Where is bias found

But all people harbor beliefs and attitudes about groups of people based on their race or ethnicity, gender, body weight and other traits. Those beliefs and attitudes about social groups are known as biases. Biases are beliefs that are not founded by known facts about someone or about a particular group of individuals.

For example, one common bias is that women are weak despite many being very strong. Another is that obese people are lazy when their weight may be due to any of a range of factors, including disease. People often are not aware of their biases. And such implicit biases influence our decisions whether or not we mean for them to do so. Rather, biases develop partly as our brains try to make sense of the world. Our brains process 11 million bits of information every second.

A bit is a measure of information. The term is typically used for computers. But we can only consciously process 16 to 40 bits.

In other words, the vast majority of the work that our brains do is unconscious. For example, when a person notices a car stopping at a crosswalk, that person probably notices the car but is not consciously aware of the wind blowing, birds singing or other things happening nearby.

To help us quickly crunch through all that information, our brains look for shortcuts. One way to do this is to sort things into categories. A dog might be categorized as an animal. But it also can allow unfair biases to take root.

Those messages can be direct, such as when someone makes a sexist or racist comment during a family dinner. Or they can be indirect — stereotypes that we pick up from watching TV, movies or other media.

Our own experiences will add to our biases. The good news is that people can learn to recognize their implicit biases by taking a simple online test. Later, there are steps people can take to overcome their biases. Hillard is a psychologist at Adrian College in Michigan. And it takes only minor cues for our minds to call up, or activate , cultural stereotypes about those groups. This is true even in people who say they believe all people are equal.

Many people are not aware that stereotypes can spring to mind automatically, Hillard explains. Those efforts usually backfire. Instead of treating people more equally, people fall back even more strongly onto their implicit biases.

Race is one big area in which people may exhibit bias. Some people are explicitly biased against black people. That means they are knowingly racist. One study, for example, found that when Black and White job seekers sent out similar resumes to employers, Black applicants were half as likely to be called in for interviews as White job seekers with equal qualifications.

Even when employers strive to eliminate potential bias in hiring, subtle implicit biases may still have an impact on how people are selected for jobs or promoted to advanced positions. Certainly, age, race, or health condition should not play a role in how patients get treated, however, implicit bias can influence quality healthcare and have long-term impacts including suboptimal care, adverse outcomes, and even death.

For example, one study published in the American Journal of Public Health found that physicians with high scores in implicit bias tended to dominate conversations with Black patients and, as a result, the Black patients had less confidence and trust in the provider and rated the quality of their care lower.

Researchers continue to investigate implicit bias in relation to other ethnic groups as well as specific health conditions, including type 2 diabetes, obesity, mental health, and substance use disorders. Implicit biases can also have troubling implications in legal proceedings, influencing everything from initial police contact all the way through sentencing.

Research has found that there is an overwhelming racial disparity in how Black defendants are treated in criminal sentencing. Not only are Black defendants less likely to be offered plea bargains than White defendants charged with similar crimes, but they are also more likely to receive longer and harsher sentences than White defendants.

Implicit biases impact behavior, but there are things that you can do to reduce your own bias:. Implicit biases can be troubling, but they are also a pervasive part of life. Perhaps more troubling, your unconscious attitudes may not necessarily align with your declared beliefs. While people are more likely to hold implicit biases that favor their own in-group, it is not uncommon for people to hold biases against their own social group as well. The good news is that these implicit biases are not set in stone.

Even if you do hold unconscious biases against other groups of people, it is possible to adopt new attitudes, even on the unconscious level. Learn the best ways to manage stress and negativity in your life. Jost JT. The existence of implicit bias is beyond reasonable doubt: A refutation of ideological and methodological objections and executive summary of ten studies that no manager should ignore.

Research in Organizational Behavior. Measuring individual differences in implicit cognition: The implicit association test. J Pers Soc Psychol. Physicians' implicit and explicit attitudes about race by MD race, ethnicity, and gender. J Health Care Poor Underserved. Implicit racial bias in medical school admissions. Acad Med. Kiefer AK, Sekaquaptewa D. Implicit stereotypes and women's math performance: How implicit gender-math stereotypes influence women's susceptibility to stereotype threat.

Journal of Experimental Social Psychology. On the leaky math pipeline: Comparing implicit math-gender stereotypes and math withdrawal in female and male children and adolescents. Journal of Educational Psychology. Silvia Chiappa of DeepMind has even developed a path-specific approach to counterfactual fairness that can handle complicated cases where some paths by which the sensitive traits affect outcomes is considered fair, while other influences are considered unfair.

These improvements will help, but other challenges require more than technical solutions, including how to determine when a system is fair enough to be released, and in which situations fully automated decision making should be permissible at all.

These questions require multi-disciplinary perspectives, including from ethicists, social scientists, and other humanities thinkers. Among others, we see six essential steps:. First, business leaders will need to stay up to-date on this fast-moving field of research. Tech companies are providing some help here. Now, with more advanced tools to probe for bias in machines, we can raise the standards to which we hold humans.

Importantly, when we do find bias, it is not enough to change an algorithm—business leaders should also improve the human-driven processes underlying it. Fourth, consider how humans and machines can work together to mitigate bias. More will be needed. This will require investments in education and opportunities — work like that of AI4ALL , a nonprofit focused on developing a diverse and inclusive pipeline of AI talent in under-represented communities through education and mentorship.

But that will only be possible if people trust these systems to produce unbiased results. AI can help humans with bias — but only if humans are working together to tackle bias in AI. Example: images are powerful. Look at how the image portrays the subject. Example: word choice. The type of language used can influence how people react to the information. Example: information portrayed in a frame or story format. Usually framed around a conflict.

Example: information is fast paced. Sometimes the information is reported before all the facts are available and checked. Example: information not included or incomplete. While it's not possible to cover every detail, there shouldn't be gaps in the information. This type of bias can be difficult to identify unless you read a variety of sources across an issue.

For instance, if the information presented is extremely or solely one-sided, that may be an indication of omission. Other Keywords There are some keywords you should keep in mind when you're evaluating for bias: Agenda , n. Report a problem. Subjects: News , Research process.