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Discuss with reference to psychological theories and applied research.
Social psychologists describe attitudes toward an item or an individual as an evaluative disposition. This can be on an unconscious level, implicit, or a conscious level, explicit. Bias works on the same manifestation. When individuals are unaware of their bias, this is implicit. Whereas, bias on an explicit level can be seen considerably more often in the expression of a person’s likes and dislikes (Greenwald & Krieger, 2006). Heuristics, the ‘rule of thumb’ to quick decision making, play a large role in bias decisions. Heuristics will cause a person to make a rapid decision that the individual will often think is based on logic rather than a pre-existing unconscious bias (Making better decisions, n.d).
Bias attitudes and stereotypes can be measured via a test of association. Quite often correlations are used between concepts and evaluations of a subject or object (Project Implicit, 2011). The most commonly used measure for implicit bias is the Implicit Associations Test, IAT. The IAT is how the strength between the concept and evaluation is measured. This works by testing how strong the mental link is between the two. The key to this test is rapid speed, it works by pairing two items together such as ‘white people’ and ‘bad’ on one side of the screen and the opposing opposites on the other side. During the test, positive and negative emotion words and monochromatic photos of ‘white’ and ‘black’ faces appear on the screen. The participant must sort the words and photos to the matching side of the screen using two pre-set keys of the keyboard (Ratliff & Smith, 2015). The speed of the responses is measured and this is how the biases are determined. The tests show how strong a bias is on a scale of slight to strong and also includes no preference. As with any test for psychological issues, there are some limitations to the IAT. The main limitation of the IAT is due to the speed at which the participant must respond to the stimuli. Participants who may make lots of mistakes will have an inconclusive result. The test may show that there is a bias towards a certain group or object, however, the results will also explain that the number of faults can make the test less valid and reliable. This is important to note as a person may be upset by their result, this can be damaging to the participant even if it is explained that the test isn’t providing a completely reliable result for them. The accuracy of the test is questioned as participants when tested again will often not produce the same results, reasons for this can include basic order effects, as participants will get better at the task as they practice or worse as they get bored and tired. Following on from this the IAT can be said to have low internal reliability as in most cases the same participant will not get identical results on IAT’s regarding the same biases. Some participants also report confusion, which slows their reaction time when the IAT adds in more factors or when the factors themselves switch to the opposite side of the screen. On the flipside, the weaknesses of the Implicit Associations Test also double up as the strengths. The speed of the response is not only a weakness but is said to be a strength because it allows us to gain insight into a participant’s unconscious thoughts. This is important as the test is set to measure implicit bias rather than explicit.
In the Justice System, biases often make for unfair judgements and sentencing in the jurisdiction. Studies have shown that even police officers that have no overtly racist intentions can act upon an unconscious bias. Especially towards black criminals and black individuals in general (Salmanowitz, 2018). This is a highly negative impact of bias decision making as it can cause an endangerment of life to innocent people or people who pose no true threat to society or the police. During police altercations, fifty-seven per cent of unarmed black women were fatally shot by police over a twenty-month period between May 2013 and January 2015. This is a staggering increase on the amount of unarmed white males who were shot fatally just twenty per cent of the time. (Johnson, Gilbert & Ibrahim, 2017 as cited by Everding-Wustl, 2018). Sommers and Ellsworth (2000) found that black drivers are stopped and searched by police more frequently and also treated more harshly as a result of resisting arrest. Biases also appear to be ‘ironed out’ when attention is brought to the bias as this research also found that when race is not specifically made an important factor of a case then black defendants would receive a harsher sentence than white defendants. Thus, suggesting that bias can be due to not only pre-acquired biases but they can also be mitigated when social desirability factors appear, such as the fear of being racist.
