Ethics and Authorship in AI-Driven Art: A Complex Intersection

AI doesn't have an ethics problem. Humanity does We're having the wrong conversation. The endless debates about "AI ethics" are a distraction. The real, uncomfortable truth is that we are not debating machine morality. We are engaged in a brutal, global negotiation over human values. Every time we argue about AI bias, we are really arguing about historical human bias, codified at scale. Every time we panic about AI taking jobs, we are confronting our own societal failure to define the value of human labor beyond economic output. Every time we fear an AI's decision in a self-driving car, we are forced to answer the Trolley Problem—a philosophical question we've elegantly avoided for centuries. The machine is merely a mirror. It is forcing us to look at ourselves. The core problem is this: We are attempting to encode a single, universal set of "ethics" into a technology that will be used by thousands of distinct cultures, each with its own nuanced, and often conflicting, moral frameworks. Whose ethics do we choose? 📍The Western individualistic model? 📍The Eastern collectivist model? 📍A committee-driven, corporate compromise? The result is a predictable mess. We get sanitized, lowest-common-denominator AIs that are terrified of causing offense but incapable of providing profound truth. We create systems that are "ethically" neutralized because we cannot agree on what "good" means. This is not a problem that more AI research can solve. This is a philosophical and political challenge of the highest order. We are being forced to do what we've never successfully done: explicitly define, in actionable code, the principles that should guide human civilization. The question is no longer "How do we make AI ethical?" The question is: "Which humanity are we building for?" Until we can answer that as a species, our most powerful AI will remain a reflection of our own deepest confusions. #AIethics #ArtificialIntelligence #Philosophy #Technology #Future #Society #HumanValues

EDP Sciences has updated its policy on artificial intelligence and ethics. It outlines responsible use of generative AI across the publishing cycle for authors, reviewers, and editors. Hope other publishers and societies follow suit. From my point of view, the updated policy reinforces a principle that should be universal: peer review has to remain a human-led process. https://lnkd.in/dJuR6A4u #ResponsibleAI #PeerReview #ResearchIntegrity #PublisherPolicy

AIF Insights No. 36 (2025) | Khmer Gatilok and Relational Ethics: A Cultural Lens for AI Morality This essay examines the Khmer ethical system of Gatilok as a culturally grounded framework for AI ethics. Unlike Western approaches that prioritize universal principles, Gatilok emphasizes relational, situational, and long-term moral reasoning rooted in Theravāda Buddhist concepts such as intention (cetanā), karma (kamma), and social harmony (sampheap). Through stories, proverbs, and oral traditions, Gatilok teaches that ethical behavior depends on context, relationships, and the consequences of actions over time. Applying these insights to AI governance highlights the importance of relational accountability, participatory oversight, culturally sensitive datasets, and long-term impact assessments. By integrating Gatilok into AI design and policy, this perspective encourages ethically aware, contextually appropriate, and culturally responsive AI systems that respect local values and foster social cohesion. https://lnkd.in/esTRW2fy

⭐ We’re excited to announce the launch of Cambridge Elements in AI Ethics and Society! Elements are short books (20,000-30,000 words), fully peer-reviewed but with a fast turnaround and good online and open options access. We are now accepting proposals! We are open to a wide range of methods, approaches and topics, as long as the work is making a significant and original contribution to the study of AI ethics, governance or social impact. Topics of interest include: -The social impact of AI in important sectors such as health and defence; -Insights from particular methodological approaches such as Confucianism and design theory; -Explanations of key topics such as fairness and explainability. Series Editors: Professor Stephen Cave (Cambridge) and Dr Kerry McInerney (Auckland). For more information, and to download a proposal form, follow this link: https://lnkd.in/e9z3eYU4

The Morality of AI Usually when we talk about AI ethics, we are talking about how we apply human ethics to the development and application of AI systems. To be clear from the start - that’s not what this article is about. We are going to explore something different – what ethicsl would we expect AI to spontaneously develop? If you’re reading this with a furrowed brow, relax, this article is not about doomsday scenarios of the emergence of world-dominating machine overlords. It is, rather, a muse on why AI will almost inevitably develop its own version of ethics, and how those ethics may evolve. Perhaps surprisingly we are going to find that AI’s moral development may be driven by analogous forces to those which have shaped human morality over the centuries. Read more here: https://lnkd.in/eGPyWPjA

