the vertical can stand in as a proxy for the equivalent amount of work that is required during the overall process.

      This shape could be reframed for a refined zettelkasten method as an indication of work

      Forte's diamond shape provided gives a visual representation of the overall process of the divergence and convergence.

      But what if we change that shape to indicate the amount of work that is required along the steps of the process?!

      Here, we might expect the diamond to relatively accurately reflect the amounts of work along the path.

      If this is the case, then what might the relative workload look like for a refined zettelkasten? First we'll need to move the express portion between capture and organize where it more naturally sits, at least in Ahren's instantiation of the method. While this does take a discrete small amount of work and time for the note taker, it pays off in the long run as one intends from the start to reuse this work. It also pays further dividends as it dramatically increases one's understanding of the material that is being collected, particularly when conjoined to the organization portion which actively links this knowledge into one's broader world view based on their notes. For the moment, we'll neglect the benefits of comparison of conjoined ideas which may reveal flaws in our thinking and reasoning or the benefits of new questions and ideas which may arise from this juxtaposition.

      Graphs of commonplace book method (collect, organize, distill, express) versus zettelkasten method (collect, express, organize (index/link), and distill (edit)) with work on the vertical axis and time/methods on the horizontal axis. While there is similar work in collection the graph for the zettelkasten is overall lower and flatter and eventually tails off, the commonplace slowly increases over time.

      This sketch could be refined a bit, but overall it shows that frontloading the work has the effect of dramatically increasing the efficiency and productivity for a particular piece of work.

      Note that when compounded over a lifetime's work, this diagram also neglects the productivity increase over being able to revisit old work and re-using it for multiple different types of work or projects where there is potential overlap, not to mention the combinatorial possibilities.


      It could be useful to better and more carefully plot out the amounts of time, work/effort for these methods (based on practical experience) and then regraph the resulting power inputs against each other to come up with a better picture of the efficiency gains.

      Is some of the reason that people are against zettelkasten methods that they don't see the immediate gains in return for the upfront work, and thus abandon the process? Is this a form of misinterpreted-effort hypothesis at work? It can also be compounded at not being able to see the compounding effects of the upfront work.

      What does research indicate about how people are able to predict compounding effects over time in areas like money/finance? What might this indicate here? Humans definitely have issues seeing and reacting to probabilities in this same manner, so one might expect the same intellectual blindness based on system 1 vs. system 2.

      Given that indexing things, especially digitally, requires so little work and effort upfront, it should be done at the time of collection.

      I'll admit that it only took a moment to read this highlighted sentence and look at the related diagram, but the amount of material I was able to draw out of it by reframing it, thinking about it, having my own thoughts and ideas against it, and then innovating based upon it was incredibly fruitful in terms of better differentiating amongst a variety of note taking and sense making frameworks.

      For me, this is a great example of what reading with a pen in hand, rephrasing, extending, and linking to other ideas can accomplish.

    2. If you ignore that inner voice of intuition, over time it will slowlyquiet down and fade away. If you practice listening to what it is tellingyou, the inner voice will grow stronger. You’ll start to hear it in allkinds of situations. It will guide you in what choices to make andwhich opportunities to pursue. It will warn you away from people andsituations that aren’t right for you. It will speak up and take a standfor your convictions even when you’re afraid.I can’t think of anything more important for your creative life—andyour life in general—than learning to listen to the voice of intuitioninside. It is the source of your imagination, your confidence, and yourspontaneity

      While we have evolved a psychological apparatus that often gives us good "gut feelings" (an actual physical "second brain"), we should listen careful to them, but we should also learn to think about, analyze, and verify these feelings so we don't fall prey to potential cognitive biases.

    1. It is now impossible for the world’s leaders to say that they “didn’t know” that this was going on, and that we didn’t have the power to prevent it all along. We scientists have been working hard, collecting evidence, writing reports, and presenting it all to the world’s leaders and the broader public. No one can honestly say that we haven’t been warning the world for decades.

      And therein lies the great mystery. How is it that with this specific way of knowing, we can still ignore the overwhelming science? It's not just a small minority either, but the majority of the elites. As research from Yale and other leading research institutions on climate communications have discovered, it is not so much a knowledge deficit problem, as it is a sociological / pyschological ingroup/outgroup conformity bias problem.

