Why AI treats men and women differently and what to do about it - Alexandra Ebert

Is AI inherently sexist? Or are we building AI with the biases we are still struggling to root out of our human interactions? And is a lack of diversity in the innovation process translating into the technology? AI is built and maintained by data, and if the data collected only represents the view of one type of individual or overly weights the importance of this information then the decisions AI makes will reinforce this inequality.  

In a 2019 article for Sandford Social Innovation Review, entitled 'When Good Algorithms Go Sexist: Why and How to Advance AI Gender Equity', the co-author Genevieve Smith shared how she and her husband applied for the same credit card. Despite having a slightly better credit score and the same income, expenses and debt as her husband, the credit card company set her credit limit at almost half the amount. Customer service employees were unable to explain why the algorithm deemed the wife significantly less creditworthy. 

What is most likely to have happened in this case is that AI was to blame as Genevieve shares in her article many institutions make decisions based on artificial intelligence (AI) systems using machine learning (ML), whereby a series of algorithms takes and learns from massive amounts of data to find patterns and make predictions.  Yet gender bias in these systems is pervasive and has profound impacts on women’s short and long-term psychological, economic and health security. 

On today’s episode we welcome Alexandra Ebert who will share what AI is and how it will impact our jobs but also why you don’t need to be scared of it. Most importantly, Alexandra tells us why we need to manage AI carefully to ensure equitable outcomes and so as not to exacerbate or perpetuate existing gender inequities.

 

Alexandra's Story

LinkedIn - Alexandra Ebert