– TechCrunch is highlighting remarkable women in AI through a series of interviews to give them the recognition they deserve
– One of the featured women, Allison Cohen, is a senior applied AI projects manager at Mila, specializing in socially beneficial AI projects
– Cohen emphasizes the importance of interdisciplinary collaboration and navigating challenges in the male-dominated tech industry to drive responsible AI development.
TechCrunch has been featuring remarkable women in the AI industry to give them the recognition they deserve. One of the women highlighted is Allison Cohen, a senior applied AI projects manager at Mila, a research institute specializing in AI. Cohen has worked on projects such as detecting misogyny, identifying online activity of human trafficking victims, and developing an agricultural app for sustainable farming in Rwanda.
Cohen started in AI while completing a master’s in global affairs and was inspired by the field’s potential to impact world politics. She believes interdisciplinary collaboration is crucial in AI work. She emphasizes the importance of diversity, inclusion, and feminist standpoint theory in navigating the male-dominated tech industry.
Cohen’s advice for women entering the AI field is to find opportunities to volunteer and build from there. She shares her experience of transitioning into AI through volunteering with an AI ethics organization. Cohen also highlights the pressing issues facing AI, such as designing technology to fit local contexts and incorporating anthropologists and sociologists in the design process.
She raises awareness about labor exploitation in AI and recommends following the work of advocates like Krystal Kauffman. Cohen emphasizes the importance of responsible AI design from the early stages of development by considering factors like problem definition, supporting or challenging power dynamics, and empowering communities through technology use.
Cohen suggests that investors should inquire about the team’s values and accountability to local communities when evaluating projects. By prioritizing responsible practices and community impact, investors can better push for ethical AI development.