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Women in AI: Allison Cohen on building responsible AI projects | TechCrunch

Apr 20, 2024 - techcrunch.com
TechCrunch is launching a series of interviews focusing on women who have contributed to the AI revolution. One of the interviewees is Allison Cohen, the senior applied AI projects manager at Mila, a Quebec-based community of over 1,200 researchers specializing in AI and machine learning. Cohen's work includes a tool that detects misogyny, an app to identify online activity from suspected human trafficking victims, and an agricultural app to recommend sustainable farming practices in Rwanda. She has also co-led on AI drug discovery at the Global Partnership on Artificial Intelligence and served as an AI strategy consultant at Deloitte.

In the interview, Cohen shares her journey into the AI field, her proudest work, and how she navigates the male-dominated tech industry. She advises women seeking to enter the AI field to find an open door and use it to hone their voice in the space. Cohen also discusses the pressing issues facing AI, including the need for local adaptation, interdisciplinary collaboration, and designing tools for those who need them most. She also highlights the issue of labor exploitation in AI and the importance of building AI responsibly from the earliest stages of the process.

Key takeaways:

  • Allison Cohen, the senior applied AI projects manager at Mila, is working on socially beneficial AI projects, including a tool that detects misogyny and an app to identify online activity from suspected human trafficking victims.
  • One of Cohen's projects involved building a dataset containing instances of subtle and overt expressions of bias against women, which was recognized at the socially responsible language modeling workshop at the leading AI conference, NeurIPS.
  • Cohen advises women seeking to enter the AI field to find an open door and use it to hone their voice in the space, even if it's through volunteering or unrelated to their background or experience.
  • She believes the most pressing issues facing AI include reconciling the scalability of AI with local knowledge and needs, incorporating anthropologists and sociologists into the AI design process, and altering incentives to design tools for those who need it most rather than those whose data or business is most profitable.
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