The PRO Framework: From Documentation to Due Diligence
The CORE framework captures AI system architecture as a blueprint, while PRO adds policies, risk analysis, and outcomes that support due diligence.
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AI Technology for Lawyers: Resources and Further Reading
Resources and further reading for applying the technical concepts introduced in the AI Technology for Lawyers series.
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AI Technology for Lawyers: Alignment, Evaluation, and Drift
Alignment, evaluation, explainability, and drift determine how AI systems are tested, monitored, and governed over time.
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AI Technology for Lawyers: Agentic AI
Agentic AI moves from generating outputs to taking actions, changing the authorization, liability, and security questions organizations must answer.
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AI Technology for Lawyers: Retrieval and Grounding
Retrieval-augmented generation connects AI models to external documents, improving grounding while introducing its own legal and governance considerations.
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AI Technology for Lawyers: Model vs. System
When lawyers discuss AI, they often conflate the model with the deployed system, creating analytical errors.
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AI Technology for Lawyers: Tokens, Context, and Inference
Tokens are the units that models actually process, shaping AI costs, context limits, and inference behavior.
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AI Technology for Lawyers: How Models Learn
How AI models learn patterns through transformers, training, fine-tuning, and inference—and what those distinctions mean for legal analysis.
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AI Technology for Lawyers: The AI Hierarchy
The term “artificial intelligence” encompasses a broad range of technologies, and imprecise usage creates confusion.
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AI Technology for Lawyers: A Technical Foundation
Understanding AI technology is no longer optional for lawyers.
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AI Governance Beyond the EU AI Act
Why effective AI governance must address intellectual property, contractual, liability, data, safety, and operational risks beyond regulatory categories.
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