In his book Thinking Fast and Slow, which summarizes his life and Tversky’s work, Kahneman introduces biases that stem from misalignment — the false belief that a combination of two events is more likely than one event alone. Conjunction bias is a common error of reasoning in which we believe that two events occurring together are more likely than one of those events to occur on its own. While representativeness bias occurs when we ignore low base rates, conjunction error occurs when we attribute a higher probability to an event with a higher specificity. [Sources: 9]

However, the coincidence of probabilities was not taken into account, and regarding the choice of the model compared to the mean, the author points out that it is difficult to determine exactly which strategy was used by the participants. The observed probability matching behavior suggests that the nervous system samples the hypothesized distribution of the model at each trial. [Sources: 6]

These robust correspondences and discrepancies between human judgment and probability theory challenge non-sampling models of probabilistic bias; Costello and Watts (2014, 2016, 2018) have shown how a sampling model captures both biases and patterns in human probabilistic judgments, demonstrating that these judgments, they say, are, after all, “remarkably rational” and that irrational judgments are the result of noise [Sources: 2]

To illustrate, with one sample, each event will have a probability of 1 (i.e., 1 out of 1) or 0 (0 out of 1). If the brain can sample indefinitely, then under certain circumstances the sampling rates will match the “true” probabilities with arbitrary precision. One of the biggest problems with observational studies is that the likelihood of being exposed or unirradiated to a group is not accidental. [Sources: 2, 3]

The more correct covariates we use, the more accurate our prediction of the likelihood of exposure. We use covariates to predict the probability of exposure (PS). We want to match exposed and unexposed subjects in terms of their likelihood of being exposed (their PS). Below 0.01, we can get a lot of variability within the estimate because it is difficult for us to find matches, and this leads us to discard these items (incomplete match). [Sources: 3]

We would like to see a significant reduction in bias due to inconsistent and consistent analyzes. Ultimately, PSM scores are as good as the characteristics used for comparison. Since all characteristics related to treatment participation and outcomes are observed in the dataset and are known to the investigator, propensity scores provide significant matches for assessing the impact of the intervention. [Sources: 3, 8]

Specifically, PSM will calculate the probability of a unit participating in the program based on the observed characteristics. PSM then compares the processed units with the unprocessed units based on the propensity score. This ensures that units with the same covariate value have a positive chance of healing, but will not be cured. [Sources: 8]

Evaluate the impact of the intervention on the fit sample and calculate the standard errors. Using these coincidences, the researcher can assess the impact of the intervention. The obtained match pairs can also be analyzed using standard statistical methods, for example, Thus, if positive examples are observed in 60% of cases in the training sample, and negative examples are observed in 40% of cases, then the observer using the probability matching strategy predicts (for unlabeled examples) class label “positive.” in 60% of cases and class label “negative” in 40% of cases. [Sources: 3, 5, 8]

But the combination, that is, heads in two-thirds of the cases and tails in one-third of the cases, will be corrected with a probability of (2/3 x 2/3) + (1/3 x 1/3) = 5/9. … While probabilistic matching was a modal response strategy found in the current study, we are not suggesting that probabilistic matching is used in all perception problems, or even in all spatial problems. [Sources: 2, 6]

Recent research has shown that observer behavior is consistent with the expected loss function in a visual discrimination problem [40], but the results are ambiguous with respect to the specific decision-making strategy (mean, choice, and comparison of probabilities) they might make. similar predictions. Moreover, the effects of bias can be explained in terms of setting the response criteria, rather than the goodness-of-fit criteria, as is the case with the Ratcliffe approximations. Different probability distributions, rewards, or changes in context did not affect the results. It is more “rational” because deviations from probability theory arise from its use before improving probability estimates based on a small number of samples. [Sources: 1, 2, 6, 7]

It is also known that Thompson sampling is equivalent to probability matching, a heuristic often called suboptimal, but in fact it can work quite well under the assumption of a non-stationary environment. It also ties in with the converging evidence that participants can use a combination of direct and random exploration in multi-armed bandits, and I’m not sure how this can be accounted for in DBM. I believe that the direct inclusion of information acquisition in the model is analogous to the direct exploration strategy, while the softmax parameter can track random (value-based) exploration. [Sources: 10]

It is clear that the maximization strategy outweighs the coincidence strategy. However, the maximization strategy is rarely found in the biological world. From bees to birds to humans, most animals correspond to probabilities (Erev & Barron, 2005; CR Probabilistic Matching (PM) is a widely observed phenomenon in which subjects compare the likelihood of choice with the likelihood of reward in a stochastic context. [Sources: 1]

Matchmaking strategy is to pick A 70% of the time and B 30% of the time. Combination with substitution reduces distortion by better matching between objects. This effect is especially evident in the no-tip and no-feedback group, where the first ten-reel game was dominated by pairs (bottom right panel). [Sources: 1, 3, 4]

Of those participants who were asked to rate which strategy gives the higher expected return before forecasting, 74% correctly identified the maximization strategy as the best. When comparing these three strategies, the behavior of the overwhelming majority of observers in performing this perceptual task was more consistent with the comparison of probabilities. The third strategy is to select a causal structure in proportion to its likelihood, thus trying to match the likelihood of a putative causal structure. Choosing a matching strategy, subjects violate the axioms of decision theory, and therefore their behavior cannot be rationalized. [Sources: 1, 4, 6]

Based on the theory of optimal foraging (Stephens & Krebs, 1986), IFD predicts that the distribution of individuals between food stalls will match the distribution of resources, a pattern often observed in animals and humans (Grand, 1997; Harper, 1982; Lamb & Ollason, 1993 ; Madden et al., 2002; Sokolowski et al., 1999). There are discrepancies between the model and observed behavior, but foraging groups tend to approach IFD. [Sources: 1]

Indeed, this is the conditional expansion probability given the set of covariates Pr (E + | covariates). Therefore, the likelihood of being exposed is the same as the likelihood of not being exposed. [Sources: 3]

— Slimane Zouggari

##### Sources #####

[0]: https://stats.stackexchange.com/questions/392493/propensity-score-matching-bias-adjustment

[1]: http://naturalrationality.blogspot.com/2007/11/probability-matching-brief-intro.html

[2]: https://journals.sagepub.com/doi/full/10.1177/0963721420954801

[3]: https://www.publichealth.columbia.edu/research/population-health-methods/propensity-score-analysis

[4]: https://link.springer.com/article/10.3758/s13421-012-0268-3

[5]: https://en.wikipedia.org/wiki/Probability_matching

[6]: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1000871

[7]: https://pubmed.ncbi.nlm.nih.gov/2913571/

[8]: https://dimewiki.worldbank.org/Propensity_Score_Matching

[9]: https://fs.blog/bias-conjunction-fallacy/

[10]: https://proceedings.neurips.cc/paper/2018/file/f55cadb97eaff2ba1980e001b0bd9842-Reviews.html

For example, in plant biology, the term “higher plants” is used arbitrarily, without considering its meaning or meaning. If there is a definition of higher plants, then it is synonymous with vascular plants, but the image it evokes is linear and leafy terrestrial plants. The problem is that the above is a condemning term, implying that the group is superior to its non-vascular relatives. [Sources: 6]

Therefore, humans seem to be blind to most living things, not just plants. As for wild plants-those landscapes or foods that are outside of nature and not grown by humans-many of them have not been noticed by humans. [Sources: 4, 7]

One theory suggests that because plants usually grow close together, do not move, and often visually mix, they often go unnoticed in the presence of animals. Some scientists have suggested that this bias against plants may be due to the fact that the plants are immobile, grow close to each other, are often similar in color and visually mix, making it difficult for people to see them outside the uniform green block. [Sources: 0, 10]

Research shows that humans tend to be more interested in animals than plants, and find it harder to spot pictures of plants than pictures of animals. It is well known that humans are better at recognizing animals than plants, and this relative inability of humans to recognize plants is increasingly referred to as “plant blindness.” [Sources: 8, 10]

This phenomenon is known as plant blindness, a form of cognitive impairment that makes people less likely to recognize the presence and importance of plants in their daily lives. Research by Wandersee and Schusslers (2001) has shown that people with plant blindness fail to recognize the importance of plants as part of a larger ecosystem and in our daily life. The historical bias against plants means that children are not fully educated about them in school, and botany degrees in the UK are already out of date. [Sources: 1, 9]

