Remove 2010 Remove Analytics Remove Machine learning
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Peter Geovanes

Colin S. Levy

Peter Geovanes is a results-driven data, analytics & AI/ML executive (JD/MBA) who provides a unique background that combines data science, artificial intelligence and machine learning capabilities along with business strategy, innovation, R&D, project management and management consulting skills.

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The Law Library of Babel: Exploring the Infinite Dimensions of Law and Technology

Colin S. Levy

As a representative from Lex Machina, a legal analytics company, took the stage, I had no idea that the journey I was about to embark upon would lead me to the very frontiers of human knowledge and understanding. Duke University Press Books, 2010. Perspectives from Analytical, Phenomenological, and Indian Traditions.

Law 103
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The Future of AI within LexisNexis and the Legal Industry with Lexis CTO Jeff Reihl – TGIR Ep. 197

3 Geeks and a Law Blog

The panelists included, Danielle Benecke, who is the founder and Global Head of machine learning at Baker McKenzie, so large law firms are hiring people to lead up machine learning within our law firms. Aaron Crews as SVP of analytics and AI at UnitedLex. Foster Sayers general counsel from Pramata.

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The Future of AI within LexisNexis and the Legal Industry with Lexis CTO Jeff Reihl – TGIR Ep. 197

Legal Tech Monitor

The panelists included, Danielle Benecke, who is the founder and Global Head of machine learning at Baker McKenzie, so large law firms are hiring people to lead up machine learning within our law firms. Aaron Crews as SVP of analytics and AI at UnitedLex. Foster Sayers general counsel from Pramata.

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Increased Focus by Federal Regulators on AI and Consumer Protection in the Financial Sector

Debevoise Data Blog

As financial institutions increasingly deploy artificial intelligence (“AI”), including machine learning and automated decision-making technologies, across their business lines, U.S. Gensler also raised the need to prevent analytics from “reinforc[ing] societal inequities that may be embedded in data,” thereby deepening bias.