Blog: AI Ethics for Business Leaders

Post #9: How Bioethics Can Inform Ethical AI Governance

As the global AI community grapples with the task of crafting practical operating models for AI governance, there is a need for new applied frameworks that adapt learnings from other domains where ethics has been successfully incorporated. Bioethics offers the most compelling example of such a domain.     

In this week’s essay, we explore the core discipline of Bioethics and consider the lessons we can glean from its history, principles, and practical applications within the field. Our aim is to extrapolate the established frameworks of Bioethics to...

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Post #8: Into the Abyss: Examining AI Failures and Lessons Learned

Amidst the dynamic integration of Artificial Intelligence (AI) across diverse sectors, instances of AI initiatives veering off course serve as poignant reminders (and cautionary tales) of the practical perils of AI development and deployment. These episodes underscore the multifaceted risks associated with AI integration and help frame conversations on the societal implications of AI-driven technologies in more practical terms. By examining these cases of AI misalignment, we unearth invaluable insights into the immediate ramifications that accompany the integration of AI into our lives....

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Post #7: The External Forces Influencing Business AI Governance 

This essay outlines the external forces influencing the responsible and ethical design, development, and deployment of AI systems by businesses. Companies are moving fast to launch generative AI applications to remain competitive in their fields and produce innovations relevant to their customers and other key stakeholders. AI-fueled transformation is happening across all sectors at breakneck speed, with new applications outpacing associated governance protocols. As discussed in previous essays, AI is an incredibly powerful technology that yields risks that can be material for both the...

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Post #6: The Caremark Rule and Board Level AI Risk Management 

In a previous essay, we outlined the relatively sparse legal and regulatory global landscape for AI as driven by government/policymakers as key stakeholders. We noted in this previous piece that the Caremark standard governs board oversight of company risks, with direct implications for a company’s AI program. See In re Caremark Intern, Inc. Derivative Litigation 698 A.2d 959 (1996). We contended that the principles enunciated in Caremark have far-reaching implications for a US board. 

In this essay, we further examine the Caremark rule...

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Post #5: Reimagining AI Ethics, Moving Beyond Principles to Organizational Values

It’s difficult to find an organization that hasn’t publicly stated its adherence to some externally formulated set of AI principles. As Emre Kazim and Adriano Soares Koshiyama highlight in their insightful piece, “A High-Level Overview of AI Ethics, in 2020 a mere 80 organizations across academia, NGOs, civil society, and commercial sectors had issued statements affirming their adherence to these external principles. (Special acknowledgement to Kazim and Koshiyama for their persuasive work, which has deeply influenced the ideas presented in this essay). With the explosion of generative AI experimentation and adoption, there are now hundreds, if not thousands, of organizations embracing this principles-based approach to steer their AI endeavors.... Read more about Post #5: Reimagining AI Ethics, Moving Beyond Principles to Organizational Values

Post #4: The State of Global AI Regulation

In our previous blog post, we highlighted the primary stakeholders across the AI governance landscape, the unique roles they play in shaping the collective global response to AI risks, and the areas of misalignment (and material gaps) that exist in their architecture and approaches.   

In this post, we set forth the contextual legal framework driven by the government as a primary stakeholder. As we suggest, extant laws are inadequate. In nearly all instances, they were not designed to govern many of the new realities arising from AI's ubiquitous uptake. This gap between existing laws and decision-makers' need for clarity both motivates and necessitates our research.... Read more about Post #4: The State of Global AI Regulation

Post #3 The AI Ethics Landscape: Government, Academia, and Business Approaches

In our previous blog posts, we have explored the urgency and critical importance of developing an applied (practical) AI ethics framework for business. We are motivated by our mission to design, develop, and deploy an applied ethical framework for the business use of AI. In designing this framework—as a more pragmatic response to the unique ethical challenges presented by AI—we need to first examine current practices and identify what works and, importantly, what is missing.  

The ethical use of AI in the business community is a multifaceted challenge that involves...

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Post #2: Why We're Embarking on This Business AI Ethics Journey

Welcome back to our Business AI Ethics blog! In our inaugural entry, we explored the significance of AI systems across today's business landscape. Jeff took the pen for today’s entry – en route home from an exhilarating session with a Fortune 50 company’s Risk team. There, we investigated the paramount importance of adopting an Applied AI Ethics approach. This encounter underscored not only the critical nature of our work but also the glaring gap in the world for an effective AI ethics framework tailored to business leaders.  

Today, let’s dive into the heart of the...

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Post #1: Applied AI Ethics for Corporate Leaders

Artificial Intelligence (AI) is no longer merely a science fiction motif - it is quickly becoming an everyday reality. As AI systems continue to reshape the contours of innovative possibility, integration of AI (generative AI in particular) into corporate strategies and decision-making is imperative for companies striving to stay competitive in a complex global landscape. 

Generative AI will revolutionize business, enhance products and operational efficiencies, and unlock new business models for growth. As we navigate the AI [r]evolution, there is a need to balance AI’s...

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