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Present bias shows up not just in experiments, of course, but in the real world. Especially in the United States, people egregiously undersave for retirement—even when they make enough money to not spend their whole paycheck on expenses, and even when they work for a company that will kick in additional funds to retirement plans when they contribute.

hen people hear the word bias, many if not most will think of either racial prejudice or news organizations that slant their coverage to favor one political position over another. Present bias, by contrast, is an example of cognitive bias—the collection of faulty ways of thinking that is apparently hardwired into the human brain. The collection is large. Wikipedia’s “List of cognitive biases” contains 185 entries, from actor-observer bias (“the tendency for explanations of other individuals’ behaviors to overemphasize the influence of their personality and underemphasize the influence of their situation … and for explanations of one’s own behaviors to do the opposite”) to the Zeigarnik effect (“uncompleted or interrupted tasks are remembered better than completed ones”)

If I had to single out a particular bias as the most pervasive and damaging, it would probably be confirmation bias. That’s the effect that leads us to look for evidence confirming what we already think or suspect, to view facts and ideas we encounter as further confirmation, and to discount or ignore any piece of evidence that seems to support an alternate view

Human decision-making shows systematic simplifications and deviations from the tenets of rationality (‘heuristics’) that may lead to suboptimal decisional outcomes (‘cognitive biases’). There are currently three prevailing theoretical perspectives on the origin of heuristics and cognitive biases: a cognitive-psychological, an ecological and an evolutionary perspective. However, these perspectives are mainly descriptive and none of them provides an overall explanatory framework for

the underlying mechanisms of cognitive biases. To enhance our understanding of cognitive heuristics and biases we propose a neural network framework for cognitive biases, which explains why our brain systematically tends to default to heuristic (‘Type 1’) decision making. We argue that many cognitive biases arise from intrinsic brain mechanisms that are fundamental for the working of biological neural networks. To substantiate our viewpoint, we discern and explain four basic neural network principles: (1) Association, (2) Compatibility, (3) Retainment, and (4) Focus. These principles are inherent to (all) neural networks which were originally optimized to perform concrete biological, perceptual, and motor functions. They form the basis for our inclinations to associate and combine (unrelated) information, to prioritize information that is compatible with our present state (such as knowledge, opinions, and expectations), to retain given information that sometimes could better be ignored, and to focus on dominant information while ignoring relevant information that is not directly activated. The supposed mechanisms are complementary and not mutually exclusive. For different cognitive biases they may all contribute in varying degrees to distortion of information. The present viewpoint not only complements the earlier three viewpoints, but also provides a unifying and binding framework for many cognitive bias phenomena.

The cognitive-psychological (or heuristics and biases) perspective (Evans, 2008; Kahneman and Klein, 2009) attributes cognitive biases to limitations in the available data and in the human information processing capacity (Simon, 1955; Broadbent, 1958; Kahneman, 1973, 2003; Norman and Bobrow, 1975)

Cognitive biases contribute significantly to diagnostic and treatment errors

A 2016 review of their roles in decision making lists 4 domains of concern for physicians: gathering and interpreting evidence, taking action, and evaluating decisions

Confirmation bias is the selective gathering and interpretation of evidence consistent with current beliefs and the neglect of evidence that contradicts them.

there’s plenty of evidence to suggest that we’re all at least somewhat subject to bias

Tell Republicans that some imaginary policy is a Republican one, as the psychologist Geoffrey Cohen did in 2003, and they’re much more likely to support it, even if it runs counter to Republican values. But ask them why they support it, and they’ll deny that party affiliation played a role. (Cohen found something similar for Democrats.

those who saw the names were biased in favour of famous artists. But even though they acknowledged the risk of bias, when asked to assess their own objectivity, they didn’t view their judgments as any more biased as a result.

The university-led collaborative administers web-based tests that purport to reveal whether a person is unknowingly biased about a wide range of issues.

Much has been written on the effects of implicit bias and how the often-unconscious attitudes and beliefs that nearly all of us hold foster our comprehension of race, gender, class, ethnicity, and a host of other social constructs

With all this angst rattling in my head, I took the test. It began innocently enough, with a series of questions that allowed me to state whether I had any known biases toward skin tones. I answered as honestly as possible but feared my conscious choices tilted toward skin tones similar to my own chocolate-colored skin.

A cognitive bias is a systematic pattern of deviation from rationality, which occurs due to the way our cognitive system works. Accordingly, cognitive biases cause us to be irrational in the way we search for, evaluate, interpret, judge, use, and remember information, as well as in the way we make decisions.