      This would suggest that the scientific community must rapidly pivot and place more resources on studying this important area to find the leverage points for penetrating conformity bias.

    1. but suppressed through a series of abandonments made in a vain effort to conform with societal expectations.

      Our propensity for conformity bias is extremely powerful....the same thing is destroying political discourse. However, an antidote to conformity bias is awe:


    1. if you accept that this is pretty widespread and we we can talk about all the evidence for that the question is then why like how why are we so susceptible to being spectacularly wrong about the 00:04:13 group and then end up like making something true that never was true and it's really like two underlying mechanisms right so the first is this conformity bias which that's not very novel like we know we've known for a 00:04:25 long time that is a species humans are a conforming species

      Two mechanisms behind collective illusions. The first is conformity bias.

  17. May 2022
    1. The student doesn’t have a strong preference for any of these archetypes. Their notes serve a clear purpose that’s often based on a short-term priority (e.g, writing a paper or passing a test), with the goal to “get it done” as simply as possible.

      The typical student note taking method of transcribing, using (or often not using at all), and keeping notes is doomed to failure.

      Many students make the mistake of not making their own actual notes. By this I don't mean they're not writing information down. In fact many are writing information down, but we can't really call these notes. Notes by definition ought to transform something seen or heard into one's own words. Without the transformation, these students think that they're taking notes, but in reality they're focusing their efforts on being transcriptionists. They're attempting to capture something for later consumption. This is a deadly trap! By only transcribing, they're not taking advantage of transforming information by putting ideas down in their own words to test their understanding. Often worse, even if they do transcribe notes, they don't revisit them. If they do revisit them, they're simply re-reading them and not actively working with them. Only re-reading them will lead to the illusion that they're learning something when in fact they're falling into the mere-exposure effect.

      Students who are acting as transcriptionists would be better off simply reading a textbook and taking notes directly from that.

      A note that isn't revisited or revised, may as well be a note not taken. If we were to consider a spectrum of useful, valuable, and worthwhile notes, these notes would be at the lowest end of the spectrum.

      link to: https://hypothes.is/a/QgkL6IkIEeym7OeN9v9New

  18. Apr 2022
    1. Before 2009, Facebook had given users a simple timeline––a never-ending stream of content generated by their friends and connections, with the newest posts at the top and the oldest ones at the bottom. This was often overwhelming in its volume, but it was an accurate reflection of what others were posting. That began to change in 2009, when Facebook offered users a way to publicly “like” posts with the click of a button. That same year, Twitter introduced something even more powerful: the “Retweet” button, which allowed users to publicly endorse a post while also sharing it with all of their followers. Facebook soon copied that innovation with its own “Share” button, which became available to smartphone users in 2012. “Like” and “Share” buttons quickly became standard features of most other platforms.Shortly after its “Like” button began to produce data about what best “engaged” its users, Facebook developed algorithms to bring each user the content most likely to generate a “like” or some other interaction, eventually including the “share” as well. Later research showed that posts that trigger emotions––especially anger at out-groups––are the most likely to be shared.

      The Firehose versus the Algorithmic Feed

      See related from The Internet Is Not What You Think It Is: A History, A Philosophy, A Warning, except with more depth here.

    1. Algorithms in themselves are neither good nor bad. And they can be implemented even where you don’t have any technology to implement them. That is to say, you can run an algorithm on paper, and people have been doing this for many centuries. It can be an effective way of solving problems. So the “crisis moment” comes when the intrinsically neither-good-nor-bad algorithm comes to be applied for the resolution of problems, for logistical solutions, and so on in many new domains of human social life, and jumps the fence that contained it as focusing on relatively narrow questions to now structuring our social life together as a whole. That’s when the crisis starts.

      Algorithms are agnostic

      As we know them now, algorithms—and [[machine learning]] in general—do well when confined to the domains in which they started. They come apart when dealing with unbounded domains.

    1. The way technologies like fMRI are applied is aproduct of our brainbound orientation; it has not seemed odd or unusual toexamine the individual brain on its own, unconnected to others.

      In part because of modalities of studying the brain using methods like fMRI where the images are of an individual's head, we focus too much and too exclusively on single brains bound to individuals rather than on brains working in concert.