📢 I'm happy to share the details of one of my ongoing projects: the Call for Chapters for the upcoming edited volume Engaging with AI in Business: A Virtue Ethics and Human-Centered Approach, to be published by Springer Nature as part of its Issues in Business Ethics series (2027). 🤖 The volume explores how virtue ethics and human-centered AI (HCAI) can guide responsible AI across key business domains — from finance and marketing to HR, governance, and production — aligning technology with human flourishing, organizational purpose, and the common good. 👥 Excited to co-edit this project with Miguel Velasco (CUNEF Universidad) and Jude Chua (Nanyang Technological University Singapore). Thanks to the Facultad de Económicas. Universidad de Navarra, DATAI-Universidad de Navarra, and the Universidad de Navarra for their support. 📚 More details and submission guidelines here: 👉 https://lnkd.in/dxjgVrkv 🌍 Colleagues and researchers interested in these questions are warmly invited to share the call within their networks or submit a proposal for consideration.

👩🏫 Professor Dulce M. Redín, faculty member at Facultad de Económicas. Universidad de Navarra and researcher at DATAI-Universidad de Navarra, is co-editing a new volume titled "Engaging with AI in Business: A Virtue Ethics and Human-Centered Approach", to be published by Springer Nature in 2027 as part of its Issues in Business Ethics series. 📚 Call for Chapters: The edited volume examines how virtue ethics and human-centered AI (HCAI) can guide responsible AI across core business domains. It welcomes chapter proposals that bridge theory and practice to align AI with human flourishing, organizational purpose, and the common good. 👏 👉 For more information 🔗 https://lnkd.in/dxjgVrkv 🔎 Current projects: https://lnkd.in/dqWDMF43

AI doesn’t misbehave because it’s bad. It misbehaves because it doesn’t understand us. It optimises what it can measure, not what we mean. After the LSE AI Ethics Programme, one truth stuck: the real challenge isn’t technical — it’s moral. We’ve written enough principles. Now we need systems that can interpret human intent. In my latest piece, I share: - Why alignment is about meaning, not metrics, and - 5 tools to embed moral meaning into your AI design process

Just attended the "Publishing with Purpose: Research Integrity & Ethics" webinar by Wiley, a really insightful session for anyone starting their research journey. Here are a few key takeaways that stood out to me: Generative AI can be useful for ideas or overcoming writer’s block, but it must be used ethically. It’s not a substitute for human writing, and its use should always be disclosed. Plagiarism is completely unethical and undermines the credibility of research. Authorship matters, only those who played a substantial, accountable role in the research should be listed as authors. Others can be acknowledged as contributors (with consent). Conflicts of interest should always be disclosed clearly and factually — transparency builds trust. Ethical peer review is the foundation of strong research publishing; it helps improve articles before they reach readers. Grateful for this session, it truly emphasized that integrity is just as important as innovation in research. 

When companies and researchers talk about "ethical AI" or "aligned AI," they're usually presenting it as if ethics were universal and obvious. Whose ethics are embedded in AI systems today?Primarily those of: The predominantly Western, educated developers building them The corporations funding development (with their profit motives and liability concerns) The regulatory environments they operate in (mostly US and EU frameworks) The specific groups who get to provide feedback during development Different cultures have genuinely different values. What counts as "harmful" content varies dramatically - political speech, religious criticism, discussions of sexuality, appropriate ways to address authority figures. Even concepts like privacy, individual vs. collective good, and what constitutes "fair" decision-making aren't universal. When someone says an AI should be "helpful, harmless, and honest," each of those terms requires judgment calls: Helpful for whom and for what purposes?Harmless by whose definition of harm? Honest in ways that align with which cultural communication norms? AI systems today largely reflect the values of those with resources to build them. When a company says their AI represents "broadly held values," they often mean "values we think are broadly held among people like us and won't get us sued." There is no "ethical AI." There's only "whose ethics got the most funding." #AIEthics #TechColonialism #WhoseEthics #AfricanTech #DigitalDecolonization