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Ep 255: Is Gen AI the New Paradigm for Technology Assisted Review in E-Discovery? Three Redgrave Scientists Discuss

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Conteúdo fornecido por Ben Ambrogi, Populus Radio, and Robert Ambrogi. Todo o conteúdo do podcast, incluindo episódios, gráficos e descrições de podcast, é carregado e fornecido diretamente por Ben Ambrogi, Populus Radio, and Robert Ambrogi ou por seu parceiro de plataforma de podcast. Se você acredita que alguém está usando seu trabalho protegido por direitos autorais sem sua permissão, siga o processo descrito aqui https://pt.player.fm/legal.

For at least two decades, artificial intelligence has been used in e-discovery to help surface and prioritize review of potentially responsive documents from large document collections. But while technology-assisted review (TAR) has traditionally been driven by AI in the form of supervised machine learning, some vendors and e-discovery professionals are starting to experiment with the use of generative AI in its place.

So how effective is generative AI for document review in e-discovery? Is it a replacement for traditional TAR or a supplement? Are there other ways in which this rapidly evolving technology can be used in discovery?

On this week’s LawNext, we are discussing the application of generative AI in e-discovery. To do so, host Bob Ambrogi is joined by three computer and data scientists from Redgrave Data, a consulting firm that specializes in e-discovery and data science. Today’s guests are:

  • Dave Lewis, chief scientific officer, who has over three decades of experience in AI and statistics.

  • Lenora Gray, data scientist, who has worked for more than 15 years in law firm project management and matter support roles.

  • Jeremy Pickens, head of applied science, a pioneer in the fields of collaborative exploratory search and technology assisted review.

Thank You To Our Sponsors

This episode of LawNext is generously made possible by our sponsors. We appreciate their support and hope you will check them out.

If you enjoy listening to LawNext, please leave us a review wherever you listen to podcasts.

  continue reading

271 episódios

Artwork
iconCompartilhar
 
Manage episode 432874640 series 2389291
Conteúdo fornecido por Ben Ambrogi, Populus Radio, and Robert Ambrogi. Todo o conteúdo do podcast, incluindo episódios, gráficos e descrições de podcast, é carregado e fornecido diretamente por Ben Ambrogi, Populus Radio, and Robert Ambrogi ou por seu parceiro de plataforma de podcast. Se você acredita que alguém está usando seu trabalho protegido por direitos autorais sem sua permissão, siga o processo descrito aqui https://pt.player.fm/legal.

For at least two decades, artificial intelligence has been used in e-discovery to help surface and prioritize review of potentially responsive documents from large document collections. But while technology-assisted review (TAR) has traditionally been driven by AI in the form of supervised machine learning, some vendors and e-discovery professionals are starting to experiment with the use of generative AI in its place.

So how effective is generative AI for document review in e-discovery? Is it a replacement for traditional TAR or a supplement? Are there other ways in which this rapidly evolving technology can be used in discovery?

On this week’s LawNext, we are discussing the application of generative AI in e-discovery. To do so, host Bob Ambrogi is joined by three computer and data scientists from Redgrave Data, a consulting firm that specializes in e-discovery and data science. Today’s guests are:

  • Dave Lewis, chief scientific officer, who has over three decades of experience in AI and statistics.

  • Lenora Gray, data scientist, who has worked for more than 15 years in law firm project management and matter support roles.

  • Jeremy Pickens, head of applied science, a pioneer in the fields of collaborative exploratory search and technology assisted review.

Thank You To Our Sponsors

This episode of LawNext is generously made possible by our sponsors. We appreciate their support and hope you will check them out.

If you enjoy listening to LawNext, please leave us a review wherever you listen to podcasts.

  continue reading

271 episódios

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