      Greater flexibilities in tools and methods should help do studies of humans working in concert.

      Link this to the anecdote:

      I recall a radiology test within a medical school setting in which students were asked to diagnose an x-ray of a human patient's skull. Most either guessed small hairline fractures in the skull or that there was nothing wrong with the patient.

      Can you diagnose the patient?

      Almost all the students failed the question, and worse felt like idiots when the answer was revealed: the patient must be dead because the spinal column and the rest of the body are not attached. Compare:

  19. Mar 2022
    1. computers might therefore easily outperform humans at facial recognition and do so in a much less biased way than humans. And at this point, government agencies will be morally obliged to use facial recognition software since it will make fewer mistakes than humans do.

      Banning it now because it isn't as good as humans leaves little room for a time when the technology is better than humans. A time when the algorithm's calculations are less biased than human perception and interpretation. So we need rigorous methodologies for testing and documenting algorithmic machine models as well as psychological studies to know when the boundary of machine-better-than-human is crossed.

    1. In less than 6 hours after starting on our in-house server, our model generated 40,000 molecules that scored within our desired threshold. In the process, the AI designed not only VX, but also many other known chemical warfare agents that we identified through visual confirmation with structures in public chemistry databases. Many new molecules were also designed that looked equally plausible.

      Although the model was driven "towards compounds such as the nerve agent VX", it found VX but also many other known chemical warfare agents and many new molecules...that looked equally plausible."

      AI is the tool. The parameters by which it is set up makes something "good" or "bad".

    1. The study’s authors suggest that this discrepancy may emerge fromdifferences in boys’ and girls’ experience: boys are more likely to play withspatially oriented toys and video games, they note, and may become morecomfortable making spatial gestures as a result. Another study, this oneconducted with four-year-olds, reported that children who were encouraged togesture got better at rotating mental objects, another task that draws heavily onspatial-thinking skills. Girls in this experiment were especially likely to benefitfrom being prompted to gesture.

      The gender-based disparity of spatial thinking skills between boys and girls may result from the fact that at an early age boys are more likely to play with spatially oriented toys and video games. Encouraging girls to do more spatial gesturing at an earlier age can dramatically close this spatial thinking gap.

    1. Newton arranged an experiment in which one person — a “tapper” — was asked to tap out the melody of a popular song, while another person — the “listener” — was asked to identify it. The tappers assumed that their listeners would correctly identify about 50% of their melodies; they were amazed to learn that the listeners only got about one out of 40 songs correct. To the tappers, their melodies sounded perfectly clear and obvious, but the listeners heard no music, no instrumentation in their heads — only the muffled noise of a finger tapping on a table.

      An example of the curse of knowledge effect.

  20. Feb 2022
    1. The velocity of social sharing, the power of recommendation algorithms, the scale of social networks, and the accessibility of media manipulation technology has created an environment where pseudo events, half-truths, and outright fabrications thrive.

      As it has been stated by Daniel Kahneman, we all are "cognitively lazy." This a very telling statement that helps to reveal the different reasonings of why we are in a world full of "half-truths" but, deeper than that, why we all continue to accept these half-truths. A lot of times we do not want to take the necessary time it takes to evaluate information instead of just accepting things to be true.

    1. Deepti Gurdasani. (2022, January 10). Lots of people dismissing links between COVID-19 and all-cause diabetes. An association that’s been shown in multiple studies- whether this increase is due to more diabetes or SARS2 precipitating diabetic keto-acidosis allowing these to be diagnosed is not known. A brief look👇 [Tweet]. @dgurdasani1. https://twitter.com/dgurdasani1/status/1480546865812840450

    1. Read for Understanding

      Ahrens goes through a variety of research on teaching and learning as they relate to active reading, escaping cognitive biases, creating understanding, progressive summarization, elaboration, revision, etc. as a means of showing and summarizing how these all dovetail nicely into a fruitful long term practice of using a slip box as a note taking method. This makes the zettelkasten not only a great conversation partner but an active teaching and learning partner as well. (Though he doesn't mention the first part in this chapter or make this last part explicit.)

