Speaker "Frida Polli" Details Back



Keeping AI Accountable and Bias-Free


As the use of AI grows across industries so does the need to develop processes to ensure AI benefits everyone, not the select few. As the use of AI continues to grow, we have to monitor them to ensure it’s development continues to align with our objectives. • Management: Key point of contact in the event that is something goes wrong this person must have the authority to manage any negative fallout from an algorithmic system. How often should developers check in on their AI? • AI Auditing: Historical data is inaccurate to rely on; this way of relating perpetuates bias, especially if bias is already inherent within the dataset. • Explainable AI: How every decision / error needs to be understood in order mitigate similar issues in the future.


Dr. Frida Polli began her professional career as an academic neuroscientist at Harvard and MIT for four years. During her tenure at MIT, Frida was at the top 1% of postdoctoral fellows for winning multiple awards including the NIH National Research Service Award ($120K); NARSAD Young Investigator Award ($60K); and HST Catalyst Award ($80K). From 2010 to 2012 Dr. Polli enrolled in Harvard Business School, where she was the Winner of Robert S. Kaplan Life Sciences Fellowship Award, served as the VP of Keynotes for HBS Cyberposium 17, and Co-Founded CrimsonTies - an HBS-based online social platform to facilitate volunteering. After graduation, Dr. Polli converged her neuroscience and entrepreneurship education to become Co-Founder of pymetrics; an AI-based platform that uses proven neuroscience games and cutting edge data science to reinvent the way companies recruit, hire, and retain talent by providing hiring managers with an objective view of how an applicant’s cognitive abilities stack next to top performers. The technology powering pymetrics has contributed to dozens of Fortune 500 companies -- from Unilever to Accenture -- observing drastic improvements in hiring, including up to a 60 percent increase in employee retention, a 75 percent reduction in time to hire, an 18 percent increase in female technical hires, and a 150 percent increase in female applicants for financial roles.