Cognitive biases affect every area of our life, from how we form our memories, to how we shape our beliefs, and to how we form relationships with other people. In doing so, they can lead to both relatively minor issues, such as forgetting a small detail from a past event, as well as to major ones, such as choosing to avoid an important medical treatment that could save our life.Because cognitive biases can have such a powerful and pervasive influence on ourselves and on others, it’s important to understand them. As such, in the following article you will learn more about cognitive biases, understand why we experience them, see what types of them exist, and find out what you can do in order to mitigate them successfully.

By treating them as the same, we miss nuances that are important for understanding human decision-making.

Biases—regardless of whether they are hardwired into us due to evolution, learned through socialization or direct experience—or a function of genetically influenced traits, represent predispositions to favor a given conclusion over other conclusions. Therefore, Biases might be considered the leanings, priorities, and inclinations that influence our decisions[2].

Heuristics are mental shortcuts that allow us to make decisions more quickly, frugally, and/or accurately than if we considered additional information. They are derived from experience and formal learning and are open to continuous updates based on new experiences and information. Therefore, heuristics represent the strategies we employ to filter and attend to information[3].

Political biases are omnipresent, but what we don’t fully understand yet is how they come about in the first place.

In 2014, Michele J. Gelfand, a professor of psychology at the Stanford Graduate School of Business formerly at the University of Maryland, and Jesse R. Harrington, then a Ph.D. candidate, conducted a study designed to rank the 50 states on a scale of “tightness” and “looseness.”

titled “Tightness-Looseness Across the 50 United States,” the study calculated a catalog of measures for each state, including the incidence of natural disasters, disease prevalence, residents’ levels of openness and conscientiousness, drug and alcohol use, homelessness and incarceration rates.

It’s likely that some researchers are consciously cherry-picking data to get their work published. And some of the problems surely lie with journal publication policies. But the problems of false findings often begin with researchers unwittingly fooling themselves: they fall prey to cognitive biases, common modes of thinking that lure us toward wrong but convenient or attractive conclusions.

Peer review seems to be a more fallible instrument—especially in areas such as medicine and psychology—than is often appreciated, as the emerging “crisis of replicability” attests.

Psychologists have shown that “most of our reasoning is in fact rationalization,” he says. In other words, we have already made the decision about what to do or to think, and our “explanation” of our reasoning is really a justification for doing what we wanted to do—or to believe—anyway. Science is of course meant to be more objective and skeptical than everyday thought—but how much is it, really?

Now scientists have found a more noble purpose for the technique in a study that suggests deep-rooted biases about race and gender could be “unlearnt” during a short nap. The findings appear to confirm the idea that sleeping provides a unique window for accessing and altering fundamental beliefs – even prejudices that we don’t know we have.

Simply playing auditory cues while people slept partially undid racial and gender bias, the study found, and the effects were still evident at least a week later.

“These biases are well-learned,” said Hu. “They can operate efficiently even when we have the good intention to avoid such biases. Moreover, we are often not aware of their influences on our behaviour.”

ognitive bias is an umbrella term that refers to the systematic ways in which the context and framing of information influence individuals’ judgment and decision-making. There are many kinds of cognitive biases that influence individuals differently, but their common characteristic is that—in step with human individuality—they lead to judgment and decision-making that deviates from rational objectivity.

In some cases, cognitive biases make our thinking and decision-making faster and more efficient. The reason is that we do not stop to consider all available information, as our thoughts proceed down some channels instead of others. In other cases, however, cognitive biases can lead to errors for exactly the same reason. An example is confirmation bias, where we tend to favor information that reinforces or confirms our pre-existing beliefs. For instance, if we believe that planes are dangerous, a handful of stories about plane crashes tend to be more memorable than millions of stories about safe, successful flights. Thus, the prospect of air travel equates to an avoidable risk of doom for a person inclined to think in this way, regardless of how much time has passed without news of an air catastrophe.

In an era when everyone seems eager to point out instances of “fake news,” it is easy to forget that knowing how we make sense of the news is as important as knowing how to spot incorrect or biased content

While the ability to analyze the credibility of a source and the veracity of its content remains an essential and often-discussed aspect of news literacy, it is equally important to understand how we as news consumers engage with and react to the information we find online, in our feeds, and on our apps

People process information they receive from the news in the same way they process all information around them — in the shortest, quickest way possible

To better understand the roots of racial division in America, think about this:The human brain seems to be wired so that it categorizes people by race in the first one-fifth of a second after seeing a face. Brain scans show that even when people are told to sort people by gender, the brain still groups people by race.

Racial bias also begins astonishingly early: Even infants often show a preference for their own racial group. In one study, 3-month-old white infants were shown photos of faces of white adults and black adults; they preferred the faces of whites. For 3-month-old black infants living in Africa, it was the reverse.