Biases can influence decision making by introducing another factor into the decision. These factors are not fully to do with the decision, rather they are based on an individual’s own personal take on the decision at hand. This is all subconscious to the person themselves. Different types of biases can introduce distinctive factors into decision making. For example, confirmation bias introduces the factor of looking for specific information that confirms what an individual already thinks that they know. Thus, confirming that the correct decision is being made, even if this decision is made based on biased information. Other types of bias that produce biased in decision making include; anchoring, over-reliance on one piece of information; the halo effect, the use of impressions particularly in relation to appearance; and overconfidence bias, when an individual overestimates their own judgement. (“Barriers to Decision Making | Boundless Management”, 2018)
Theory supports that being aware of your own bias can mitigate the use of biases in decision making. De Bono (1985/2016) suggested the ‘Six Thinking Hats’ strategy to overcome conformational bias. The ‘Six Thinking Hat’ tool suggests that you mentally represent ‘Hats’ that symbolise certain aspects of decision making. De Bono (1985/2016) represented the ability to look at all available data and the influence of it, as a ‘white hat’. Other ‘hats’ included aspects such as thinking about the negative outcome of a decision, ‘black’ and ‘red’ for using your gut instinct. It was suggested that once an individual had represented all six ‘hats’ they have the ability and information to make an unbiased decision (De Bono, 1985/2016, as cited by Manktelow et al 2018). However, saying this assumes that an individual is willing to make an unbiased decision and does not rely on other biases such as anchoring. Personally, I believe that by forcing others to think about their biases through conversation and challenging their views you can help to change their biases. Research suggests that this can partially be the case. Entrepreneurs when forced to make tough decisions are occasionally asked to consider questions such as ‘what information do they rely on when producing a difficult decision?’ They also consider if they are working from facts or a hunch. This is suggested to be helpful in overcoming overconfidence bias (Manktelow et al, 2018) as entrepreneurs display higher levels of overconfidence bias than the average person (Simon, Houghton & Aquino, 2000). It could also be argued that social desirability plays a role in decision making. Sommers and Ellsworth (2000) saw evidence that racially biased decisions were mitigated when the race issue was brought to the decision makers attention. I believe this trend is shown because of the social desirability to not appear to be racist. As defendants with similar backgrounds would be given harsher jail sentences, if they were black and race was not made a specifically important factor of the case.
To conclude, it appears entirely possible to mitigate bias in decision making. Research suggests that the most effective way to do this is to simply think about every aspect of the decision at hand, such as using De Bono’s (1985/2016) ‘Six Thinking Hat’ strategy to view each possible outcome and every aspect of the information needed to make a clear decision. Sommers and Ellsworth (2000) also demonstrated that after being made aware of the bias, the effects were vastly reduced. However, it is not clear whether or not the bias itself is no longer present or whether the decision has just been made without a biased view attached to it. The developed test for implicit bias, IAT, could also use some improvement as its limitations call into question its reliability to produce an accurate result and allow someone to know their implicit biases. Overall, I personally believe that it is possible to overcome biases once aware of them, however, it takes a vast amount of time, effort and knowledge of the bias to do so. Also, some biases may be too hard to overcome for an individual as the bias may have been born out of a previous and terrible experience.
- Barriers to Decision Making | Boundless Management. (2018). Retrieved from https://courses.lumenlearning.com/boundless-management/chapter/barriers-to-decision-making/
- De Bono, E. (2016). Six thinking hats. London: Penguin UK. “Original work Published, 1985)
- Everding-WUSTL, G. (2018). 60% of black women killed by police were unarmed – Futurity. Retrieved from https://www.futurity.org/police-killings-unarmed-black-women-1675912-2/
- Greenwald, A., & Krieger, L. (2006). Implicit Bias: Scientific Foundations. California Law Review, 94(4), 945. doi: 10.2307/20439056
- Johnson, O., Gilbert, K., & Ibrahim, H. (2017) Race, Gender, And the Contexts of Unarmed Fatal Interactions with Police.
- Making better decisions. Retrieved from https://www1.bps.org.uk/system/files/Public%20files/Comms-media/Making%20better%20decisions.pdf
- Manktelow, J., Jackson, K., Swift, C., Edwards, S., Bishop, L., Pearcey, E., Mugridge, T., Bell, S., Robinson, R., Bruce, E. (2018). Avoiding Psychological Bias in Decision Making How to Make Objective Decisions. Retrieved from https://www.mindtools.com/pages/article/avoiding-psychological-bias.htm
- Project Implicit. (2011). Project Implicit. Retrieved from https://implicit.harvard.edu/implicit/faqs.html
- RATLIFF, K., & SMITH, C. (2015). Measuring the implicit biases we may not even be aware of. Retrieved from http://news.ufl.edu/articles/2017/10/measuring-the-implicit-biases-we-may-not-even-be-aware-of.php
- Salmanowitz, N. (2018). The impact of virtual reality on implicit racial bias and mock legal decisions. Journal of Law And The Biosciences, 5(1), 174-203. doi: 10.1093/jlb/lsy005
- Simon, M., Houghton, S., & Aquino, K. (2000). Cognitive biases, risk perception, and venture formation. Journal Of Business Venturing, 15(2), 113-134. doi: 10.1016/s0883-9026(98)00003-2
- Sommers, S., & Ellsworth, P. (2000). Race in the Courtroom: Perceptions of Guilt and Dispositional Attributions. Personality And Social Psychology Bulletin, 26(11), 1367-1379. doi: 10.1177/0146167200263005
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