“Age” IAT
I chose the “Age” IAT test to find out if I have any hidden biases toward age. Even though I believe that I am not biased when it comes to age, I know that everyone has implicit biases that are influenced by different factors. Although I want to do well on the test, I understand that my results will give me important information about how I feel about “Age”, even if I don’t realize it. By understanding my biases, I can try to reduce their impact and have more inclusive attitudes toward people of all ages.
My outcome of the “Age” IAT test showed a preference for young people over old people, which may reflect the hidden biases I have. I believe that these biases are often automatic and shaped by culture, stereotypes, and experiences. In my opinion, the result of my outcome is based on the speed with which I categorized the images and words related to youth and age. The results showed that I was able to associate positive words with young people and negative words with older people. Before I took the test, I felt like I didn’t have any bias toward younger and older people, so these results shocked me a little bit because I believe that these biases can cause harm and lead to discrimination in aspects like work, health, care, and education. Also, ageism affects all ages, not just old people. Young people can also be hurt by stereotypes that they’re inexperienced or unqualified. Lastly, the test helped me learn about my hidden biases and made me more aware of them, which will help me focus on them later on in life.
“Transgender” IAT
I want to learn more about the hidden biases I may have about transgender people by taking the “Transgender” test. I believe that I will do poorly on the test, so if that is the case, I will be able to face my own biases, become more aware of them, and accept them by identifying my areas of improvement. My goal is to become a better helper to the transgender community and to be more accepting.
My outcome of the “Transgender” IAT test showed that there is no automatic preference between transgender people and cisgender people. This means that there is no significant or consistent bias towards either group. In my opinion, the result of my outcome is based on the inconsistency of associating transgender or cisgender individuals with positive or negative attributes. I believe that this is due to a variety of factors, such as exposure to diverse individuals and experiences. Before I took the test, I felt like I am biased toward transgender people and I still am, accordingly, I am a little bit confused that the results showed the opposite. To an extent, I feel relieved that I am not biased toward a specific group; however, deep inside I know that I am biased toward transgenders, so it’s a little bit complicated. Overall, I believe that people should think about their feelings towards others and make an effort to decrease their bias and encourage inclusiveness.
Validity/Credibility of IAT
The IAT is intended to measure the unconscious or implicit biases of individuals towards certain groups or concepts, but some psychologists argue that it may not be a reliable indicator of an individual’s biases. According to a research article published in the journal Perspectives on Psychological Science, there is evidence to suggest that the IAT has limited predictive validity and may not be a reliable measure of implicit biases. The authors argue that the IAT may be influenced by factors such as participants’ motivation, familiarity with the task, and the influence of prior beliefs or stereotypes. However, it should be noted that other psychologists have defended the validity and usefulness of the IAT as a tool for assessing implicit biases. In a recent meta-analysis of 492 studies that used the IAT, the authors concluded that the IAT provides a reliable measure of implicit biases. The authors also noted that the IAT’s predictive validity was comparable to other measures of implicit biases, such as self-report measures. Finally, this remains a topic of ongoing debate and research within the field of psychology.
Sources:
https://journals.sagepub.com/doi/full/10.1177/1745691619872986
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