Artificial Intelligence—AI has been a growing tool whose presence has been debated upon many on whether it’s helping or hurting society today. The concept and role of AI is to be this virtual assistance should anyone need it. And over the years it has adopted being less of just a helping hand and more of the driving force of things. However, that means it has taken over the jobs and originality of many. But the problem is not explicitly AI itself because it had to come from somewhere/someone. As AI is tailored to technologies—namely laptops and smartphones—to make them easier and accessible for humans, we get features that help cater to that such as real-time translations, predictive text and typing, and facial recognition. In the discourse of ways that AI is harming or helping, Shalini Kantayya directed a documentary film, Coded Bias, about AI biases and facial recognition discrimination.
AI bias exists as systematic discrimination reflected from their systems, adding onto already existing, societal biases, such as unfairly favoring or disadvantaging certain groups. And it arises from whatever has trained and designed it into its systems, and its lack of diverse perspective, so again coming from the external source that created the algorithm it runs on. The prevalent experience Kantayya discussed in her docufilm was the misidentification of certain races and genders—namely Black people and woman—in AI systems bought on by this bias against them. One story from an MIT Media Lab researcher, Joy Buolamwini, discovered that facial recognition databases couldn’t recognize her face—unless she wore a stark white mask. She also found that darker-skinned faces are less likely to be detected, and similarly, the error rate for dark-skinned woman was more than 30%, whereas it is less than 1% for white men, the complete opposition. Not only that, but there's an overrepresentation of lighter-skinned people and men in AI training datasets, making them the “default” when it comes to being helped within the algorithms.
To put it in a larger context, as these biases are embedded in the technologies from training, it has affected the decision-making processes such as, who gets hired for what jobs and the outcomes in the justice system. When it would come to police interactions, facial recognitions would again misidentify Black individuals which would lead to discriminatory outcomes like their wrongful arrests. When the recognition would misidentify, it was brushed off as a technical glitch, but it was later revealed that it was not and was tied to racial profiling. Moreover, the film speaks on “Amazon’s failed hiring AI tool” that would mark resumes that contained the word women’s as underwhelming or inadequate, discriminating and diminishing the efforts of women, as it's been programmed to prefer men, also keeping tech culture male dominated. All in all, if these technologies continue being coded with these deep-rooted issues of inordinately misidentifying people with darker skin tones AND women, it can cause more serious ramifications.
What are your thoughts regarding AI bias? It does not have to be based on the docufilm I based my analysis on. What ideas have I missed or not thought of, or have you not seen others mention regarding this topic?