Scholars suggest that in evolutionary times we became hard-wired to make instantaneous judgments about whether someone is in our “in group” or not — because that could be lifesaving. A child who didn’t prefer his or her own group might have been at risk of being clubbed to death.

Before Kahneman and Tversky, people who thought about social problems and human behavior tended to assume that we are mostly rational agents. They assumed that people have control over the most important parts of their own thinking. They assumed that people are basically sensible utility-maximizers and that when they depart from reason it’s because some passion like fear or love has distorted their judgment.

Kahneman and Tversky conducted experiments. They proved that actual human behavior often deviates from the old models and that the flaws are not just in the passions but in the machinery of cognition. They demonstrated that people rely on unconscious biases and rules of thumb to navigate the world, for good and ill. Many of these biases have become famous: priming, framing, loss-aversion.

We are dual process thinkers. We have two interrelated systems running in our heads. One is slow, deliberate and arduous (our conscious reasoning). The other is fast, associative, automatic and supple (our unconscious pattern recognition). There is now a complex debate over the relative strengths and weaknesses of these two systems. In popular terms, think of it as the debate between “Moneyball” (look at the data) and “Blink” (go with your intuition).

In 2013, five years after he co-authored a paper showing that Democratic candidates in the United States could get more votes by moving slightly to the right on economic policy1, Andrew Gelman, a statistician at Columbia University in New York City, was chagrined to learn of an error in the data analysis. In trying to replicate the work, an undergraduate student named Yang Yang Hu had discovered that Gelman had got the sign wrong on one of the variables.

Gelman immediately published a three-sentence correction, declaring that everything in the paper's crucial section should be considered wrong until proved otherwise.

Reflecting today on how it happened, Gelman traces his error back to the natural fallibility of the human brain: “The results seemed perfectly reasonable,” he says. “Lots of times with these kinds of coding errors you get results that are just ridiculous. So you know something's got to be wrong and you go back and search until you find the problem. If nothing seems wrong, it's easier to miss it.”

Predictive statistical analysis, harnessed to big data, appears poised to alter the way millions of people are hired and assessed.

By one estimate, more than 98 percent of the world’s information is now stored digitally, and the volume of that data has quadrupled since 2007.

The application of predictive analytics to people’s careers—an emerging field sometimes called “people analytics”—is enormously challenging, not to mention ethically fraught

We think of computers as emotionless automatons and artificial intelligence as stoic, zen-like programs, mirroring Mr. Spock, devoid of prejudice and unable to be swayed by emotion.

They say that AI picks up our innate biases about sex and race, even when we ourselves may be unaware of them. The results of this study were published in the journal Science.

After interacting with certain users, she began spouting racist remarks.

The virtual hand illusion (VHI) paradigm demonstrates that people tend to perceive agency and bodily ownership for a virtual hand that moves in synchrony with their own movements. Given that this kind of effect can be taken to reflect self–other integration (i.e., the integration of some external, novel event into the representation of oneself), and given that self–other integration has been previously shown to be affected by metacontrol states (biases of information processing towards persistence/selectivity or flexibility/integration), we tested whether the VHI varies in size depending on the metacontrol bias. Persistence and flexibility biases were induced by having participants carry out a convergent thinking (Remote Associates) task or divergent-thinking (Alternate Uses) task, respectively, while experiencing a virtual hand moving synchronously or asynchronously with their real hand. Synchrony-induced agency and ownership effects were more pronounced in the context of divergent thinking than in the context of convergent thinking, suggesting that a metacontrol bias towards flexibility promotes self–other integration.

As in previous studies, participants were more likely to experience subjective agency and ownership for a virtual hand if it moved in synchrony with their own, real hand. As predicted, the size of this effect was significantly moderated by the type of creativity task in the context of which the illusion was induced.

It is important to keep in mind the fact that our present findings were obtained in a paradigm that strongly interleaved what we considered the task prime (i.e., the particular creativity task) and the induction of the VHI—the process we aimed to prime. The practical reason to do so was to increase the probability that the metacontrol state that the creativity tasks were hypothesized to induce or establish would be sufficiently close in time to the synchrony manipulation to have an impact on the thereby induced changes in self-perception. However, this implies that we are unable to disentangle the effects of the task prime proper and the effects of possible interactions between this task prime and the synchrony manipulation. There are indeed reasons to assume that such interactions are not unlikely to have occurred

One major problem is that stopping the virus from spreading requires us to override our basic intuitions.

Three cognitive biases make it hard for us to avoid actions that put us in great collective danger.

1. Misleading Feedback