AI Ethics
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When AI Conversations Become Compliance Risks: Rethinking Confidentiality in the ChatGPT Era
AI chats may seem private, but legal experts warn they could become courtroom evidence. As AI integrates into legal work, professionals must rethink digital confidentiality and privilege risks.
The Shape of Justice: How Topological Network Mapping Could Transform Legal Practice
What if justice had a shape — not rigid scales or a blindfolded figure, but a living, dynamic map? Imagine causation as a multidimensional space, where influence, control, and responsibility could be mapped across a...
Criminal Conviction Reversed After State Failed to Timely & Fully Disclose its Use of a Type of Artificial Intelligence
A Maryland appellate court reversed a robbery conviction after prosecutors failed to timely disclose their use of facial recognition technology, an AI tool central to the investigation. The court found the late and incomplete disclosure...
Epiphanies or Illusions? Testing AI’s Ability to Find Real Knowledge Patterns – Part Two
The moment of truth had arrived. Were ChatGPT’s insights genuine epiphanies, valuable new connections across knowledge domains with real practical and theoretical implications, or were they merely convincing illusions? Had the AI genuinely expanded human...
Beagle Launches Professional Services Line to Support Ethical, Accurate AI Use in Legal Practice
Discover Beagle introduces Professional Services to guide legal teams in ethical, defensible AI use across any review platform, offering prompt engineering, training, and behavior coaching.
When AI Policies Fail: The AI Sanctions in Johnson v. Dunn and What They Mean for the Profession
The Johnson v. Dunn case marks a turning point in judicial tolerance for AI citation errors. Despite clear firm policies and experienced counsel, the court imposed severe sanctions, signaling that only individual verification, not institutional...
Adobe’s Legally Grounded AI Model Offers a Blueprint for Responsible Innovation
Adobe sets a new benchmark for legal AI development with Firefly, a model trained exclusively on licensed data. Its compliance-first strategy highlights a path forward in a contentious landscape.
Navigating AI’s Twin Perils: The Rise of the Risk-Mitigation Officer
Generative AI is reshaping trust and accountability in the digital landscape, leading to the emergence of the AI Risk-Mitigation Officer role. This strategic position blends technical, regulatory, and ethical expertise to proactively manage AI risks,...
The $20 Test: What a Parking Lot Taught Me About AI and Legal Judgment
When a young lawyer found a $20 bill, he faced a simple yet profound ethical choice. Decades later, Hon. Judge Ralph Artigliere (ret) compares his human decision to AI’s analysis, revealing why empathy, intuition, and...
Panel of Experts for Everyone About Anything – Part Two: Demonstration by analysis of an article predicting new jobs created by AI
In this article, Ralph Losey continues discussing the software, Panel of Experts for Everyone About Anything, and its demonstration while exploring potential job roles arising from AI, particularly the “Sin Eater” concept proposed by Professor...
Document Content vs. Metadata in eDiscovery AI: A Clarification of Scope, Access, and Accuracy
Clear separation between document content and metadata is essential for accurate AI-driven eDiscovery. Without proper handling, legal teams risk flawed timelines, missed privilege indicators, and incomplete review.
Avoiding the Third Rail of Legal AI: Don’t Let the Machine Think for You
As AI becomes more powerful, legal professionals face growing pressure to rely on it for core tasks. But true responsibility means using these tools wisely, without surrendering judgment, accountability, or the human craft of legal...