The research behind Authentic Intelligence

What question does the dissertation address?

Financial institutions can use AI to process applications, rank candidates, and support hiring decisions. The ethical question begins before asking how to optimize those systems: should AI perform the proposed role in the first place?

The dissertation examines the obligations owed to applicants and other stakeholders when hiring is mediated by AI. It argues that permission to use a system depends on protections and governance that an organization can actually maintain, including when a vendor controls important parts of the process.

What is the research method?

The study uses qualitative document analysis to synthesize scholarship, standards, and policy materials. Its primary contribution is a normative, conceptual argument grounded in moral philosophy. Deontological ethics supports threshold duties; consequentialist reasoning informs lifecycle effects and monitoring; virtue and care ethics illuminate moral agency and responsibility.

Responsible leadership extends attention to stakeholders beyond the immediate hiring transaction. Authentic leadership contributes a discipline of self-awareness, transparency, balanced consideration of evidence, and an internalized moral perspective when leaders implement AI-shaped decisions.

What does the research contribute?

The Authentic Intelligence Model organizes the argument into Gate 0, the Triangle, and the Orbit. Gate 0 addresses permission to use AI. The Triangle evaluates applicant, hiring manager, and institution-community relationships through Rights, Reasons, and Results. The Orbit considers broader institutional, workforce, security, environmental, and community effects.

Vendor governance is a condition running across the model. Decision records, scorecards, appeal pathways, and monitoring thresholds show how the ethical argument can become reviewable leadership practice. Vignettes and a documentary case analysis illustrate the model’s use.

What are its limits?

The dissertation does not claim statistical generalizability or report proprietary internal audits of a financial institution’s hiring system. Its conclusions depend on the scope and quality of the public materials analyzed. Its examples demonstrate theoretical operationalization, rather than empirical proof that a scorecard produces ethical outcomes.

AIM also assumes a willingness to treat affected people as persons with moral standing. A framework can make missing safeguards visible; it cannot supply ethical commitment where leaders refuse it.

How does the research relate to the book?

Authentic Intelligence: A Leader’s Guide to Ethical AI, planned for January 2027, brings the research into a practical leadership context and extends its questions beyond hiring. The dissertation offers the academic argument; the book and free companion workbook help teams work through decisions and document their responsibilities.

Additional papers

Explore the qualifying-exam papers and white paper shared on Christopher Law’s LinkedIn profile. These works are distinct from the published dissertation. The PDF copies preserve the pages shared on LinkedIn.

Ask Authentic Intelligence can help you explore the summaries and compare their themes.