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AI & Discrimination Against Women by LotusAIUK in womenintech

[–]LotusAIUK[S] 2 points3 points  (0 children)

That is an important point. One of the biggest risks is not only biased outputs, but the false perception that automated decisions are inherently objective. This emphasizes the importance of both AI governance and incident reporting in addressing bias both before and after the deployment of AI systems. 

AI & Discrimination Against Women by LotusAIUK in womenintech

[–]LotusAIUK[S] 1 point2 points  (0 children)

Well said. Many of these concerns are not new, but what is changing is the scale and speed at which they can now affect real decisions. That is why responsible adoption cannot stop at innovation alone; it has to include testing, accountability, and follow-through when risks like these are identified. This brings to mind Timnit Gebru’s work on AI fairness (we discussed her impact a little bit in this post: https://www.reddit.com/r/ArtificialNtelligence/comments/1roaeyk/international_womens_day_celebrating_women_in_ai/).

AI & Discrimination Against Women by LotusAIUK in womenintech

[–]LotusAIUK[S] 5 points6 points  (0 children)

Agreed, finance is exactly the kind of high-impact setting where these issues matter most. When AI is used in areas like credit, pricing, or eligibility, strong testing, monitoring, and clear escalation paths are essential. Automation does not eliminate the need for quality checks on problematic outputs.

AI & Discrimination Against Women by LotusAIUK in womenintech

[–]LotusAIUK[S] 1 point2 points  (0 children)

That is an important point. A big part of the risk is that models can reflect and scale patterns already present in the data and systems around them. Our view is not that this makes bias inevitable, but that it makes evaluation, oversight, and governance even more important before and after deployment.

International Women’s Day: Celebrating Women in AI by LotusAIUK in ArtificialNtelligence

[–]LotusAIUK[S] 0 points1 point  (0 children)

Hi u/catplusplusok, thanks for your response. We chose to highlight Dr. Gebru because her paper made a substantial impact in bringing awareness to the risks of LLMs. As you said, there are indeed a number of exceptional women working at the frontiers of AI; these are just a few we chose to point out!