Abstract:
In this workshop, Aparna will present a talk on how to operationalize responsible AI using machine learning observability techniques: notably with explainability – she will look at how to use statistical distance checks to monitor features and model output in production, how to analyze the effects of the changes on models and how to use explainability techniques to determine if issues are model or data related. The first step in better understanding how to manage responsible AI is model transparency. Understand and explain how models arrive at specific outcomes for any cohort of predictions and implement ML Observability into your ML workflow.
Secondly, this workshop will include a panel discussion. Engage with unique perspectives on how to approach responsible AI from an operational standpoint. Join major thought leaders championing responsible, fair, and ethical AI. Armed with a diverse array of educational and professional backgrounds, this discussion will uncover actionable insights into how to approach responsible AI from the ground up.

What You’ll Learn:
– Learn about ML Observability: how to troubleshoot, monitor, and explain models in production
– A deep dive into explainability and common explainability techniques at the global, cohort, and local level
– An understanding of common explainability use cases and how explainability can help detect bias issues in models
– A chat about ML fairness, new research, and how to make sure your models aren’t acting in discriminatory ways – operationalizng AI Ethics

Aparna Dhinakaran is Chief Product Officer at Arize AI; a startup focused on ML Observability. She was previously an ML engineer at Uber, Apple, and Tubemogul (acquired by Adobe). During her time at Uber, she built several core ML Infrastructure platforms, including Michaelangelo. She has a bachelor’s from Berkeley’s Electrical Engineering and Computer Science program, where she published research with Berkeley’s AI Research group. She is on a leave of absence from the Computer Vision Ph.D. program at Cornell University.

Amber Roberts is an astrophysicist and machine learning engineer, who was previously the Head of AI at Insight Data Science. Since then she has been at Splunk in their ML Product Org to build out ML feature solutions as an ML Product Manager. She now joins us at Arize as an ML Sales Engineer looking to help teams across industries build ML Observability into their productionalized AI environments.

Abigail Hing Wen is a New York Times Best Selling Author, rare woman-in-tech leader specializing in artificial intelligence, a filmmaker as well as a wife and mother of two. She writes and speaks about tech, AI ethics, women’s leadership, implicit bias, equity, and transforming culture.
Abigail penned the New York Times best selling novel, Loveboat, Taipei. The companion novel, Loveboat Reunion, follows a girl navigating her interests in artificial intelligence (HarperCollins Jan 25, 2022). Abigail is executive producing the Loveboat, Taipei film adaptation with the creators of the Netflix franchise, To All the Boys I’ve Loved Before. She and her work have been profiled in Entertainment Weekly, Forbes, Fortune, Cosmopolitan, NBCNews, Bloomberg, Google Talk and the World Journal, among others.
Abigail holds a BA from Harvard, where she took coursework in film, ethnic studies and government. She also holds a JD from Columbia and MFA in writing from Vermont College of Fine Arts. In her career in tech, she has negotiated multibillion dollar deals on Wall Street and in Silicon Valley, worked in venture capital and hosted Intel’s Artificial Intelligence podcast featuring leading industry experts including Andrew Ng, Facebook’s Chief AI Scientist Yann LeCun and US Congresswoman Robin Kelly. She also serves with the Partnership on AI.
“One of the most respected voices in fairness and AI.” Forbes.
Abigail lives with her husband and two sons in the San Francisco Bay Area. Her third novel (2023) explores cognitive differences in Silicon Valley and she is writing her fourth novel and a feature film script based in Silicon Valley, as well as producing a girls-in-tech animated series.
For more information: www.abigailhingwen.com
Follow IG: @abigailhingwen and Twitter: @abigailhingwen

Reid Blackman, Ph.D., is the Founder and CEO of Virtue, where he works with companies to integrate ethical risk mitigation into the development, procurement, and deployment of emerging technology products. He is the author of the book Ethical Machines, forthcoming from Harvard Business Review Press, he sat on Ernst & Young’s Artificial Intelligence Advisory Board, is a member of IEEE’s Ethically Aligned Design Initiative, and is the Chief Ethics Officer of the Government Blockchain Association.
Reid’s work has been profiled in The Wall Street Journal and Dell Perspectives and he has contributed multiple pieces to The Harvard Business Review, TechCrunch, and VentureBeat. He is regularly quoted in the news media and he delivers keynote addresses to organizations in industry, non-profit, and academia. Recent venues include The World Economic Forum, SAP, Cannes Lions, AIG, Forbes, NYU Stern School of Business, and Columbia University.
Prior to founding Virtue, Reid was a professor of philosophy at Colgate University and the University of North Carolina, Chapel Hill. His research appeared in numerous prestigious professional journals including the European Journal of Philosophy, The Canadian Journal of Philosophy, and Erkenntnis. He also founded a fireworks wholesaling company and was even a flying trapeze instructor. He received his B.A. from Cornell University, his M.A. from Northwestern University, and his Ph.D. from The University of Texas, Austin.