AI Ethics: A Comprehensive Research-Based Framework

AI systems are making consequential decisions about credit, hiring, healthcare, and criminal justice. Most organizations have no systematic framework for ensuring those decisions are fair, accountable, or transparent. This report builds that framework from the research up.

Not philosophy. Not compliance theater. A rigorous, evidence-based examination of the AI ethics questions that actually determine whether AI deployment goes well or badly for the people affected by it.

What's inside

• The Kellette Ethics Gap Analysis: a framework for measuring the distance between stated AI values and actual AI decisions in your organization
• The Accountability Void: Kellette's mapping of where responsibility disappears in AI systems and how to fill the gap
• A taxonomy of AI bias with documented case studies: historical bias, representation bias, measurement bias, aggregation bias, deployment bias
• The Gender Shades study and its implications: 42x error rate differences in facial recognition across demographic groups
• The EU AI Act explained: what it requires, who it applies to, and what non-compliance costs (up to 7% of global annual revenue)
• The US regulatory patchwork: CFPB, FTC, FDA, EEOC, and what they mean for AI deployment in your sector
• A four-question organizational framework that any business leader can apply to any AI decision

Who this is for

Business leaders, technology executives, legal and compliance professionals, and anyone making decisions about AI deployment who wants a rigorous framework rather than a vague commitment to responsible AI.

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