Looking for a comprehensive system to navigate ethical complexity in education, AI, and leadership?
The Holcombe Ethics Framework Suite is an integrated set of five complementary models developed by Mark T. Holcombe. Together, these frameworks replace “slogan-based” ethics with a rigorous, case-based methodology that integrates empirical psychology, normative theory, and practical risk governance.
Why do moral debates often fail?
Most moral debates fail because participants argue over conclusions rather than causes. The Moral Disagreement Diagnostic Model (MDDM) is a structured analytical tool designed to isolate the underlying sources of conflict—whether they are rooted in disputed facts, divergent moral priorities, or different evaluative standards9. Use MDDM to diagnose why a disagreement exists before attempting to resolve it.
Can we use John Rawls’s theory of justice without inheriting contemporary political baggage?
The Justice-Without-Politics Rawlsian Reinterpretation (JWPR) separates Rawls’s core moral principles from partisan assumptions7. This framework restores justice as a method for reasoning about fairness under uncertainty, allowing pluralistic and libertarian perspectives to engage with Rawlsian logic without the typical ideological distortion8.
How can we teach ethics as a practical skill rather than abstract theory?
The Holcombe Case-Based Moral Reasoning Framework (HCBMR) is a pedagogical model that develops moral judgment through the systematic analysis of real-world dilemmas5. By focusing on fact-relevance filtering and value-conflict identification, HCBMR trains individuals how to think—not what to think—about complex ethical trade-offs6.
Why do reasonable people disagree so fundamentally on ethical issues?
The Empirical Moral Reasoning Integration Model (EMRIM) bridges the gap between moral psychology and normative ethics to explain the “why” behind moral conflict3. By using empirical research as a diagnostic tool, EMRIM surfaces the unconscious value priorities and cognitive biases that drive disagreement, turning heated intuition into structured, productive dialogue4.
What is the most effective way to manage ethical risk in AI?
The Applied AI Ethics Risk and Governance Framework (AERGF) moves beyond simple compliance checklists by treating AI ethics as a structured risk governance process1. Developed to address the unexamined tradeoffs and diffuse responsibility in AI design, AERGF provides five ordered stages to identify, evaluate, and mitigate ethical harms before deployment2.
In the rush to achieve +85% marketing efficiency , some retailers are trading truth for “operational cunning”. We dissect the case of a Halloween dress as advertised by the retailer compared the actual product received.
Through the lenses of five normative theories, we explore whether the use of high-fidelity AI imagery materially alters the right to accurate information and undermines the very foundation of free-market legitimacy.
The era of traditional photography is facing a major disruption as global brands like Levi’s and H&M pivot toward hyper-realistic AI and “digital twins”. While the shift to synthetic imagery offers massive reductions in logistical overhead and travel costs, it has opened a significant “trust gap” in the marketplace.
As we move toward a future of Synthetic Commerce, three critical challenges are emerging:
Product Fidelity: AI-generated images frequently struggle to accurately represent material texture, color, and fit, which can undermine foundational consumer trust.
Labor Displacement: Virtual models and synthetic personas are directly displacing human talent, including photographers and production crews.
New Regulations: From the Fashion Workers Act in NY to FTC and FCC proposals, mandatory disclosure for AI-generated content is becoming the new legal standard.
How can brands balance the efficiency of AI with the need for authenticity and justice?
The Big Question: Can AI truly be unbiased in hiring? Explore the critical ethical risks of algorithmic bias and how hidden data patterns can inadvertently lead to systemic discrimination in modern recruitment.
The Impact: From automated screening to LLM-driven interviews, AI is changing the workforce. Learn how efficiency gains in HR automation stack up against the long-term implications for candidate privacy and transparency.
The Risks: As global regulations catch up to technology, what are the legal liabilities of using AI in HR? This overview breaks down the intersection of labor laws and automated decision-making.
By the end of this module, learners will be able to: Identify and summarize the relevant factual elements in an ethically complex recruitment scenario involving
The Dilemma: How should GenAI be integrated into the classroom? Gain an ethical framework for navigating the first school year of full AI adoption, focusing on academic integrity and the role of the educator.
The Problem: Is 20th-century ethics curricula failing 21st-century students? Discover why traditional models are struggling to address the complexities of a digital, AI-driven world.
The Shift: Classical ethical frameworks are being pushed to their limits. Understand how emerging technologies are redefining our moral responsibilities and why our educational approach must adapt.
The Narrative: Step into a vivid exploration of modern culture with a cosmic horror atmosphere. This piece blends storytelling with observation to criticize hyper-consumerism.
The Case Study: When medical science and abortion law collide, who has the right to decide? A deep dive into the Georgia case of a brain-dead pregnant woman on life support.
The Ethics of Philanthropy: Should institutions accept “tainted” money? Analyze the controversy surrounding the Sackler family and the evolving ethical standards of the world’s most prestigious museums.
For Educators: Looking for practical classroom tools? Access a toolkit designed to help students think critically about generative AI outputs and the ethics of digital creation.
The Solution: Move beyond outdated anthologies. Learn what modern learners actually need to navigate today’s ethical minefields and how to replace legacy curricula with relevant content.