Panelist Yan Chow

Yan Chow

Automation Everywhere

United States

Yan Chow joined Automation Anywhere in 2019 to help launch the intelligence automation company’s health care vertical. He was previously medical director for digital medicine in the Translational Medicine group at biotech company Amgen and CIO at health care consultancy LongView International Technology Solutions. Chow has founded and advised a number of startups in the digital health, AI, storage, and database spaces, including a venture-funded NLP analytics company that achieved a successful exit. He has a bachelor’s degree from Harvard University; a medical degree from the University of California, San Diego; and an MBA from the University of California, Berkeley’s Haas Business School.

Voting History

Statement	Response
Organizations are sufficiently expanding risk management capabilities to address AI-related risks. Disagree	“AI is becoming a playmaker for future technologies. But AI’s data security can be compromised, often by weaponized AI, like deepfakes and automated attacks. Fighting fire with fire, generative AI and automation empowers infosec teams to respond quickly, accurately, and scalably. Unfortunately, fast-moving technologies require time and experience to be understood. This time lag is an asymmetric window of opportunity hackers can exploit repeatedly. AI can exhibit bias. Errors in analytics incorporated into AI algorithms have led to discriminatory outcomes in hiring, loan approvals, and health coverage. Watchdogs are now calling for closer scrutiny of data inputs. Yet organizations have neither the expertise, resources, nor industry guidance to address this issue. AI also introduces complex legal and ethical questions, such as the rights of individuals and the liability for harm caused by AI. Job displacement and workforce restructuring raise ethical and socioeconomic concerns. Worker reskilling and responsible AI inevitably come into focus. Organizations in the early stages of AI adoption have limited options. AI was created to understand and help us. It may take AI to understand its own risks.”

Statement

Response

Organizations are sufficiently expanding risk management capabilities to address AI-related risks. Disagree

“AI is becoming a playmaker for future technologies. But AI’s data security can be compromised, often by weaponized AI, like deepfakes and automated attacks. Fighting fire with fire, generative AI and automation empowers infosec teams to respond quickly, accurately, and scalably. Unfortunately, fast-moving technologies require time and experience to be understood. This time lag is an asymmetric window of opportunity hackers can exploit repeatedly.

AI can exhibit bias. Errors in analytics incorporated into AI algorithms have led to discriminatory outcomes in hiring, loan approvals, and health coverage. Watchdogs are now calling for closer scrutiny of data inputs. Yet organizations have neither the expertise, resources, nor industry guidance to address this issue.

AI also introduces complex legal and ethical questions, such as the rights of individuals and the liability for harm caused by AI. Job displacement and workforce restructuring raise ethical and socioeconomic concerns. Worker reskilling and responsible AI inevitably come into focus.

Organizations in the early stages of AI adoption have limited options. AI was created to understand and help us. It may take AI to understand its own risks.”