One of the key factors for this underestimation of plant life may be the education and teaching methods of plant biology. Not only are general concepts taught in animals, but in comparison with zoology and human biology, the class time of plant biology is usually very small. For example, in biology textbooks, plants have much smaller space than animals, and students may feel that plants are not important. [Sources: 2, 4, 10]

Environmentalists view plants as a value in their own right, so it might seem odd to propose advocating plant conservation by thinking about how plants are like humans. At Natural Plants, we try to maintain a Catholic attitude towards what constitutes a plant and, above all, what will be of interest to plant biologists. [Sources: 6, 10]

However, much of the discussion in these studies focuses on what the similarities of these organisms to angiosperms can tell about the history of colonization of terrestrial plants, and even more so about their remarkable features and characteristics. Now, in a new review published in the journal Conservation Biology, biologists Mung Balding and Catherine Williams of the University of Melbourne in Australia looked at previous research to understand why this bias against plants exists and whether it can be changed. [Sources: 0, 6]

This bias is attributed to perceptual factors such as the lack of movement of plants and their tendency to visually mix with each other, as well as cultural factors, such as the increased focus on animals in formal biological education. Wandersee and Schussler (2001) also note that students (at least in the US and my personal experience in the UK) are taught less about plants than about animals (read about vertebrates), so this also helps to restore information bias. which pushes plants into the background. The fact that we are less likely to notice and like plants also has important consequences for their conservation, as we are more likely to care about what we notice and see. [Sources: 2, 7, 11]

Consequently, conservation programs can help reduce this bias. Several cultural and cognitive aspects have been suggested as implicit, and suggestions have been made to overcome this bias and the attendant impact it has on the level of support provided in areas such as investment and training in plant research and conservation work. In a new survey study, researchers are examining why humans, including conservationists, tend to bias plants and whether that bias can be challenged. [Sources: 0, 3, 11]

Plant blindness is a cognitive bias, in the broadest sense, it represents a person’s tendency to ignore plant species. Wandersee and Schussler (2001) defined plant blindness as the inability to see or notice plants in the environment. The term “plant blindness” was first coined by two American botanists (Wandersee and Schuessler) more than 20 years ago. They used it to describe “the inability to notice plants in the environment”, which is reflected in the underestimation and inability of plants. Recognize their importance (1). This can have a huge impact on many different sectors, from plant biology research to protection and legislation. [Sources: 1, 2, 12]

The problem is that if most people are oblivious to plants and the vital role they play in sustaining life, society is unlikely to accept that plant conservation is one of the greatest challenges for humankind. Not to mention supporting research and education in plant science. … In fact, it is not difficult to conclude that such repeated exposure to anthropocentric classification of plants as inferior to animals leads to the erroneous conclusion that they do not deserve human attention. Our tendency to favor animals over plants, treating them only as reference material, has long troubled scientists. [Sources: 1, 4, 5]

Whether caused by innate biology or social education and upbringing, plant blindness is present in our modern societies, and in order to lessen its impact, we need to change the way we look at plants and their meaning. Here I argue that contempt for any non-vertebrate organism (like us) is the most common problem, but fighting plant blindness is a good starting point for improving education, awareness and concern for other organisms we live with on the same planet. … Earth. [Sources: 2, 7]

I wanted to discuss this topic today because as a scientific communicator and plant enthusiast, I hope this podcast series will help address the issue of plant blindness and awaken curiosity about plants and other neglected organisms. In addition to this podcast, if you feel like plants are something of a blind spot in your knowledge, be sure to check out Britannicas’ articles, lists and other stories about plants. Understanding and identifying plants shouldn’t be a niche interest – we need to encourage more interaction with plants, and apps like Google Lens can be a fantastic way to do this, as long as they’re not blind to the plants themselves. Research has already reported that existing biases are programmed in artificial intelligence, so it might not be surprising that we could also program plant blindness in general identification applications. [Sources: 4, 8]

Without dismissing these prejudices, Wandersee and Schuessler argue in an article published in the Plant Science Bulletin that the main cause of plant blindness is the nature of the human visual information processing system (www.botany.org/bsa/psb/2001/ psb47 -1 .pdf). Since plants are static, they blend in with the background and do not eat people, they usually do not attract visual attention. Their research and that of other biology teachers have shown not only that most students prefer to study animals over plants, but that the first experience of growing plants with a knowledgeable and friendly mentor is a good predictor of students’ later interest in plants. [Sources: 5]

— Slimane Zouggari

##### Sources #####

[0]: https://psmag.com/news/can-plant-blindness-be-cured

[1]: https://study.soas.ac.uk/curing-our-plant-blindness-how-we-can-protect-the-planet-this-earth-day/

[2]: https://www.ecos.org.uk/undergraduate-highly-commended-plant-blindness-the-botanical-bias-that-no-one-has-heard-of/

[3]: https://www.summerfieldbooks.com/product/plant-blindness/

[4]: https://www.britannica.com/podcasts/botanize/Botanize-podcast-plant-blindness

[5]: https://academic.oup.com/bioscience/article/53/10/926/254897

[6]: https://www.nature.com/articles/s41477-020-00777-x

[7]: https://nph.onlinelibrary.wiley.com/doi/full/10.1002/ppp3.36

[8]: https://www.botany.one/2020/02/plant-blindness-in-smartphone-identification-applications-are-we-passing-on-our-biases-to-our-helpful-apps/

[9]: https://www.danforthcenter.org/news/creating-new-solutions-for-plant-blindness/

[10]: https://theconversation.com/people-are-blind-to-plants-and-thats-bad-news-for-conservation-65240

[11]: https://pubmed.ncbi.nlm.nih.gov/27109445/

[12]: https://www.sciencetimes.com/articles/20946/20190504/plant-blindness-lead-disastrous-consequences.htm

In contrast, Connell-Price and Jamison (2015) [22] reported that more “myopic” people (with bias at present) exercised more, and this finding can be partially explained by satisfying exercise. the standard view in the literature of exercise as “future-oriented” preventive health behavior. We hypothesized that those who maintained regular physical activity during surgery were less prone to bias, more patients (and therefore more interested in long-term health and financial benefits), while inactive people were more prone to bias about the present. and impatience. and they more seriously ignore both types of future benefits. A joint assessment of timing and risk preferences based on observed diabetes management decisions would be very difficult and therefore beyond the scope of this study. [Sources: 2, 5]

Since existing prejudices may increase people’s uncertainty about the effectiveness of compliance delaying diabetes complications, it may be appropriate to propose a package of interventions to improve compliance in practice. Discussion and conclusions This study uses a dynamic discrete choice model to evaluate the prejudice and naiveness of human decision-making, and uses the decisions of people diagnosed with diabetes to follow evidence-based guidelines as a case study. The following cases show that we have made very different decisions for the present and the future. [Sources: 5, 7]

Obviously, we spend our day making decisions with different cognitive biases. For example, anchor bias forces us to place too much emphasis on the first information we encounter. Due to the optimism bias, we consistently underestimate the time or cost of a project – all of you DIY enthusiasts know this all too well. And the country fights against confirmation bias, our tendency to seek or accept only evidence to support our beliefs. [Sources: 11]

Current bias is the tendency to settle for less reward in the present, rather than expect more reward in the future in a compromise situation. In the field of behavioral economics, the current bias is associated with hyperbolic discount, which is temporally constant. Present bias occurs when people place more emphasis on the goods / income they have received in the moment, rather than receiving the same goods / income in the future. [Sources: 3, 4]

This assumes that you can choose between paying today and paying in the future; we will choose the award now. This suggests that people may be inconsistent over time, making decisions that they may regret in the future. This happens when we discount the value of future premiums by a factor that increases with the length of the delay. [Sources: 3]

We tend to choose a smaller immediate reward over a larger future prize because it instantly makes us happy. Simply put, when given the opportunity to choose between less reward right now and more reward in the future, people tend to choose immediate reward. True bias describes our tendency to choose less immediate reward for more in the future. Research shows that taking the time to imagine yourself in the future may motivate us to choose long-term benefits over instant gratification. [Sources: 7, 10]

At the beginning of each day, imagine that by the end of the day you are completely satisfied. By following this routine, your present self is doing everything it can to help yourself in the future. Thus, you will save your future from the mistakes that the present makes. Well, being able to predict your future behavior means that your current self has the ability to help yourself in the future. [Sources: 7, 10]