    2. Reading, especially rereading, caneasily fool us into believing we understand a text. Rereading isespecially dangerous because of the mere-exposure effect: Themoment we become familiar with something, we start believing wealso understand it. On top of that, we also tend to like it more(Bornstein 1989).

      The mere-exposure effect can be dangerous when rereading a text because we are more likely to falsely believe we understand it. Robert Bornstein's research from 1989 indicates that we will tend to like the text more, which can pull us into confirmation bias.

      Bornstein, Robert F. 1989. “Exposure and Affect: Overview and Meta-Analysis of Research, 1968-1987.” Psychological Bulletin 106 (2): 265–89.

    3. The linear process promoted by most study guides, which insanelystarts with the decision on the hypothesis or the topic to write about,is a sure-fire way to let confirmation bias run rampant.

      Many study and writing guides suggest to start ones' writing or research work with a topic or hypothesis. This is a recipe for disaster to succumb to confirmation bias as one is more likely to search out for confirming evidence rather than counter arguments. Better to start with interesting topic and collect ideas from there which can be pitted against each other.

    4. “I had [...]during many years followed a golden rule, namely, that whenever apublished fact, a new observation or thought came across me, whichwas opposed to my general results, to make a memorandum of itwithout fail and at once; for I had found by experience that such factsand thoughts were far more apt to escape from the memory thanfavorable ones. Owing to this habit, very few objections were raisedagainst my views, which I had not at least noticed and attempted toanswer.” (Darwin 1958, 123)

      Charles Darwin fought confirmation bias by writing down contrary arguments and criticisms and addressing them.

    5. psychologists call the mere-exposure effect: doing something many times makes us believe wehave become good at it – completely independent of our actualperformance (Bornstein 1989). We unfortunately tend to confusefamiliarity with skill.

      The mere-exposure effect leads us to confuse familiarity with a process with actual skill.

    6. Our brains work not that differently in terms of interconnectedness.Psychologists used to think of the brain as a limited storage spacethat slowly fills up and makes it more difficult to learn late in life. Butwe know today that the more connected information we alreadyhave, the easier it is to learn, because new information can dock tothat information. Yes, our ability to learn isolated facts is indeedlimited and probably decreases with age. But if facts are not kept

      isolated nor learned in an isolated fashion, but hang together in a network of ideas, or “latticework of mental models” (Munger, 1994), it becomes easier to make sense of new information. That makes it easier not only to learn and remember, but also to retrieve the information later in the moment and context it is needed.

      Our natural memories are limited in their capacities, but it becomes easier to remember facts when they've got an association to other things in our minds. The building of mental models makes it easier to acquire and remember new information. The down side is that it may make it harder to dramatically change those mental models and re-associate knowledge to them without additional amounts of work.

      The mental work involved here may be one of the reasons for some cognitive biases and the reason why people are more apt to stay stuck in their mental ruts. An example would be not changing their minds about ideas of racism and inequality, both because it's easier to keep their pre-existing ideas and biases than to do the necessary work to change their minds. Similar things come into play with respect to tribalism and political party identifications as well.

      This could be an interesting area to explore more deeply. Connect with George Lakoff.

    7. Just followyour interest and always take the path that promises the mostinsight.

      What specific factors does one evaluate for determining what particular paths will provide actual (measurable) insight?

      Most people have a personal gut reaction about which directions to go in heuristically, but can these heuristics be broken down explicitly to enable better evaluating them? How can they be used to avoid cognitive biases?

    1. Deepti Gurdasani. (2022, January 30). Have tried to now visually illustrate an earlier thread I wrote about why prevalence estimates based on comparisons of “any symptom” between infected cases, and matched controls will yield underestimates for long COVID. I’ve done a toy example below here, to show this 🧵 [Tweet]. @dgurdasani1. https://twitter.com/dgurdasani1/status/1487578265187405828

  21. Jan 2022
    1. An over-reliance on numbers often leads to bias and discrimination.

      By their nature, numbers can create an air of objectivity which doesn't really exist and may be hidden by the cultural context one is working within. Be careful not to create an over-reliance on numbers. Particularly in social and political situations this reliance on numbers and related statistics can create dramatically increased bias and discrimination. Numbers may create a part of the picture, but what is being left out or not measured? Do the numbers you have with respect to your area really tell the whole story?