With the continued rise of AI, the issue of ethics in regards to equality and diversity is a very important one to consider. Are all people treated equally, or is there such a thing as inequality and racism when it comes to AI and its industry?
Tech companies are reluctant to acknowledge this reality, but yes, there have been many instances of bias within the AI industry and the AI itself. An example of such bias is the fact that the makers of AI are predominantly white and the number of women involved is significantly small, as explained by Dr. Timnit Gebru, an AI expert who used to work at Google (Metz, 2021).
Other examples of bias, this time with the AI itself as perpetrator are:
1.A 2019 study by researchers from Georgia Tech found that the algorithm used to detect human figures was more likely to fail to detect people with darker skin.
2.Racial bias in an algorithm used to predict risk levels and needs in the US healthcare system. As a result, Black patients’ healthcare needs were consistently minimized in comparison to healthier white patients.
3.In 2020, Twitter users began noticing that large images which portrayed people of different races would crop out darker-skinned people and focus on lighter-skinned people.
4.Beauty AI was the first beauty contest to be judged by AI. In 2016 there were 60,000 applications from over 100 countries, and entrants weren’t allowed to have makeup, glasses or a beard. Robot judges were using parameters like wrinkles, face symmetry, skin color, gender, age group and ethnicity to determine winners. Although 11% of the entrants were black, none of the 45 winners were black. Thoughts are this was because of the algorithms used to perform the analysis.
5.The autosuggestions feature in Google Search was listing some less than desirable results when entering ‘Why are Nigerians so…’. Algorithms have since been updated to actively remove negative results, or enable users to limit the type of data that is returned.
These five examples are taken from the topic “How racism is embedded in AI and algorithms”, from the very interesting course “Anti-Racist Approaches in Technology”, by the British digital education platform Future Learn.
For details about the course and how to enroll, click on this link: https://www.futurelearn.com/courses/anti-racist-technologies
To summarize, racial bias is unfortunately also to be found within the AI industry and the AI itself. Courses, such as the Anti-Racist Approaches in Technology help to understand the issue and give ideas on how to tackle it.
References
Metz, C. (2021). Who Is Making Sure the A.I. Machines Aren’t Racist? The New York Times. [online] 15 Mar. Available at: https://www.nytimes.com/2021/03/15/technology/artificial-intelligence-google-bias.html.