An opportunity to hear first-hand insight and ask questions on how regulation is taking shape, what to expect and what you can do to prepare now.
Get ahead of the curve with an understanding of how different businesses are proactively preparing as the US and EU start to align on future AI regulation. This panel will explore how regulation is likely to take shape and what organizations should be doing now to ensure they are proactively prepared.
Shawn Rizvi
Integrity Risk Launches - Artificial Intelligence & Machine Learning
Meta
Shawn (CIPP, CDPSE) has over 10 years of experience in managing Data Risk across Regulatory, Privacy, Governance and Cybersecurity vectors. He started his career with IBM in 2012 and would go on to join Deloitte’s Canadian practice in 2015 and EY’s Canadian practice in 2018. In 2021 he would become the CPO at the Edtechn Unicorn – Applyboard where established and led the company’s first Privacy & Data Governance department, program and strategy. His strategic leadership was critical to Applyboard’s success in preventing major operational cost from rapidly evolving regulatory changes across its over 120 countries in which it operated in. He is now currently at Meta, where he works within the Integrity and Risk Launches organization and has successfully helped launch over 300 related AI and ML related projects. He has also helped drive EU Digital Service Act and Digital Markets Act preparedness across multiple Meta products.
Shawn has worked with market leaders across the globe to drive better business decisions based on enabling and scaling AI technologies through effective risk management and data governance techniques. This includes helping global brands navigate complex regulations and pioneering new frameworks that ensure cutting edge technology empowers society responsibly. He is also a subject matter expert on over 100 different regulations, framework and practices related to data risk. On his spare time, he provides mentorship to start up tech firms in Toronto and is passionate about helping start-ups succeed.
Karen Silverman
CEO and Founder
The Cantellus Group
Karen is a leading global expert in practical governance strategies for AI and other frontier technologies. As the CEO and Founder of The Cantellus Group, she advises Fortune 50 companies, startups, consortia, and the public sector on how to manage cutting-edge technologies in a rapidly changing policy environment. Her expertise is informed by more than 20 years of practice and management leadership at Latham & Watkins, LLP where she advised global businesses in complex antitrust matters, M&A, governance, ESG, and crisis management. Karen chairs the board of a public benefit corporation developing complex content moderation tools. She is an SME for the Business Roundtable's Responsible AI Initiative, and a World Economic Forum Global Innovator and Karen sits on its Global AI Council. She serves on the boards of Krunam, AI.EDU, Legal Momentum and Not For Sale.
Brandon Allgood
Chief AI Officer
Valo
In groups, participants will share best practices and insight to address a series of challenges facing enterprises as they deploy and scale AI solutions. Attendees will take part in three out of five discussions, rotating every 20 minutes.
- Defining, building and leveraging trust
- Develop internally or buy third party?
- Ensuring robustness and building resilience
- Mitigating algorithmic bias
- Shining a light on explainability
- Establishing effective communication: top-down or bottom-up?
Jillian Powers
Responsible AI Lead
JP Morgan Chase
Shawn Rizvi
Integrity Risk Launches - Artificial Intelligence & Machine Learning
Meta
Shawn (CIPP, CDPSE) has over 10 years of experience in managing Data Risk across Regulatory, Privacy, Governance and Cybersecurity vectors. He started his career with IBM in 2012 and would go on to join Deloitte’s Canadian practice in 2015 and EY’s Canadian practice in 2018. In 2021 he would become the CPO at the Edtechn Unicorn – Applyboard where established and led the company’s first Privacy & Data Governance department, program and strategy. His strategic leadership was critical to Applyboard’s success in preventing major operational cost from rapidly evolving regulatory changes across its over 120 countries in which it operated in. He is now currently at Meta, where he works within the Integrity and Risk Launches organization and has successfully helped launch over 300 related AI and ML related projects. He has also helped drive EU Digital Service Act and Digital Markets Act preparedness across multiple Meta products.
Shawn has worked with market leaders across the globe to drive better business decisions based on enabling and scaling AI technologies through effective risk management and data governance techniques. This includes helping global brands navigate complex regulations and pioneering new frameworks that ensure cutting edge technology empowers society responsibly. He is also a subject matter expert on over 100 different regulations, framework and practices related to data risk. On his spare time, he provides mentorship to start up tech firms in Toronto and is passionate about helping start-ups succeed.
