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The New York Times OpenAI Lawsuit and Machine Learning for Lawyers

Clio

Those using the technology place significant trust in AI platforms—yet many of us don’t question where our large language models (LLMs) are getting the information they rely on to help us create AI-generated work products or complete daily tasks.

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AI and Its Impact on the Legal Industry

MatterSuite

Ultimately enabling them to make more informed decisions and provide better counsel to their clients. Contract Analysis and Due Diligence: AI technologies, such as natural language processing (NLP), have made significant strides in automating contract analysis and due diligence processes.

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Navigating Rapid Change: How AI Empowers Legal Teams to Stay Ahead

MatterSuite

This accelerates legal teams’ efficiency and prevents crucial details from being lost in the information overload. Analyzing past cases and judge behavior allows legal teams to make informed decisions on litigation, settlement, or alternative dispute resolution.

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The Future of Legal Tech: How Technology Is Transforming the Business of Law

MatterSuite

Here are some of the key technologies shaping the legal industry: Artificial Intelligence (AI) and Machine Learning Legal Research: AI-powered platforms, like ROSS, use natural language processing (NLP) and machine learning. This helps lawyers to assess the strength of their cases and make informed decisions.

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Legal AI Tools

Lawmatics

Advanced algorithms can quickly analyze vast legal information databases, statutes, and case law to provide relevant and up-to-date information. Predictive analytics: AI can predict case outcomes based on historical data to help lawyers and legal professionals make more informed decisions about case strategy and settlement options.

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Johannes Scholtes: AI Is Finally Here. Now the Hard Work Begins for the Legal Industry (TGIR Ep. 191)

3 Geeks and a Law Blog

This means that a law firm needs to work with the AI to have it better understand how to process legal information. So so it’s really, it’s really the combination of technology and the business process of ediscovery and information, governance, and then make sure that that technology is implemented in the proper way, use it the proper way.

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Helpful Guidance on Managing AI-Related Cybersecurity Risks from Hong Kong’s SFC

Debevoise Data Blog

Sensitive Inputs : LCs should have controls to assess and mitigate the risks of sensitive confidential information, such as personal data, being input by users or fed into AI LMs. Client Data : LCs should ensure that controls in relation to confidential client and business information remain effective throughout the model lifecycle.