Over the past few years, many have become more familiar with the potential risks posed to the improper deployment and usage of AI/ML systems. Companies of almost all sizes and across almost all sectors have seen examples of major AI failures, leading into significant decay in trust of these systems. As a result, stakeholders across organizations have emerged as interested in remediating these risks and getting a handle on AI -- in owning AI governance. Some are drawn to technical capabilities which promise solutions to ethical problems and enable quality. Others rely on existing compliance and policy methods to enforce standards. In this session, we will describe what these different approaches look like, the pros and cons of each, and considerations to build a robust framework around AI governance that engages technical, business, and compliance teams.
Ilana Golbin, Director @ PwC Emerging Technologies and Responsible AI Lead
Ilana is a Director in PwC Labs (Emerging Tech & AI), where she serves as one of the leads for Artificial Intelligence. Ilana specializes in applying machine learning and simulation modeling to address client needs across sectors regarding strategic deployment of new services, operational efficiencies, geospatial analytics, explainability and bias. Ilana is a Certified Ethical Emerging Technologist, is listed as one of 100 “Brilliant Women in AI Ethics” in 2020, and was recently recognized in Forbes as one of 15 leaders advancing Ethical AI. Since 2018, she has led PwC’s efforts globally in the development of cutting-edge approaches to build and deploy Responsible AI.
Course curriculum
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Emerging Approaches to AI Governance: Tech-Led vs Policy-Led
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Emerging Approaches to AI Governance: Tech-Led vs Policy-Led
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