The immediacy of reward in such interventions may substantially ignore the individual’s bias in the present, encouraging the participant to engage in health behaviors now, with health benefits in the future. The public health implications of this are significant, as people who are biased about the present exhibit self-control problems and are unlikely to give up current rewards for future health benefits unless current incentives are paid. Ongoing biased decision-making often underlies the idea that certain health behaviors are cost-effective in the first place, with benefits only coming later. Plus, hyperbolic discounting prevents you from seeing the benefits of making long-term decisions. [Sources: 2, 4, 7]

Since this is only possible in an ideal economy, wealth inequality arises from the fact that people working in time benefit from irrational monetary decisions made by biased economic rivals. But perhaps this paradoxical result is also explained by behavioral economics. And ING research shows that about half of people in 13 European countries say they run out of money from time to time or most of the time at the end of their payroll period, so it’s no surprise that many today take guaranteed money and use it directly. … In other words, it was found that people prefer immediate benefits to future ones, because their discount decreases rapidly over a short period of time, while the discount decreases the smaller the future premiums are. [Sources: 4, 9, 11]

Behavioral economics softens the traditional assumption that consumers behave rationally when given enough information. Economic models use a present bias, also known as dynamic inconsistency, to explain the distribution of wealth. [Sources: 4, 11]

According to ODoghue and Rabin (1999), d is the standard discount factor, which reflects long-term and permanent time preference, and b is the current bias factor, which reflects short-term impatience. A complex person who makes decisions at any period t, correctly knows the real bias of the future “I” b and accurately foresees his behavior, making decisions at the period t of the future “I”, that is, b ~ = b. [Sources: 5]

People who see their present and future as more alike also show more patience when choosing a reward. McClure’s dual system model argues that these areas of the brain are impulsively activated by immediate benefits rather than future rewards. Thus, students’ responses indicate that they can do future mentoring (average 85 minutes), whereas they will do it less often now (average 27 minutes). [Sources: 4, 7]

On the other hand, deadlines do not increase the completion percentage in our experiment. We document the high demand for commitments in terms of the deadlines we set. In his blog post on procrastination and temporal inconsistency, Clear gives examples of this exercise, such as imagining that you will lose weight in the future. [Sources: 6, 7]

External and internal consistency of choices made in convex time budgets. Expected returns, limited liquidity, and intertemporal choice anomalies. Consistency and heterogeneity of individual behavior under conditions of uncertainty. [Sources: 1]

When we fail to eat healthier foods, save more, or make progress towards our goals, we dig holes and allow our future selves to try to find a way out. Your financial health will improve and you will be able to fulfill your current commitments and achieve your future goals. After graduating from college, she now has a stable job and a salary that covers rent, transportation, utilities and other monthly expenses. He is 35 years old and has been thinking about saving for a pension for some time. [Sources: 0, 10]

— Slimane Zouggari

##### Sources #####

[0]: https://www.santander.com/en/stories/how-the-present-bias-influences-our-personal-finances

[1]: https://link.springer.com/article/10.1007/s10683-019-09617-y

[2]: https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-018-6305-9

[3]: https://www.economicshelp.org/blog/glossary/present-bias/

[4]: https://en.wikipedia.org/wiki/Present_bias

[5]: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6594564/

[6]: https://www.sciencedirect.com/science/article/pii/S0899825619301757

[7]: https://clockify.me/blog/managing-time/present-bias/

[8]: https://www.behavioraleconomics.com/resources/mini-encyclopedia-of-be/present-bias/

[9]: https://think.ing.com/articles/what-is-present-bias-the-consequences-of-instant-gratification/

[10]: https://blog.doist.com/present-bias-comic/

[11]: https://www.cincinnati.com/story/money/2018/08/28/present-bias-retirement-savings-paradox/1120777002/

Although optimism bias comes from positive events (for example, believing that you are financially more successful than others) and negative events (for example, you are less likely to have alcohol problems), there is more research and evidence that the bias is stronger. Negative events (valency) effect). Studies have shown that people are less optimistic when they are negative, but are more optimistic when they are positive. Although researchers try to help people reduce their optimistic biases, especially by promoting healthy lifestyles and reducing risky behaviors, they find that reducing or eliminating prejudice is actually very difficult. In studies that included the following actions to reduce optimism bias, researchers found that these attempts were rare, such as educating participants about risk factors, encouraging volunteers to consider high-risk examples, educating participants and explaining why they are at risk middle. What did they give. This has changed, and in some cases even increased optimism bias. [Sources: 4, 10]

Moreover, surveying people in these demographic groups could be considered more “rational” as their beliefs are more factual, with less optimism bias and pessimistic bias. In addition, research is needed to find out if more positive moods can protect populations from the effects of negative emotions without negatively impacting adherence to public health guidelines.31 In addition, in this study, we have demonstrated that older adults, people with higher levels of emotional activity … education and those who worked or studied in a medical-related field tended to be lower in pessimism and magical beliefs. [Sources: 2]

Research is needed to understand whether other cultures with interdependent self-esteem exhibit a lack of optimism bias when assessing the relative risk of experiencing negative and positive events. Unrealistic optimism and pessimism are event-related prejudices, “expressed by individuals, but measured at the group level” (Jansen et al., 2011, p. 2). The opposite of optimistic bias is pessimistic bias (or pessimistic bias), because the principle of optimistic bias continues to apply to situations where people think they are inferior to others. Pessimistic bias is a cognitive bias that causes people to overestimate the possibility of negative events and underestimate the possibility of positive things, especially when it comes to the assumption that future events will produce negative results. [Sources: 1, 6, 10]

Finally, please note that in some cases, people display optimistic biases rather than pessimistic biases, including underestimating the possibility of negative things and overestimating the possibility of positive things. Whether they show a particular bias depends on various factors. People may show optimistic bias in some situations and pessimistic bias in other situations. Optimism bias (or optimism bias) is a cognitive bias that causes someone to believe that they are unlikely to experience negative events. Pessimism can mean focusing on the dark side of a situation or event, expecting negative results, or lacking hope for the future. [Sources: 1, 5, 10]

Although a certain degree of pessimism is necessary and can also play a protective role, excessive pessimism or unbalanced pessimism can lead to poor mental health and may force people to self-discipline, leading to loss of growth and success. Chance. Challenging unrealistic pessimistic ideas, such as “There is no way to get this job” or “No one understands me” can help people realize that some of their pessimistic beliefs are not rooted in reality. For example, it may involve using your pessimism as a motivation to prepare for important future events. [Sources: 1, 5]

Optimism can help entrepreneurs persevere in adversity, but it can also motivate them to take risks regardless of the consequences. The conundrum of optimism bias Optimism bias increases the belief that no matter what good things happen to you, it will happen in your life, but it can also lead to wrong decisions because you are not worried about risks. Optimism bias is actually a misunderstanding that our chances of experiencing negative events are lower than our peers, while our chances of experiencing positive events are higher than our peers. [Sources: 0, 4]

Regulatory models show that optimistic and pessimistic behavioral biases can be adaptive in the face of risk or uncertainty. Some people may also be more prone to bias than pessimism, which means they are more likely to overestimate the likelihood of a negative outcome. Second, as with many similar psychological phenomena, there is considerable variation in how people experience pessimism bias, which means that different people will experience this bias to varying degrees in different situations. As a result, this biased information influences decisions in risky situations in ways that may not be optimal.27 As negative emotions build up, people may rely more on negative evidence about COVID-19 to form their opinion than other data. [Sources: 1, 2, 3, 5]

For example, it can make you overestimate the likelihood that something bad will happen to someone you care about, or overestimate the likelihood that past events will end in negative outcomes. It is believed that the operation of this self-centered bias leads to unrealistic optimism about rare negative events and unrealistic pessimism about frequent negative events. People experience the most optimism bias when they think that events are under the direct control and influence of a person. [Sources: 1, 4, 6]

Non-entrepreneurs are most likely the most irrational because their beliefs are overly pessimistic. I suspect the lesson is that pessimistic prejudice undermines everything that people perceive as the status quo. In the United States, people (oddly) perceive laissez-faire as the status quo, so pessimism helps the government grow. But where government is the status quo, pessimism can and often pushes in the opposite direction. [Sources: 0, 8]