Aysha Machingara
Risk Strategy- Decision Science & Analytics
Uber
Suhas Manangi
Group Product Manager- AI,ML Defense Platform
Airbnb
Suhas Manangi is the product head of the AI/ML Defense Platform team at Airbnb, where he leads work on accelerating the use of AI and machine learning in fighting fraud and abuse to ensure trust and safety on the online marketplace. Before joining Airbnb, he spent many years working with trust and safety teams at Amazon, Lyft, and Microsoft. Manangi is also active in the product management community, helping product managers transition to using AI/machine learning in their products.
Jie Chen
Managing Director in Corporate Model Risk
Wells Fargo
Kiran Yalavarthy
Executive Vice President, Head of Risk Modeling Group
Wells Fargo
Adhar Walia
Senior Director of Product Management, AI ML
CVS Health
AI governance frameworks could help organizations learn, govern, monitor, and mature AI adoption and scale. While there is no one-size-fits-all approach, organizations can consider adopting processes to mitigate risk. This session will explore:
- What an effective AI governance and risk management framework looks like in practice
- The core principles that can be operationalized
- Implementation of a functional framework irrespective of available resources and organization size
- The most vital aspects of a framework and how to tailor them based on need
- Generating maximum additional value as a result
Gurleen Virk
Responsible Innovation Program Manager- Responsible AI, ML
Google
Ken Archer
AI Ethics - Principal Product Manger
Twitch
Daniel Wu
Strategic AI Leadership | Keynote Speaker | Educator | Entrepreneur Course Facilitator
Stanford University
Daniel Wu is an accomplished technical leader with over 20 years of expertise in software engineering, AI/ML, and team development. With a diverse career spanning technology, education, finance, and healthcare, he is credited for establishing high-performing AI teams, pioneering point-of-care expert systems, co-founding a successful online personal finance marketplace, and leading the development of an innovative online real estate brokerage platform. Passionate about technology democratization and ethical AI practices, Daniel actively promotes these principles through involvement in computer science and AI/ML education programs. A sought-after speaker, he shares insights and experiences at international conferences and corporate events. Daniel holds a computer science degree from Stanford University.
Mitigating risk is a means to achieve optimal business outcomes and ethical concerns belong in the conversation. So how can organizations effectively bridge current divides between innovation and ethics, and catalyze previously impossible growth?
Betsy Greytok
VP of Ethics and Policy
IBM
Valeria Sadovykh
Technology Strategist
Microsoft
Oriana Medlicott
Senior Researcher - Technology & Innovation Strategy (Lead on AI Ethics)
Fujitsu
Oriana Medlicott is leading AI Ethics in the Technology Strategy Unit at Fujitsu. She is the co-founder and co-host of Let’s Chat Ethics Podcast and on the advisory board of the AI Ethics Journal at UCLA. Prior to Fujitsu, Oriana worked as an AI Ethics consultant with start-ups, think tanks and academia across the USA and Europe. In Autumn of 2022, Oriana will lecture introduction to AI Ethics in industry at Nottingham Trent University. She holds a Masters in Philosophy, looking at the Ethics of AI and Biotech.
AI has tremendous potential to create sustained long-term value – as long as you get it right. From day one of developing AI strategies, it is imperative that management understand the risks and the opportunities – and how ethics can influence them both.
Daniel Wu
Strategic AI Leadership | Keynote Speaker | Educator | Entrepreneur Course Facilitator
Stanford University
Daniel Wu is an accomplished technical leader with over 20 years of expertise in software engineering, AI/ML, and team development. With a diverse career spanning technology, education, finance, and healthcare, he is credited for establishing high-performing AI teams, pioneering point-of-care expert systems, co-founding a successful online personal finance marketplace, and leading the development of an innovative online real estate brokerage platform. Passionate about technology democratization and ethical AI practices, Daniel actively promotes these principles through involvement in computer science and AI/ML education programs. A sought-after speaker, he shares insights and experiences at international conferences and corporate events. Daniel holds a computer science degree from Stanford University.
Daniel Kandola
Vice President, EMEA
Camms
Daniel Kandola is responsible for Camms’ development growth strategy in the UK and Europe, whilst overseeing the process and operations within the region. Daniel has experience in implementing powerful and agile GRC, ESG, Strategy and Project software solutions, and has played a key role in leading the growth of the EMEA client base over the past 7 years. Daniel is passionate about helping organisations harness their risk intelligence to achieve strategic business success. A graduate from the University of Sheffield, Daniel obtained a First Class Bachelor of Science degree in Information Management for Business.
