Description
Total Credits: 1.0 Professional Practice
In the third session of NYSBA’s Artificial Intelligence Webinar Series, panelists will discuss current data privacy laws, both in the U.S. and the E.U., including their implications for the use of artificial intelligence, analytics, and big data. Our panelists will provide their views on the impact of the new General Data Protection Regulation, and practical steps lawyers and their clients can take towards compliance.
Program Faculty
Lisa J. Sotto, Esq., Managing Partner, Hunton & Williams LLP, NYC, and Chair of the Firm’s Global Privacy and Cybersecurity Practice
Joseph W. Jerome, Esq., Privacy Counsel, Privacy & Data Project at Center for Democracy & Technology, Center for Democracy & Technology
Committee on Technology and the Legal Profession Chair
Mark A. Berman, Esq., Ganfer & Shore LLP
Materials
Slides |
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Slides |
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| ABA Model Rule 1.1 and Comment | Available after Purchase | ||
| ABA Model Rule 1.1 and Comment | Available after Purchase | ||
| PowerPoint | Available after Purchase | ||
| New York Rule 1.1 | Available after Purchase | ||
| PowerPoint | Available after Purchase | ||
| PowerPoint | Available after Purchase | ||
Materials |
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Materials |
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| New York Rule 1.1 | Available after Purchase | ||
| ABA Model Rule 1.6 and Comment | Available after Purchase | ||
| Artificial Intelligence and the Future of Legal Practice | Available after Purchase | ||
| K. Hume - The Temporality of Artificial Intelligence – Quam Proxime As near as may be | Available after Purchase | ||
| ABA Model Rule 1.6 and Comment | Available after Purchase | ||
| K. Hume - How to Spot a Machine Learning Opportunity, Even If You Aren’t a Data Scientist | Available after Purchase | ||
| Artificial Intelligence and the Future of Legal Practice | Available after Purchase | ||
| K. Hume - Ethical Algorithims - Bias and Explainability in Machine Learning Systems | Available after Purchase | ||
| New York Rule 1.6 | Available after Purchase | ||
| Faculty Bios | Available after Purchase | ||
| Faculty Bios | Available after Purchase | ||
| New York Rule 1.6 | Available after Purchase | ||
| Faculty Biographies | Available after Purchase | ||
| K. Hume - The Temporality of Artificial Intelligence – Quam Proxime As near as may be | Available after Purchase | ||
| Faculty Biographies | Available after Purchase | ||
| K. Hume - How to Spot a Machine Learning Opportunity, Even If You Aren’t a Data Scientist | Available after Purchase | ||
| K. Hume - Ethical Algorithims - Bias and Explainability in Machine Learning Systems | Available after Purchase | ||
| Faculty Bios | Available after Purchase | ||