Talking to a friend or loved one who is prone to optimism can open up more optimistic outlooks for the pessimistic person. This study suggests that both pessimism and optimism are essential for human survival, and that the connection between the left and right brain hemispheres can help people find a healthy balance between pessimistic and optimistic views. As for the optimistic bias, when people are confronted with the average person, regardless of whether they are of the same gender or age, the target is still seen as less human and less personalized, leading to less favorable comparisons between themselves and others. … Third, this “negative bias” is further reinforced in the age of social media. [Sources: 5, 9, 10]

Optimism bias is widespread and transcends gender, race, nationality, and age. In a study in which participants directly compared probability estimates, respondents in Japan and the United States showed unrealistic optimism about rare negative events and unrealistically pessimistic attitudes toward frequently occurring negative events ( Rose et al., 2008). In a study in which participants directly compared probability estimates, respondents in Japan and the United States showed unrealistic optimism about rare negative events and unrealistically pessimistic attitudes toward frequently occurring negative events ( Rose et al., 2008). [Sources: 6, 10]

There is more evidence that the base interest rate is biased towards optimistic/pessimistic positive development. Analysis shows that this effect is partly due to self-centered bias and partly due to lack of self-improvement bias. Compared with participants working in other working groups, participants working in the medical field had better overall scores in terms of optimistic bias, pessimistic bias, magical beliefs, and conspiracy theory beliefs (1129.96, 1029.56, 1072.57, and 1057.59, respectively). Low. (P value <0.01). [Sources: 2, 6, 7]

— Slimane Zouggari

##### Sources #####

[0]: https://hbr.org/2014/02/entrepreneurs-dont-have-an-optimism-bias-you-have-a-pessimism-bias

[1]: https://effectiviology.com/pessimism-bias/

[2]: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8103486/

[3]: https://www.sciencedirect.com/science/article/pii/S2352154616301875

[4]: https://www.verywellmind.com/what-is-the-optimism-bias-2795031

[5]: https://www.goodtherapy.org/blog/psychpedia/pessimism

[6]: https://www.frontiersin.org/articles/10.3389/fpsyg.2013.00006/full

[7]: https://journals.sagepub.com/doi/10.1177/01461672012712006

[8]: https://www.econlib.org/archives/2007/07/the_consequence.html

[9]: https://www.brookings.edu/blog/future-development/2019/06/13/why-are-we-so-pessimistic/

[10]: https://en.wikipedia.org/wiki/Optimism_bias

[11]: https://psychology.fandom.com/wiki/Pessimism_bias

If the result is not good for you, think about what you missed when making the decision. Try to write down all the conclusions you have reached after receiving the results. If random factors will affect the decision, please do not judge by the result. By evaluating your process, you can make better decisions in the future without letting the bias in the results affect your judgment. [Sources: 5, 7]

By evaluating the process and the outcome, we can make better decisions in the future. Learning to avoid resulting bias can help improve the quality of decision-making. Thus, it is important to understand outcome bias and how it affects us; can help you make better and more effective decisions and avoid unnecessary suffering and loss in the future. [Sources: 3, 4]

Outcome bias is a cognitive bias that allows us to judge decision making based on the outcome of a process, rather than the quality of the process itself. A manager who makes decisions on the basis of “intuition” – when his team strongly advises him in one direction and the manager goes in another – will consider his process to be good if he gets a positive result from it. A manager who makes decisions based on his “intuition” – one who goes in the opposite direction because his intuition says so when his team strongly advises him in one direction – will trust his intuition if he gets a positive outcome. These managers suffer from confirmation bias: their false belief in their instincts is confirmed (which increases their self-confidence) when, fortunately, the result is in their favor. [Sources: 3, 9]

Results bias is applied to leaders (such as superintendents) because often their process and decision-making process is ignored and people focus solely on results, whether those results are consistent with leadership positions or not. Finally, outcome bias can be detrimental to decision-makers, such as doctors or politicians who are agents of others, because when the results are negative, people blame the agent for not being able to predict a negative outcome in the decision-making process. To avoid the influence of outcome bias, the decision should be evaluated by ignoring the information gathered ex post and focusing on what is the correct answer or whether it was at the time the decision was made. While the bias in the assessment of past events is very similar to the bias in the outcome, which unduly influences the assessment of events in the past, the bias in the judgments of the quality of decisions is the bias of the results, not the bias of the retrospective analysis. [Sources: 6, 7, 8]

In a recent study looking at outcome bias in legal decision-making, it was found that judges felt that a particular person acted more deliberately when that person’s actions produced a dramatically negative outcome than an outcome. Moderately negative (Kneer & Bourgeois-Gironde, 2017). Moreover, in hindsight, people tend to allow the consequences of a particular decision or action to unduly influence their judgments about the quality of that action or decision in such a way that they are more perceived negatively after a negative outcome and after a positive outcome (e.g. outcome bias; Baron & Hershey , 1988). [Sources: 8]

Because of retrospective analysis and inferences, decisions made by the director that seemed reasonable at the time could be perceived as careless if the outcome was unsuccessful (for example, retrospective bias includes the tendency of retrospective observers to reject any possibility that the outcome of a decision could be accepted in different ways (that is, although they are quite similar, the difference between the two is that retrospective bias causes an inaccurate view of the past due to distorted memory of events, while its relative importance causes a person to attach too much importance to the result More important than other information, Hawkins and Hasti describe hindsight bias as the inability to recreate a previous causal model that would have been available if the adaptive information of the processing mechanisms had not updated it so quickly based on feedback from outcome to. [Sources: 4, 7, 8, 10]

One possibility comes from a study by Slovic and Fischhoff, 8 who found that retrospective bias can be reduced by asking people to think about how other possible outcomes might have happened. [Sources: 10]

When coaches and teams come back to watch videos of past games, they may encounter biased results because they determine the quality of player decisions based on the results rather than analyzing the overall situation. When evaluating the behavior of others, most people pay more attention to the outcome of the decision rather than the intention. Psychologists call this phenomenon result bias. When employees are judged based on their performance rather than the quality of their decisions, result bias comes into play. When people judge the quality of a leader’s decision, they tend to focus more on the result than the intention. [Sources: 0, 7]

In such situations, asking the evaluators of candidates to make decisions about them before checking whether the decisions made by the candidate have led to good or bad results for the organization will ensure an impartial process. In these situations, making decisions about them before looking to see if their decisions led to positive or negative results will provide you with an impartial process. [Sources: 0, 9]

If you have reason to believe that someone’s decisions are made at the highest level, do not blame them for a negative result. Neither a bad result means a bad decision, nor a good result means a good decision. Usually, you assume a good solution for a good result and a mistake or a bad solution for a bad result. [Sources: 2, 5]

Sooner or later, he makes egregious decisions based on his confidence in previous results. A decision made with good intentions and sufficient thought may be criticized for not being successful. Outcome bias is your tendency to judge a decision based on its final outcome rather than the quality of the decision at the time it was made. [Sources: 5, 9]

This leads to blaming employees and managers for negative results, even if they had good intentions and made informed decisions with all the information that needs to be considered. This effect affects decision-makers, from students to business leaders and football coaches, often causing them to repeat inappropriate decision-making processes. Individuals whose judgments are affected by outcome bias are likely to hold decision-makers accountable for events beyond their control. Retrospective bias is the tendency of people with knowledge of the outcome to exaggerate the degree to which they could have predicted an event in advance, while outcome bias refers to the effect of knowledge of the outcome on judging the quality of decisions. [Sources: 4, 6, 9, 10]

They found that information about results consistently influences assessments of decision quality, the competence of decision-makers, and the willingness to allow decision-makers to make decisions for the subject. Although the interviewed respondents felt that they did not need to take the results into account when making assessments, they did. [Sources: 10]

However, when participants made their assessments individually, the well-meaning physician’s assessments did not differ from those of the selfish physician, suggesting that individual assessors were less likely to be affected by biases than collaborative assessors. In one study, we found that requiring evaluators to make judgments about the choice of decision-makers before the results of those results are known reduces results bias in the context of joint assessment, but not in the context of separate assessment. [Sources: 0]

— Slimane Zouggari

##### Sources #####

[0]: https://hbr.org/2016/09/what-we-miss-when-we-judge-a-decision-by-the-outcome

[1]: https://www.macmillandictionary.com/us/dictionary/american/outcome-bias

[2]: https://towardsdatascience.com/focus-on-decisions-not-outcomes-bf6e99cf5e4f

[3]: https://www.interaction-design.org/literature/article/outcome-bias-not-all-outcomes-are-created-equal

