Christopher Law publishes dissertation on ethical AI hiring in financial services

Christopher Law has released an open-access dissertation that lays out a framework for judging when AI should assist hiring decisions and when human judgment should stay in charge. The research, completed at Muskingum University and available through OhioLINK, targets leaders in financial services but is positioned as relevant to other high-stakes workplace decisions.

Why it matters: - The dissertation tackles a growing management problem: how to assign AI a role in hiring without losing accountability for the final decision. - The framework is meant to help leaders evaluate whether AI should assist, support, or automate parts of a hiring process. - The research is open-access, making the model available to practitioners, students and other researchers through OhioLINK.

What happened: - Christopher Law published his doctoral dissertation, Authentic Intelligence: An Ethical Framework for AI Hiring in Financial Services. - The dissertation was completed at Muskingum University and successfully defended in September 2026. - The work is available through OhioLINK’s Electronic Theses and Dissertations Center. - Law is a financial services and technology leader and the author of the forthcoming book Authentic Intelligence: A Leader’s Guide to Ethical AI.

The details: - The dissertation introduces the Authentic Intelligence Model, or AIM, as a framework for evaluating AI decisions through rights, reasons and results. - AIM considers responsibilities at the individual, professional and institutional levels. - The model is designed to connect ethical principles to decisions about adoption, oversight and accountability. - Law said the goal was to give leaders a practical way to decide what AI should be allowed to determine, what needs human judgment and what they should be able to explain to affected people. - AIM separates administrative assistance, decision support and decision automation. - The framework asks whether a system narrows a person's options or replaces that person's judgment. - It also addresses vendor governance and documentation. - Possible outcomes under AIM include proceeding under defined conditions, redesigning a use case or declining it. - The dissertation focuses on hiring in financial services, but it is intended to raise questions for other consequential organizational decisions as well. - The research presents an ethical decision framework and does not claim that using the framework guarantees fair outcomes. - Law's website offers public AIM resources and a free experimental companion called Ask Authentic Intelligence for exploring ethical AI dilemmas. - More information is available in the dissertation and related resources.

Between the lines: - The timing reflects rising pressure on employers to explain how AI systems influence high-stakes choices that affect applicants and workers. - AIM pushes leaders to treat AI adoption as a governance issue, not just a technology purchase. - The emphasis on documentation and vendor oversight suggests the framework is aimed at real-world organizational controls, not abstract ethics alone.

What's next: - Law's forthcoming book is set to expand the discussion to a broader leadership audience. - The public AIM resources and experimental companion tool give readers a way to test the framework against real ethical scenarios. - The dissertation's broader use will likely depend on whether leaders adopt it as a decision tool for hiring and other sensitive AI uses.

The bottom line: - Law's dissertation offers a structured way to decide where AI can help in hiring and where human judgment should remain central.