How many types of bias are there? Do you know?
More than you might guess.
I was surprised to learn that there are hundreds of different types.
This blog post will define the main categories of bias and describe some of the most common types.
Gaining a greater understanding of bias and being able to easily identify different types of bias can help us better explain bias to our audiences, in turn helping them avoid biased thinking and the actions it leads to.
First, what is the definition of bias?
Merriam-Webster dictionary provides this definition:
Bias (noun) is…
a: an inclination of temperament or outlook, especially: a personal and sometimes unreasoned judgment: prejudice
b: an instance of such prejudice
c: bent, tendency
d(1): deviation of the expected value of a statistical estimate from the quantity it estimates
d(2): systematic error introduced into sampling or testing by selecting or encouraging one outcome or answer over others
In essence, personal biases are ways we think about or perceive something that can prejudice our decisions and actions. Biased thoughts and actions can lean in positive or negative directions, making our view of something potentially better or worse than reality.
What are the main categories of bias?
Biases are often placed in one of the following general categories, which overlap:
Conscious or Explicit Bias
These biases are ones of which you are aware. They are prejudices that when acted upon may lead to discrimination.
Unconscious or Implicit Bias
These biases are ones of which you are unaware. They occur when we unconsciously attribute characteristics or stereotypes to members of a group of people.
Cognitive Bias
These biases are systematic errors in thinking that occur when we misinterpret information. These are most common when mental shortcuts are taken in forming thoughts, opinions, and making decisions. Considering our limited attention spans and the need to often make quick decisions, cognitive biases are common.
Research or Statistical Bias
These biases occur when conducting research and are often seen in biased sampling or data collection. Research biases can result in inaccurate and misleading research outcomes and the reporting of results. Research protocols and best practices such as random sampling and peer review are designed to prevent bias.
What are examples of common types of bias?
The 10 examples below are ones you have likely encountered but may not know the label used.
Actor-Observer Bias
Attributing our behaviors to external or outside influences versus attributing the actions of others to personal or internal influences. For example, I ate “too much” at Thanksgiving because Aunt Betty kept filling my plate, whereas Uncle Jack ate “too much” at Thanksgiving because he lacks willpower. This type of bias can lead to inappropriate “blaming and shaming.”
Affinity Bias
Preferring people who are most like us. This can include having similarities such as race, nationality, age, gender, occupation, etc. This type of bias can result in discriminatory hiring practices and can be explicit or implicit. Purposefully overcoming this type of bias promotes diversity.
Anchoring Bias
Basing an opinion or decision most heavily on an initial impression or the first piece of information received. First impressions are powerful. Remaining open to collecting more information helps to alleviate anchoring bias.
Availability Heuristic
Estimating the likelihood of something occurring based on the number of examples one can think of. For example, if you have known many people with cancer, you will perceive the risk of cancer higher than if you are not familiar with anyone with cancer. This cognitive bias can lead to underestimating or overestimating risk. Seek evidence beyond personal experience.
Confirmation Bias
Paying more attention to information that confirms our values and beliefs. This bias can be aggravated by social media algorithms putting more of the types of information we gravitate towards in our feeds. To counter this type of bias requires an openness to seek out and consider all sides of an issue.
Halo/Horn Effect
Expanding an initial impression of someone to our overall opinion of them. For example, thinking a person we find attractive to be intelligent and confident as well without further evidence to support or deny that thought. Conversely, a negative first impression based on a single characteristic can lead to thinking less favorably about someone’s traits in other areas.
Hawthorne Effect
Modifying one’s behaviors in response to being observed as in participating in an experiment or intervention. This bias is important to keep in mind when working with study participants or patients.
Misinformation Effect
Recalling a memory incorrectly based on various influencing factors after the event took place. These factors can include media coverage of an event, other people’s perspectives about the event, and even how one is questioned about their memory of the event.
Observer/Experimenter Bias
Favoring research results that confirm the researcher’s preconceptions or hypotheses. Avoid this bias by objectively recognizing outcomes contrary to expectations.
Publication Bias
Reporting research results that are positive or that support the researcher’s hypothesis differently and in a better light than results that are negative or inconclusive. This leads to bias in the published literature on a topic.
How can we become more aware of biases and overcome them?
Previous blogs have shared how you can become more aware of your own biases and 5 tips for overcoming bias. Check them out. Put them into practice.
"Human beings are poor examiners, subject to superstition, bias, prejudice, and a PROFOUND tendency to see what they want to see rather than what is really there." ~ M. Scott Peck
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