[4]: https://fallacyinlogic.com/outcome-bias/

[5]: https://productiveclub.com/outcome-bias/

[6]: https://en.wikipedia.org/wiki/Outcome_bias

[7]: https://www.developgoodhabits.com/outcome-bias/

[8]: https://onlinelibrary.wiley.com/doi/full/10.1111/jasp.12722

[9]: https://coffeeandjunk.com/outcome-bias/

[10]: https://qualitysafety.bmj.com/content/12/suppl_2/ii46

[11]: https://skybrary.aero/articles/hindsight-and-outcome-bias

While the first of these approaches, physical avoidance, is most commonly associated with information avoidance in general and the ostrich effect in particular, each of these approaches is an effective way of avoiding unpleasant information. While the ostrich effect is usually viewed in a negative light because it represents an irrational decision to avoid information even in cases where such information can lead to an overall positive outcome, avoiding general information is not necessarily bad. situations in which this can be useful. Hence, you should be aware that even if you are looking for more information than usual due to the meerkat effect, you can still avoid useful information to some extent due to the ostrich effect. Ignoring does not mean not knowing, but deliberately avoiding data and information. [Sources: 5, 6]

We try to avoid unpleasant truths in the hope that if we don’t face a problem, it doesn’t exist. Ignoring a problem can make it worse, but it doesn’t exist in your head until you encounter it. If we ignore the problem and don’t think about its consequences, we will also avoid the negative feelings that it usually causes. Because we avoid cognitive dissonance and choose to maintain a positive image of ourselves, if this issue forces us to rethink some of our aspects and forces us to admit that we were wrong, we may choose to avoid it. [Sources: 0, 5]

Research points to a cognitive bias called the “ostrich effect,” in which people figuratively dip their heads in the sand and avoid information they think might be unpleasant. In particular, they may ignore information presented to them, or they may interpret this information in such a way as to ignore potentially disturbing consequences. One study, for example, found that investors are more likely to control the value of their personal portfolios when markets generally rally, but less likely to do so when markets are flat or falling. [Sources: 4]

For example, in a bear market, investors may ignore their portfolios in an effort to avoid negative information. Another example is when people avoid checking their bank account balance for fear of what the position might be. Finally, another common example of the ostrich effect is when people deliberately avoid information that can help them track the progress they are making towards their goals. [Sources: 6, 11]

Thus, falling prey to the ostrich effect means avoiding important information on how to improve. Obviously, they cannot cut their losses early and, ignoring this information, run the risk of worsening the situation. Avoiding information, postponing decisions, or postponing unpleasant situations later on leads to much worse consequences. When you go astray, you sometimes actively (but unconsciously) avoid bad news, even if it contains important information. [Sources: 7, 9, 12]

Carnegie Mellon University behavioral economist George Loewenstein coined the term “ostrich effect” to describe how investors bury their heads in the sand in a bad market. If you do not observe your behavior and thinking in critical situations, the ostrich effect will affect your thinking and make you react negatively to unwanted information. The ostrich effect bias is the tendency to ignore danger or negative information by ignoring dangerous or negative information or burying your head in the sand. The ostrich effect is a cognitive bias that causes people to avoid information that they think may be unpleasant. [Sources: 3, 7, 12, 13]

The ostrich effect, also known as the ostrich problem, is a cognitive bias that describes how people often avoid negative information, including feedback, that can help them track progress towards goals. It is a cognitive bias that causes people to avoid negative information, including any feedback that might help them understand how their goals are being achieved, especially when the information is perceived as unpleasant, unwanted, or elicits a strong negative emotional reaction. Ostrich effect bias is the tendency to avoid negative information and refuse to accept objective truth because it hurts. The meerkat effect is related to the ostrich effect, as both biases affect how people process information, especially when it comes to deciding whether to receive it or not. [Sources: 3, 6, 7, 10]

Galai & Sade (2006) used a psychological explanation they called the “ostrich effect” to explain the difference in profitability in fixed income markets, and attributed this abnormal behavior to a dislike of receiving information about potential temporary losses. According to the same article, Galai and Sade (2006) coined the phrase “ostrich effect”, which they attributed to abnormal behavior and reluctant to receive information about potential temporary losses. Dwayne Seppi stated that individuals are looking for 50% of the value of their investment. Reduce the frequency by 80% during negative market periods to avoid recurring bad news. In behavioral economics, the “ostrich effect” refers to the tendency to avoid negative financial information. In the field of finance and investment, this behavior can be partly attributed to the disposal effect: even if there is no logical meaning, it tends to minimize the perceived financial loss. [Sources: 2, 3, 8, 12]

They found that people who are very worried about their finances tend to ignore potential money problems and are less likely to seek help or seek a solution. [Sources: 12]

Another study from the University of Minnesota, for example, found that 20% of people who signed up for a weight loss program never weighed themselves, indicating that they were avoiding confirming signs of a problem. However, we humans tend to do this and it is considered a serious cognitive impairment. We come to the sobering conclusion that nation states and corporations are also exposed to the dangers of the cognitive biases to which we, as individuals, are exposed. Now that we know why organizations can be subject to these prejudices, we can better prepare ourselves to mitigate the impact of such future disasters. [Sources: 0, 5, 11]

Avoiding inconvenient information doesn’t make you stupid; it just confirms that you are human. Thus, learning to accept discomfort becomes an important step in overcoming your prejudices and finding information that may be unpleasant at first, but can save you a lot of mental anguish in the future. But even unconsciously turning into the notorious ostrich, over time your problems will only grow. [Sources: 7, 12]

If you’re a jaded ostrich and want to break the cycle of avoidance, there are several ways to prepare yourself for success. Write down the problems you encounter while avoiding information, and refer to them from time to time as a helpful reminder of the importance of dealing with such situations in a timely manner. [Sources: 7, 8]

In some situations, when we are too emotional and the situation makes us feel scared, it may be appropriate to seek help from an outside observer who can evaluate the situation more objectively and tell us whether we are really avoiding the problem. Without acknowledging that there is a problem, we will not actively collect information so that we can evaluate all options and formulate the best solution. [Sources: 5]

— Slimane Zouggari

##### Sources #####

[0]: https://ecotalker.wordpress.com/2020/04/21/everyones-an-ostrich-the-ostrich-effect-in-the-context-of-covid-19/

[1]: https://breakingdownfinance.com/finance-topics/behavioral-finance/ostrich-effect/

[2]: https://en.wikipedia.org/wiki/Ostrich_effect

[3]: http://writer.meteo24.nazwa.pl/hit/the-ostrich-effect-short-story

[4]: https://www.mckinsey.com/business-functions/strategy-and-corporate-finance/our-insights/bias-busters-lifting-your-head-from-the-sand

[5]: https://psychology-spot.com/ostrich-effect/

[6]: https://effectiviology.com/ostrich-effect/

[7]: https://www.techtello.com/ostrich-effect/

[8]: https://www.psychologytoday.com/us/blog/loaded/201904/the-ostrich-effect

[9]: https://educ8all.com/cognitive-bias-ostrich-effect/

[10]: https://www.shortform.com/blog/ostrich-effect/

[11]: http://econowmics.com/the-ostrich-effect/

[12]: https://coffeeandjunk.com/ostrich-effect/

[13]: https://www.thinkingcollaborative.com/stj/ostrich-effect

The more optimistic a person was, the higher the activity in these regions when imagining positive future events (in comparison with negative ones) and the stronger the connection between the two structures. When contemplating an accident such as a broken leg, rACC activity modulated signals in an area called the striatum, which conveyed the positive and negative aspects of the event in question, polarizing the activity in a positive direction. [Sources: 0]

Only recently have we been able to solve this mystery by scanning the brains of people who process positive and negative information about the future. We now turn to describing a new study in which we explore how people combine good news and bad news into their beliefs about the possibility of experiencing positive and negative life events, while trying to avoid the two pitfalls mentioned above. [Sources: 0, 11]

We find optimistic renewal biases for negative and positive life events. After correcting the mistakes we found in the experiment of Shah et al., it revealed the optimistic update error of positive life events. The optimistic update bias of positive incentives has been described previously (Krieger et al., 2014; Wiswall and Zafar, 2015). [Sources: 11]

Together, these relationships constitute a strong argument for true optimistic asymmetries in belief renewal. Based on this data, it is suggested that the rostral ACC plays a critical role in creating positive images of the future and, ultimately, in providing and maintaining an optimism bias. [Sources: 11, 15]

