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The Transformative Power of Generative AI in the Legal Field

Law Technology Today

Enter generative AI, a revolutionary technology that has taken the world by storm. By harnessing machine learning models, generative AI can generate quick content in response to users’ prompts – whether it be text, images or code (and other examples are sure to follow).

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A Roadmap for Integrating AI at Your Law Firm 

Centerbase

For example, the American Bar Association’s Law Technology Today often covers topics related to AI, machine learning, and automation in law practice. This helps ensure your firm factors in compliance and ethical considerations when making decisions about using AI.

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Handout from “Ethical Implications of Generative AI for the Michigan Lawyer” Presentation

Dennis Kennedy

It is based on advanced machine learning models that learn patterns from vast amounts of data and can produce novel outputs based on that learning. Can AI assist lawyers in maintaining records and ensuring compliance with record-keeping regulations? Absolutely.

Lawyer 85
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Handout from “Ethical Implications of Generative AI for the Michigan Lawyer” Presentation

Legal Tech Monitor

It is based on advanced machine learning models that learn patterns from vast amounts of data and can produce novel outputs based on that learning. Can AI assist lawyers in maintaining records and ensuring compliance with record-keeping regulations? Absolutely.

Lawyer 52
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Wisedocs is exhibiting at the prestigious and recognized American Bar Association Conference: ABA Techshow 2023

Law Technology Today

ABA TECHSHOW: Meet Wisedocs Wisedocs is the medical record review machine learning software for insurance carriers, healthcare providers, laws firms, and TPAs making waves in the claims industry. We serve the auto, liability, disability, workers’ compensation, tort law, and similar markets.

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Voting Is Open! Pick the 15 Finalists to Compete At Startup Alley at ABA TECHSHOW 2024 in February

Above the Law - Technology

Next, we plan to expand the product’s scope to cover more aspects of the litigation process, to improve the machine learning summarization model, and to develop visualizations of evidence based on the data present in the chronology. Finally, we plan to build integrations with e-discovery and practice management products.