The Governance AI Life Cycle Core Principle and the NIST AI Risk Management Framework
The National Institute of Science and Technology (NIST) is a well-known, highly influential voice in the technology space. It has the ear of courts, regulators, and even international organizations. NIST […]
The Incremental Approach: Driving Successful Adoption of Legal Tech
Imagine this: You’ve invested significantly in the latest legal tech promising to transform your legal department’s operations. But weeks, then…
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Using AI for Reviewing Contracts – 5 Benefits
While contracts will still need to be reviewed by humans, that doesn’t mean you can’t start utilizing artificial intelligence when reviewing contracts.
The Future Of Legal Case Management – Trends and Innovations to Watch
Did you know that technology is reshaping how lawyers manage their cases, paving the way for a more efficient and streamlined legal practice?
Ethical Contours in AI and Automated Mobility: Key Observations from the Forum on AI and Automated Mobility
Below is a summary of the key points I offered today at the Forum on Artificial Intelligence in Automated Mobility: Terms like “Trustworthy,” “Equity,” “Accountability,” “Ethics,” and “Human Centered” are […]
The Power of Persuasion (Captology) in the Age of AI Quantum Computing
We are in the initial stages of entering through the gates of a new era, one where the power of technology to persuade us is unchartered. Why so? Because the […]
GPT-4 passes the bar exam: What does that mean for artificial intelligence tools in the legal industry?
Codex–The Stanford Center for Legal Informatics and the legal technology company Casetext recently announced what they called “a watershed moment.” Research collaborators had deployed GPT-4, the latest generation Large Language […]
AI Life Cycle Core Principles
This table provides a compendium of AI core principles that I refer to simply as the “Core Principles.” Some of these were compiled from publications issued by OECD, UNESCO, IEEE, […]
A Data Stewardship Framework for Generative AI
Data is the lifeblood of generative AI applications and these apps are ultimately only as good as the data they train on. It is obvious, therefore, that having and maintaining […]