There is some evidence that personality optimism can interact with optimism bias and exacerbate the adverse effects of bias on information processing (Davidson and Pukachin, 1997), although this study measures optimism bias as the sum of risk scores for different events. No precise test is used. Although optimism bias comes from positive events (such as believing that you are financially more successful than others) and negative events (such as less likely to have alcohol problems), there is more research and evidence showing that bias is more Strong negative events (valency effect). [Sources: 10, 15]

Optimism bias is actually a misunderstanding that our chances of experiencing negative events are lower than those of our peers, while our chances of experiencing positive events are higher than our peers. This is called optimism bias: the tendency to overestimate the possibility of experiencing positive events in the future and underestimate the possibility of experiencing negative events. The belief that the future may be much better than the past and present is called optimism bias. Most of us have this tendency to overestimate the possibility of positive events that happen to us and underestimate the possibility of negative events. . [Sources: 3, 5, 7]

For example, people severely underestimate their chances of losing their job or getting a cancer diagnosis. People seriously underestimate the chances of divorce, unemployment, or being diagnosed with cancer; they expect their children to have extraordinary talents; imagine that they get more than their peers; and overestimate their possible life expectancy (sometimes 20 years or more) Long time). However, the data clearly shows that most people overestimate their chances of career success; they expect their children to have extraordinary talents; they miscalculate their possible life expectancy (sometimes twenty years or more); expectations They are healthier than ordinary people and more successful than their peers; they seriously underestimate the possibility of divorce, cancer and unemployment; in general, they believe that their future life will be better than their parents’ experience. [Sources: 2, 5, 7]

Part of the reason for the phenomenon of optimism bias is that we tend to present future events more vividly and positively, thereby making them more likely to happen,” says Shalott, whose book of the same title delves into this topic. Optimism bias is a misunderstanding. , Believes that our chances of experiencing positive events are higher than those of our peers, and our chances of encountering unwanted events are lower than those of our peers. [Sources: 4, 6]

You can also be optimistic about being overly confident about the objective chances of experiencing a positive event (or avoiding a negative event), no matter how much your odds compare to those of your peers. When comparing their own risk to that of others, people are self-centered because they focus more on their own risk factors than on those of their peers (Chambers & Windschitl, 2004); indeed, reducing this selfishness appears to weaken prejudice (Weinstein, 1983), and this self-centeredness can lead people to become unrealistically pessimistic about rare positive or common negative experiences (e.g. Chambers, Windschitl, & Suls, 2003; Kruger & Burrus , 2004). As for the optimistic bias, when people are confronted with the average person, regardless of whether they are of the same gender or age, the target is still seen as less human and less personalized, leading to less favorable comparisons between themselves and others. … People are less likely to experience an optimism bias when they encounter very close people, such as friends or family. [Sources: 3, 10, 15]

Research has shown that people are less optimistic when they are in negative moods and more optimistic when they are in positive moods. Quantitative data on the levels of optimism and pessimism in depressed patients showed that optimism bias was positively associated with low levels of depression. Optimism was also associated with physical health. Research findings that optimists live longer and healthier lives, coupled with the fact that most people display an optimistic bias, and emerging evidence that optimism is associated with specific genes, all strongly support this hypothesis. It is tempting to assume that optimism was chosen by evolution precisely because, in the end, positive expectations increase the odds of survival. [Sources: 0, 1, 5, 15]

Others believe that unrealistic optimism is a personality trait rather than a cognitive bias, and therefore more often expressed in certain groups of people, such as smokers or gamblers (Shah et al., 2016). Importantly, this series of studies overestimated unrealistic optimism as the concept of cognitive bias in human judgment and decision-making, and provided a mathematical formalization and neurobiological framework for this (Moutsiana et al., 2015; Kuzmanovic and Rigoux, 2017). In studies that included the following actions to reduce optimism bias, researchers found that these attempts were rare, such as educating participants about risk factors, encouraging volunteers to consider high-risk examples, educating participants and explaining why they are at risk middle. What did they give. This has changed, and in some cases even increased optimism bias. Respondents may also be asked to compare their risks to others with their own risks, which reduces prejudice (Otten & van der Pligt, 1996). [Sources: 3, 10, 14]

In other words, the difference between the first rating and the information provided (this is called the rating error) will be greater when participants receive bad news about positive events and when they receive good news about negative events. [Sources: 11]

Hence, it is a valid test of belief renewal using both types of life events. By selectively aligning our expectations with positive events, we can remain optimistic even in the face of negativity. Research shows that regardless of the outcome, whether successful or not, people with high expectations tend to do better. [Sources: 1, 7, 11]

— Slimane Zouggari

##### Sources #####

[0]: https://www.theguardian.com/science/2012/jan/01/tali-sharot-the-optimism-bias-extract

[1]: https://thedecisionlab.com/biases/optimism-bias/

[2]: http://content.time.com/time/health/article/0,8599,2074067,00.html

[3]: https://www.verywellmind.com/what-is-the-optimism-bias-2795031

[4]: https://harappa.education/harappa-diaries/optimism-bias-meaning-and-examples/

[5]: https://www.washingtonpost.com/national/health-science/optimism-bias-why-the-young-and-the-old-tend-to-look-on-the-bright-side/2012/12/28/ac4147de-37f8-11e2-a263-f0ebffed2f15_story.html

[6]: https://www.cnbc.com/2020/10/22/why-optimism-bias-could-be-unhelpful-in-a-pandemic-say-psychologists.html

[7]: https://fs.blog/the-optimism-bias/

[8]: https://www.bbc.com/worklife/article/20210427-how-optimism-bias-shapes-our-decisions-and-futures

[9]: https://www.coglode.com/research/optimism-bias

[10]: https://cancercontrol.cancer.gov/brp/research/constructs/optimistic-bias

[11]: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5380127/

[12]: https://bmcpsychology.biomedcentral.com/articles/10.1186/s40359-020-0389-6

[13]: https://www.behavioraleconomics.com/resources/mini-encyclopedia-of-be/optimism-bias/

[14]: https://www.frontiersin.org/articles/10.3389/fpsyg.2020.02001/full

[15]: https://en.wikipedia.org/wiki/Optimism_bias

Omission prejudice is the belief that the harm caused by inaction is more acceptable than the harm caused by action, even if the result is the same. A study found that parents who did not vaccinate their children were worried that vaccination was more dangerous than not vaccinating, even if the risk of vaccination was lower than the risk of illness. 2 This suggests that supervisory bias may be more likely to lead to acceptance of unreasonable decisions. Instead of correctly weighing the probability of each potential outcome. Omission prejudice is the tendency to place inaction (inaction) above action (action). Inaction prejudice is the tendency of humans to think that harmful behavior is more unethical than inaction, even if both will lead to the same result. [Sources: 0, 7, 12, 14]

Omission bias, cognitive bias, is the tendency to judge public and harmful behavior more strictly than harmful omission. Lack of prejudice describes the tendency of people to put inaction above action, especially when they have to make difficult decisions. The philosopher and ethicist Peter Singer also stated that omission of prejudice also allows us to limit our moral responsibility. If the burden of harmful behavior is heavy, we may be indifferent to the harm caused by our negligence. The prejudice against inaction is the result of our tendency to think that the harmful consequences of action (doing) are worse than the harmful consequences of inaction (inaction). [Sources: 2, 3, 4]

But due to the bias of inaction, people underestimate the possible negative consequences of their inaction. Often people think that harmful results caused by action are worse than equally harmful results caused by inaction. Omission bias stems from the basic view that any direct cause of harm should be avoided, but it is important to note that indirect harm can also be prevented. [Sources: 7]

I hope that these examples of missing bias will open your eyes to this cognitive bias, which can have a negative impact on your thinking and decision-making. The authors investigated the role of this omission bias in parenting decisions to vaccinate children against whooping cough. [Sources: 5, 7]

In some cases, it takes on such a strong form that no action seems to be the best choice, even if it leads to worse consequences. Prejudice is not only manifested when the result of action and inaction is the same. There are often situations where action is actually more harmful than inaction. [Sources: 3, 14]

However, using a choice architecture to design how alternatives are presented can exploit omission-based bias to make better decisions. Omission bias arises for a number of reasons, and there are also plenty of excuses for one situation that seems less harmful than another, but by analyzing the logic it is easy to see why this method of thinking is a cognitive bias. The observed bias towards the status quo is at least in part due to the bias towards omission. All of this suggests that an overlooked way of thinking in a professional environment can impair an organization’s ability to make positive decisions or beneficial changes. [Sources: 7, 11, 12]

