Universal Values in AI Ethics—Rethinking Ethics in a Global AI Age

When we talk about “universal values” in AI ethics—privacy, explainability, and fairness—we speak of these values as if they transcend culture, history, and epistemology. In his latest work, Philosopher Soraj Hongladarom challenges us to rethink this idea in a new way:

Instead of thinking these values are true because of deep moral ideas, he argues that universal values are shared because people around the world will face similar real-life problems when using AI due to global entanglement.

Put simply: The core problems of AI—opacity, bias, surveillance—are shared, even if the cultural framing differs. Universal values are a shared response to global entanglement.

• TL/DR: Global entanglement means that AI connects people, systems, and cultures in ways that make their problems—and solutions—interdependent. Because we all use similar tools and face similar risks, like algorithmic bias or data misuse, we end up needing shared ethical values, even if our cultures are different.

Why Interdependence Matters

• A gap exists in literature on non-Western approaches to ethics.

• It invites ethical pluralism without ethical relativism —> We can respect and include many cultural perspectives on ethics (ethical pluralism) without saying that every viewpoint is equally valid or beyond critique (ethical relativism)

• It asks us to stop projecting Western intellectual inheritance as default and start building dialogue instead.

Jung might say: we’ve long mistaken the mask (persona) of ethical objectivity for the deeper archetypal truth—our interconnectedness, our dependency, our mutual becoming. Ethics, too, must individuate.

Let’s not just ask: what values are universal?
But rather: what kind of universality do we want?

3 Key Takeaways

• “Ethical principles arise as a result of the actual working of the technological system rather than arrived at through rational thought alone.”

• “Privacy, explainability, or lack of bias are principles that are deeply connected with how machine learning AI works.”

• “Universality... is not a metaphysical truth... but the result of a practical agreement or negotiation among various stakeholders.”

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Stay on the Edge: 3 Cutting-Edge Reads

• “Data Sovereignty and the Postcolonial Cloud” – Kate Crawford (2024, forthcoming)

• “Relational AI: From Autonomous Systems to Entangled Agents” – Abeba Birhane & Philip Agre (2023)

• “The Buddhist Trolley Problem” – AI & Consciousness Studies (2024)

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References

Hongladarom, S. (2024). Universal values in AI ethics. In L. Checketts & B. S. B. Chan (Eds.), Social and Ethical Considerations of AI in East Asia and Beyond (pp. 179–191). Springer. https://doi.org/10.1007/978-3-031-77857-5_11

Jobin, A., Ienca, M., & Vayena, E. (2019). The global landscape of AI ethics guidelines. Nature Machine Intelligence, 1(9), 389–399. https://doi.org/10.1038/s42256-019-0088-2

Hongladarom, S., & Bandasak, J. (2023). Non-western AI ethics guidelines: Implications for intercultural ethics of technology. AI & Society. https://doi.org/10.1007/s00146-023-01665-6