In recent years, technology has become increasingly intertwined with our daily lives and the emergence of Artificial Intelligence (AI) has made it possible for computers to do tasks traditionally performed by humans. However, AI often inherits the same biases that are embedded in humans. AI bias is when algorithmically-driven decisions are based on incorrect assumptions, and it can often lead to counterproductive and discriminatory outcomes for those on the receiving end.
One form of AI bias is known as confirmatory bias, where a computer will act upon a conclusion without thoroughly exploring the facts of the situation. For example, if a computer algorithm is given data where the majority of members of a certain demographic have a negative outcome from a certain action, the computer algorithm may jump to the conclusion that members of that same demographic are not suitable for that specific action, even if the opposite could be true. This can lead to disparaging outcomes for members of minority groups and create an unfair advantage for more privileged individuals.
Additionally, another form of AI bias is known as “homophily”, a term borrowed from sociology which explains our tendency to bond with people similar to us. AI models harness this bias to target ads and content to people of a similar age, race and gender to the user, leading to “echo chambers” where people are only exposed to ideas that are in line with their existing beliefs. This can lead to an increase in polarisation between groups and entrench existing discriminatory beliefs.
However, steps can be taken to mitigate the effects of AI bias. Firstly, data sets should be diverse, representative of all demographics, and free of error and bias. Ensuring human oversight and combining complex decision logic with more straightforward data validation can also help to prevent potentially damaging AI biases. By addressing these issues and tackling bias head-on, we can ensure that AI is used in a responsible and ethical way.
Transformation! 