However, negligence will result in B (the status quo is about to change), and action is needed to maintain A. However, negligence will result in A, and action needs to be taken to maintain B. vaccine. [Sources: 5, 6]

This decrease in perceived intent for the results of omissions would make the assessment of someone’s behavior less negative. This bias is the opposite effect of action bias, where you feel uncomfortable doing nothing. The only difference is the method in which one causes death by action and the other by inaction. The decision not to act seems like the best moral choice. [Sources: 8, 14]

However, parents choose not to vaccinate their children to avoid possible consequences. Although the difference is small, an action that leads to catastrophic consequences seems more criminal than any action that leads to the same result. Despite this deterioration, at least no one can be blamed for taking action. Although in this case, inaction can lead to death, it creates bogus moral comfort for the brain. [Sources: 4, 14]

As in real life examples, you yourself are a victim of prejudice. SQ-NO, the state of the people did not change and did not take any action; An example of this version is the story of Paul in the scenario described above; CH-ACT, a person’s status has been changed by his own actions; Georges’s script is an example of this version; H-NO, the person’s status was changed without taking an action; Frank’s script is an example of this condition; and SQ-ACT, the person has maintained the status quo through action, as Henry did in the example above. Our Bias Brief series analyzes specific biases one by one, each carefully selected from our long list of ideas. [Sources: 6, 12, 14]

Regardless of the consequences of an action, that is what determines morality. While employees have the opportunity to quit their jobs and start their own businesses, the consequences are daunting. Table 2 Experiment Conditions 2. The current action condition indicates the status quo of the alternative action 1. [Sources: 6, 7, 14]

In one scenario, John, a tennis player, will face a serious opponent in a decisive match the next day. The end result will be the same for all four, but the chain of events leading up to this result will be different. [Sources: 0, 6]

People don’t always know how to assess risks and make rational decisions. To minimize the overall cost of miscarriage of justice, no-loss requires establishing a standard of proof well above 51 percent. [Sources: 1, 10]

— Slimane Zouggari

##### Sources #####

[0]: https://en.wikipedia.org/wiki/Omission_bias

[1]: https://www.wbur.org/hereandnow/2021/12/06/omission-bias-kids-vaccine

[2]: https://www.alleydog.com/glossary/definition.php?term=Omission+Bias

[3]: https://thedecisionlab.com/biases/omission-bias/

[4]: https://www.ceannas.com/omission-bias/

[5]: https://journals.sagepub.com/doi/10.1177/0272989X9401400204

[6]: https://www.sas.upenn.edu/~baron/papers.htm/sq.html

[7]: https://www.developgoodhabits.com/omission-bias/

[8]: https://pubmed.ncbi.nlm.nih.gov/8826794/

[9]: https://www.definitions.net/definition/omission+bias

[10]: https://www.jstor.org/stable/10.1086/664911

[11]: https://link.springer.com/article/10.1007/BF00208786

[12]: https://lirio.com/blog/omission-bias-lirio-bias-brief/

[13]: https://www.npr.org/2021/12/06/1061861586/study-links-abortion-denial-and-poverty-omission-bias-and-vaccines

[14]: https://productiveclub.com/omission-bias/

This means that people’s preference for things is determined by their closer interaction with them. The key element is that simple leverage refers to the fact that people start to like something more for no substantial reason other than that they are familiar with it. The simple exposure effect is also known as the dating principle, as it describes the human tendency to develop preferences for things simply because we know them. This phenomenon is an example of a simple stimulation effect or the principle of familiarity, which explains that the more we are exposed to something, or the more we become familiar with it, the more we like it. [Sources: 0, 1, 6, 11]

In other words, the more open you are to something, the more you enjoy it, simply because it seems more familiar to you. This means that someone may still be more supportive of what they are familiar with, even if they have not been consciously exposed to it. In fact, this person is still a stranger, but the simple phenomena of exposure create a sense of trust, even a potential connection. [Sources: 6, 8]

But it is a psychological phenomenon that still makes people form attachments. Simply put, people love what they are familiar with, be it people, objects, symbols, brands, or apps. [Sources: 7, 8]

Many of the above psychological principles were easy enough to apply to UX, but it’s more like what you’ve probably heard from Chad in the marketing department. [Sources: 7]

Social sociologist Robert Zayonts conducted experiments to observe the effects of repeated exposure of people to certain stimuli. His theory was that even if re-acquaintance happened without your knowledge, you would still develop sympathy. In the early years of his experiments, Zayonts found that people were more likely to develop positive reactions to certain words that they already knew. Zayonts proposed the hypothesis of affective primacy, which showed that living things show sympathy without logical thinking. [Sources: 3, 4]

His 1968 research showed how living things show fear or resistance to something new. With sufficient exposure, fear decreases and attachment to a new object increases. Even if you are neutral, you may develop sympathy after further acquaintance. [Sources: 3]

But if you don’t like something the first time, re-exposure is unlikely to change your impression. You cannot keep your instincts from preferring what you know. Your constant exposure to things forces you to use every opportunity. [Sources: 3]

Overexposure can have a negative effect, especially if the same thing happens repeatedly over a short period of time. Research has shown that too much exposure can limit and therefore diminish our attraction to stimuli. In fact, researchers have found that the effect is stronger when we are unaware of it. Researchers have found that the effect is strong when we are not aware of the stimulus. [Sources: 0, 2, 3, 11]

First, we are less insecure about something when we are familiar with it. We do not need to be consciously aware of what we are being exposed to in order for familiarity with them to influence our preferences. We prefer things that have been exposed in the past, and our preferences increase as we are exposed. [Sources: 2, 11]

A simple psychological definition of impact is when you find yourself more attached to certain things simply because you know them, which is also called the dating principle. The Simple Exposure Effect, also known as the dating principle, describes a phenomenon that makes people appreciate or feel positively about things to which they are frequently and constantly exposed, including other people. A simple impact effect is simply a psychological phenomenon in which people prefer people or things simply because they are familiar with them. [Sources: 6, 9, 12]

For example, if you meet frequently with a colleague, you are more likely to feel attracted to him and respond to him positively. If you can associate a product or service with something or someone with whom you already have a “relationship” and therefore with whom you are “familiar”, then you are more likely to treat the product / service more favorably. [Sources: 4, 5]

Greater distribution leads to familiarity, which leads to convenience, which leads to greater brand preference and increased sales. More widespread adoption leads to familiarity, which leads to convenience, which leads to significant improvements in overall conversion optimization. Most researchers agree that advertising is most effective when a product or brand is new, but when they are familiar with it, increased exposure often does not lead to an increase in preference. For example, studies of the simple effect of exposure show that experience with an object leads to increased liking (preference for acquaintance), but the opposite trend is found in other studies that use withdrawal (preference for acquaintance). Ads). [Sources: 5, 6, 10, 11]

In addition, the results of Experiment 1, according to which only familiar faces were preferred after passive exposure, but not new natural scenes, indicate that passively exposed experiences affect the two types of preferences in different ways. Consequently, tendencies toward a preference for acquaintance will require only passive exposure, while tendencies toward a preference for novelty will require active judgment during exposure. [Sources: 10]

An evolutionary point of view argues that people’s preferences for objects and conditions depend on familiarity. We know that familiar food brings comfort (like familiar food), but the principle of acquaintance extends to other experiences as well. As a vegan, I have noticed that the dating principle has a lot to do with what I eat and what the vegan food genes around the world cook. [Sources: 1, 9]

I also try new things and learn about different types of food in a familiar way, which eventually expands my comfort zone. When it triggers familiar emotions, we are more likely to try new things. We don’t need to know too much about the things we encounter in order to make them familiar. [Sources: 0, 1]

Of course, further familiarity with these subjects will eventually make children remember things, but it all starts with recognition. For example, if a person often encounters the word “create” and becomes more “familiar” with the word, then the person will tend to think that the word is more positive than other similar words such as “create” or “build”. ..”. [Sources: 4]

The results showed no discernible difference in familiarity, but did notice a significant effect on attractiveness. This “country of origin bias” stems from the fact that investors are familiar with the companies. [Sources: 2, 3]

As a consequence of this influence, neuromarketing research on products and consumers opens up new perspectives in the study of proximity and the effect of simple exposure. [Sources: 9]

