Racism in artificial intelligence. Is this possible?
Abstract
Artificial intelligence (AI). Undoubtedly, you must have heard about it. Today, it is everywhere. We use it in everything without even noticing it. However, with AI becoming more popular, some problems appeared. One of these problems is racism, as Julia Bossmann and Brian Rieger raised in their paper in “Weforum” [1] and “Labelbox” [2]. Racism is not a new concept, and it still exists in the modern world. Unfortunately, AI algorithms can also become racist because of their environment, the people around them, and the bias of some events. This can cause danger and injustice for some people or even hazardous and even a fatal problems.
Keywords: Artificial intelligence, Rasict, Racism, Injustice
1. Discussion
How does AI works? As Stuart J. Russell and Peter Norvig mentioned in their book, “Artificial Intelligence, a modern approach” [3] , AI works based on data it receives from the environment. First, it gets data from the environment via sen- sors, cameras, and other information processing tools. Then, it decodes them to a language that computers are familiar with, 0 and 1. After that, it makes decisions based on these data and the old data it received and then improves itself based on the information it receives over time.
So how can AI become racist? There can be several ways, but two are more hazardous than the others. The first way is that, unfortunately, there are still some racist people in our society. As Ernst Mach said, “We must not forget that all things in the world are connected with one an- other and depend on one another”. These people can be in any position. One of these positions is a computer scientist. So if someone related to an AI project, be racist, it can affect the judg- ment of the AI. For example, suppose he or she makes some bias on a race in the AI algorithm.
In that case, this algorithm can clearly become a racist algorithm. But, can an AI algorithm become racist itself? The answer is yes, it can. Even if the algorithm operated flawlessly, assume a crime detection algorithm based on AI to help the police force find criminals. Two possibilities can make this algorithm behave like a racist al- gorithm. The first possibility is that there can be racism in society and the algorithm learn from it. For example, maybe a few racist police forces exist, so the algorithm can learn from them. So even with a good algorithm, there is a possibility that the algorithm becomes racist because of the racism in society. The second possibility is that the algorithm becomes racist by accident. For example, in the previous example, there can be an accidentally higher crime rate for a group of peo- ple with a color of skin or a color of hair or even a nationality in a year, so the algorithm makes a bias for that group, which is obviously racism. Is there a solution? As Jane E. Fountain wrote in her paper, “The moon, the ghetto and artificial intelligence: Reducing systemic racism in com- putational algorithms” [4] , there are some ways to reduce this problem and also solve it. How- ever, the best way to reduce it in any aspect is less racism in society. There are several examples of this problem in real life. One of them that is raised by Lel Jones in “A Philosophical Analysis of AI and Racism” [5] is “racism in law enforce- ment AI”. One of the AI systems available now is COMPOS used by the police of the U.S. It checks the possibility of doing the same crime by an ar- rested person in the future based on their history. This system is designed to be fairer, but some cases show us the opposite. So there are many problems ahead of us. Some may say that these systems make racism less. They are correct, but racism is still a big problem. This system could only make a bad situation a less bad situation.
2. Conclusions
Overall, AI can solve many difficulties, but there can be some problems, and racism is one. So a programmer, a computer scientist, or an AI expert should be careful about what program he or she is writing because with some minor changes in their program, they can reduce the problem and prevent some irreversible events.
References
[1] J. Bossmann, Top 9 ethical issues in artificial intelli- gence, weform.org, Accessed, 2016.
URL https://www.weforum.org/agenda/2016/10/ top-10-ethical-issues-in-artificial-intelligence/
[2] B. Rieger, Labelbox Speaks on Ethics of AI at O’Reilly’s Strata Data Conference, Labelbox. Avail- able (2019).
[3] S.J.Russell,P.Norvig,ArtificialInteligenceAmodern approach, Pearson, Saddle River, New Jersey, 2010.
[4] J. E. Fountain, The moon, the ghetto and artificial intelligence: Reducing systemic racism in computa- tional algorithms, Government Information Quarterly (2021).
[5] L. Jones, A Philosophical Analysis of AI and Racism, Stance: An International Undergraduate Philosophy Journal 13 (2020) 36–46.
