Ethical considerations of AI. cybersecurity Tag Archives

February 25, 2026

Overview of Two VERDICT Columns by Marci A. Hamilton on the Epstein Files*

Two recent opinion columns published on Justia Verdict – Legal Analysis and Commentary from Justia examine the legal, political, and moral implications of the continuing disclosures surrounding the Jeffrey Epstein investigations. Written by Professor Marci A. Hamilton of the University of Pennsylvania and founder of CHILD USA, the essays present a forceful argument that accountability for systemic abuse requires sustained legal pressure and public transparency. The views expressed are those of the author and do not represent the official position of Justia.

1. “The Three Avenues to Justice in the Epstein Cases” (Feb. 24, 2026)

In The Three Avenues to Justice in the Epstein Cases, Professor Hamilton argues that meaningful accountability is likely to emerge through three principal legal pathways rather than through federal prosecutorial initiative alone.

February 19, 2026

From Capability to Integration: A Lawyer’s View of AI’s Next Phase

by David Badertscher

A recent practitioner commentary offers a confident assessment of the current state of large language models (LLMs) in legal practice, arguing that the primary barriers to adoption are no longer questions of intelligence or reliability but rather issues of infrastructure and workflow integration. Writing from the perspective of a lawyer who uses advanced models daily, the author contends that modern systems have already reached a level of practical competence sufficient for much of routine legal work, and that the profession’s hesitation reflects outdated assumptions about hallucinations and model limitations.

Central to the argument is the claim that hallucinations, once the dominant concern surrounding generative AI, have largely receded as a meaningful obstacle. According to the author’s experience, newer models rarely produce fabricated information, and overall error rates compare favorably with those of competent junior associates. This view reflects a broader shift in perception: rather than treating LLMs as experimental tools requiring constant skepticism, the author frames them as increasingly dependable collaborators capable of supporting substantive legal tasks.

The post also challenges prevailing narratives about the intellectual difficulty of legal work. While acknowledging that certain cases demand deep expertise, the author suggests that the majority of legal tasks rely on skills such as careful reasoning, synthesis of precedent, structured writing, and research , areas where modern LLMs already excel. By reframing legal practice as process-driven rather than exclusively intellectually rarefied, the commentary positions AI as well aligned with the day-to-day realities of the profession.

February 15, 2026

Synthetic Data: The Hidden Lever Behind Responsible AI Strategy

by David Badertscher

Synthetic data acts as a “hidden lever” in responsible AI by enabling organizations to train, test, and validate AI models without violating privacy, using copyrighted material, or relying on biased real-world datasets. It allows for the deliberate creation of diverse, balanced datasets, transforming AI development from reactive bias correction to proactive “fairness by design“.

In a recent analysis, Professor Peter Lee of UC Davis School of Law argues that synthetic data could reshape the legal and economic landscape of AI. For organizations navigating compliance, intellectual property risks, and data privacy obligations, this development deserves close attention. Synthetic datasets promise to reduce reliance on sensitive real-world information, potentially lowering exposure to copyright disputes and privacy liabilities. For executives responsible for innovative budgets and risk management, that sounds like a compelling proposition.

Yet the opportunity comes with tradeoffs. Synthetic data does not eliminate risk — it transforms it. Lee highlights issues such as hidden bias, model degradation, and governance challenges when artificial datasets begin influencing real-world decision making. In other words, the question for leadership is not whether to adopt AI tools, but how to ensure that the data behind them remains trustworthy and aligned with organizational values.

February 11, 2026

Better than the Real Thing? Promises and Perils of Synthetic Data: An Overview of Professor Peter Lee’s Essay Published in VERDICT

by David Badertscher

EXECUTIVE SUMMARY:

Professor Peter Lee’s VERDICT essay argues that synthetic data may revolutionize AI development by providing scalable, legally safer training material. Yet he warns that artificial datasets introduce new risks such as model collapse, bias, and misuse that demand proactive legal oversight. Rather than replacing existing regulatory debates, synthetic data transforms them, requiring courts, policymakers, and information professionals to rethink how innovation, privacy, and intellectual property intersect in the AI era

BETTER THAN THE REAL THING?

January 30, 2026

Responsible Use of Artificial Intelligence: Winter 2026 Issue of SciTech Magazine

by David Badertscher

SciTech Magazine is published by the Science and Technology Section of the American Bar Association.

INTRODUCTION:

The Winter 2026 issue of The SciTech Lawyer, published by the American Bar Association’s Science & Technology Law Section, arrives at a pivotal moment in the legal profession’s evolving relationship with artificial intelligence. Centered on the theme of responsible AI use, this issue explores how rapidly advancing technologies are reshaping legal practice while raising urgent ethical, regulatory, and professional responsibility concerns.

December 13, 2025

How Secure are Private Records Held by Major Credit Bureaus?

by David Badertscher

Introduction.

The “big three” credit reporting companies, TransUnion, Equifax, and Experian, hold highly sensitive consumer financial data that can affect people’s access to credit, housing, employment, and insurance. Their data security posture depends not only on resisting large-scale hacking events, but also on preventing “low-tech” account takeovers that exploit customer service processes.

This post is based on Shira Ovide’s article, “It Wasn’t Hard to Highjack Trans Union Credit Reports, I Did it Myself. published in Tech Friend , a publication of the The Washington Post on December 12. 2025. In her article, drawing on months of testing by the Public Interest Research Group (PIRG), Ovide describes a vulnerability in TransUnion’s customer service hotline that allegedly allowed callers, with minimal identity proof, to reset passwords and change account contact information, potentially enabling account takeover and unauthorized access to credit report details. TransUnion reported that it updated protocols after being contacted, and PIRG later found that additional verification was requested in most retests.

August 21, 2025

Building Your Technology Toolkit: What Law Librarians and Attorneys Can Learn from Unlocking the Future

by David Badertscher

A review of Unlocking the Future: Leveraging Technology for Personal and Professional Success, by Jeffrey M. Allen & Ashley Hallene (ABA Book Publishing 2025), 480 pp., ISBN 978-1-63905-629-3; e-book ISBN 978-1-63905-630-9; Senior Lawyers Division sponsor; list price $39.95.

The Book in Brief

In this book, Jeffrey Allen and Ashley Hallene aim to demystify fast-moving technologies for working professionals, especially lawyers, law librarians and others specializing in the law, by pairing plain-English explanations with practical checklists, tool rundowns, and risk-management advice. The American Bar Association positions the book as a comprehensive guide to “essential tools, AI, cybersecurity, [and] health tech,” organized into meticulously crafted chapters that double as a reference you can consult as needed. It runs 480 pages and is available in both print and e-book formats, with the Senior Lawyers Division serving as sponsor.¹ The ABA’s “New Books” listing shows a $39.95 list price.²

February 16, 2025

Potential Impacts of Government Efficiency Reforms Led by Elon Musk on U.S. Government Libraries

by David Badertscher

Introduction

Materials consulted in preparing this posting were curated from various sources including the recently introduced Deep Research by OpenAI.

With Elon Musk at the helm of the Department of Government Efficiency, various agencies within the U.S. government may experience restructuring aimed at streamlining operations, reducing costs, and integrating advanced technologies. One area likely to be affected is government agency libraries—institutions that provide critical research, archival, and information services to federal employees, policymakers, and researchers. These libraries, usually housed within agencies such as the Library of Congress, the National Archives, and the Department of Defense (DoD), play an essential role in supporting government functions. This essay explores how Musk’s efficiency-driven policies might reshape these libraries, with potential consequences for automation, digitization, data management, funding, privacy and information security. Although the focus of this posting is U.S. government libraries, its implications are far reaching.