The Simple Impact Effect, sometimes also referred to as the dating principle, is considered one of the most successful methods of integration into marketing and advertising. This experiment seeks to investigate whether segregation of preference for familiar faces and new natural scenes can form under simple exposure conditions. Our results indicate that a preference for facial recognition is generated regardless of whether processing involves mere display, objective judgment, or judgment of subjective preference. However, the chances are high that the simple effect of stimulation will cause your subconscious mind to rate the runner as “good” or at least “better” than the stranger, simply because you already know his face. [Sources: 4, 10, 12]

— Slimane Zouggari

##### Sources #####

[0]: https://freecourses.net/marketing/mere-exposure-effect/

[1]: https://uxdesign.cc/familiarity-feels-good-8826da719933

[2]: https://thedecisionlab.com/biases/mere-exposure-effect/

[3]: https://productiveclub.com/mere-exposure-effect/

[4]: https://www.brax.io/blog/the-magic-of-the-mere-exposure-effect-or-the-familiarity-principle

[5]: https://martech.org/6-conversion-principles-can-learn-mere-exposure-effect/

[6]: https://www.betterhelp.com/advice/general/what-is-the-mere-exposure-effect/

[7]: https://www.fyresite.com/mere-exposure-effect-the-psychology-of-familiar-ux/

[8]: https://www.scheffey.com/blog/the-psychology-of-marketing-strategy/

[9]: https://www.neuroscience.org.uk/proximity-mere-exposure-effect-social-psychology/

[10]: https://www.frontiersin.org/articles/10.3389/fpsyg.2011.00043/full

[11]: https://www.adcocksolutions.com/post/no-28-mere-exposure-effect

[12]: https://www.joshuakennon.com/mental-model-mere-exposure-effect-or-the-familiarity-principle/

Automatic bias. False priorities. A tendency to over-reliance on automated systems, which can lead to incorrect automated information overriding correct decisions. Bias in attention Bias in accessibility The tendency to perceive repetitive thoughts. Result error. The tendency to judge a decision based on its final outcome rather than the quality of the decision at the time it was made. Projection bias. The tendency to overestimate how much our future self shares our current preferences, thoughts, and values, leading to less-than-optimal choices. [Sources: 10]

Hyperbolic actualization leads to choices that become inconsistent over time: people today make choices that their “I” in the future would prefer not to make, despite the fact that they use the same reasoning. When regret is an unfortunate consequence of making a right decision, or when previous results are unrelated to subsequent choices, blindly changing choices can lead to biased decisions. When faced with a negative outcome from one of your past decisions, you tend to avoid making choices by facing similar challenges, even if the same choices you made in the past are optimal. Having received a negative result for making a decision, we tend to avoid that decision when faced with another problem, even if it was the optimal choice at the time. [Sources: 1, 5, 10, 11]

In addition, by treating someone as expected, that person may inadvertently alter their behavior to match the expectations, thereby providing additional support for the confirmation bias on the part of the perceiver. In interpersonal relationships, confirmatory bias can be problematic as it can lead to inaccurate and distorted impressions of others. Importance Confirmation bias is important because it can cause people to forcibly hold false beliefs or give more weight to information that supports their beliefs than the evidence supports. Supporting evidence bias is strong and widespread, and manifests itself in a wide variety of contexts. [Sources: 4]

The process of making decisions and processing information by people is often biased, because people simply interpret information from their point of view. This biased approach to decision making is largely unintentional and often results in conflicting information being ignored. Conspiracy theories, for example, are often influenced by various prejudices. Even the smartest people are biased in their judgments and choices. [Sources: 4, 11]

To avoid maladaptive bias towards changing choices, you must 1) acknowledge that you may be subject to such bias and 2) ensure that you have the data you need to make an objective choice. While nothing really exists in a vacuum, it is important to envision innovative decision making without reference to the past. Therefore, being able to look back and assess our past choices allows us to change future behavior and, apparently, make better decisions. We and others have previously found that these biases in choice history exhibit several hallmarks of rational and adaptive learning – for example, they are flexible in adapting to environmental stability and are governed by confidence in previous decisions (Urai et al. [Sources: 1, 5, 8]

Taken together, perceptual choice is imbalanced with respect to previous choice, modulation that grows with confidence in previous decisions, and from the direction of previous evidence, modulation that grows with the strength of previous evidence. These results indicate that previous choices and previous incentives can induce bias at certain stages of perceptual decision making. These results indicate a simultaneous bias in repetition of choices modulated by certainty in decisions and in adaptations of evidence modulated by the strength of the evidence that skew current perceptual decisions in opposite directions. Previous research shows that this repetition bias increased after previous decisions with a high degree of confidence, as indicated by response times (Urai, Braun & Donner, 2017), but also when previous decisions were based on weak sensory data ( Akaishi, Umeda, Nagase, Sakai, 2014). [Sources: 3]

These results suggest that characteristic attributes of sensory stimuli may influence selection bias, even if they are not predictive in the task [2AFC-2AUC]. These results demonstrate that gradients of stimulus similarity did not influence the generation of selection bias in our tasks [2AFC-2AUC] in mice and humans. Taken together, these results demonstrate how discriminating stimulus reduces choice bias in the actions of 2AFCs in mice and humans (see also Supplementary Figure S2). Using these adaptations, we found that stimulus similarity increased choice lateral bias in the 2AFC tasks but not in the 2AUC tasks. [Sources: 6]

In addition, by reinforcing lateral preference and alternation, we found that selection biases readily adapt to non-visual manipulation. These results demonstrate that selection bias in our tasks is consistent with recent reward history and that different levels of choice stereotypes can be exacerbated in mice and humans. Thus, selection bias was robust and relatively stable, but it was also adaptable, allowing both mice and humans to update their problem-solving strategies to cope with the specific demands of experimentation. Individuals’ tendencies to repeat or change their choices were recorded by changing their history-dependent drift bias (Figure B). [Sources: 6, 8]

The second study examined the mechanism underlying this bias, and the results supported the hypothesis that this maladaptive change in choice is caused by inhibition of the previous decision (a direct effect of experienced regret), and not by increased sensitivity to regret. subsequent choice (indirect effect of experienced regret mediated by expected regret). Non-adaptive change in choice [75] After experiencing a negative outcome of a decision problem, the tendency to avoid choices made earlier when faced with the same decision problem, even if the choice was optimal. Pseudo-Confidence Effect Prospect Theory The tendency to make non-risk choices when the expected outcome is positive, but to make risk-based choices to avoid negative outcomes. This learning process results in the constant updating of previous expectations from one decision to the next, which then distorts the current choice. [Sources: 5, 8, 10]

We agree that changing bias is usually important, but we also believe that understanding the components of decision-making is important to understanding perceptual decision-making. However, we believe that although control bias is a very important aspect of perceptual research, it is also important to describe selection bias because they are an integral part of perceptual decision-making. As we described in the introduction of the manuscript, we believe that the existence of global selection bias in the perceptual recognition problem has been recognized and incorporated into the current decision-making model, but we have been unable to find evidence to unravel the process of perception and composition. In literature. In addition, since the above analysis focuses on the distortion effects of previous selections, it is not clear that the evidence of previous stimuli affects subsequent visual processing. [Sources: 0, 3]

We then fit a number of more complex models to the data, showing that selection history bias most likely stems from imbalanced inputs (recall selective neural responses to stimuli in the sensory cortex) to the accumulators that drive behavioral choice (Figure C, right). [Sources: 8]

— Slimane Zouggari

##### Sources #####

[0]: https://elifesciences.org/articles/43994

[1]: https://cult.honeypot.io/reads/10-cognitive-biases-stop-inovation/

[2]: https://www.sciencedirect.com/science/article/pii/S2405844021011002

[3]: https://jov.arvojournals.org/article.aspx?articleid=2771979

[4]: https://www.britannica.com/science/confirmation-bias

[5]: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4476096/

[6]: https://www.frontiersin.org/articles/10.3389/fnbeh.2020.00099/full

[7]: http://www.nature.com/scitable/topicpage/neutral-theory-the-null-hypothesis-of-molecular-839

[8]: https://tobiasdonner.net/choice-history-biases-subsequent-evidence-accumulation/

[9]: https://www.healthline.com/health/self-serving-bias

[10]: https://en.wikipedia.org/wiki/List_of_cognitive_biases

[11]: https://theambitiouswriter.substack.com/p/cognitive-biases-and-how-to-outsmart