The Impact of Biases in Artificial Intelligence on the Job Market

Abstract

As artificial intelligence has become more prevalent in an ever-advancing society, so have AI based programs in various sectors of the job market. Historically, advancements in automation and technology have been seen to bring profound change to the structures of the job market and society, and artificial intelligence can be grouped in that same category of technological advancement. With AI being used to a higher degree in hiring processes, tech jobs, and automation, there is a rising fear about increased unemployment rates, economic inequality, and it being far more difficult to get certain jobs. On the other hand, artificial intelligence may allow for more jobs in other fields and can allow for enhanced productivity and growth in various business sectors. Despite its advancement, artificial intelligence still exhibits imperfections—particularly its potential for bias in the job market. For example, artificial intelligence hiring algorithms can exacerbate existing biases drawn from past data and can cause unfair hiring practices against any given race, gender, age, or other metric. Along with unfair hiring, biases in AI can lead to wage inequality/unfair employee evaluation, and on top of all of that, AI biases can have an effect on other parts of society, such as healthcare and criminal detection, by targeting certain races, genders, or age groups using existing data. While AI may posit some benefits (enhanced productivity, possibly more jobs), there still may be more downsides that follow (biases, increased unemployment rates, economic inequality).