Lecture archive
The ‘Mercator Lectures for AI in the Human Context’ are organized as part of the ‘Desirable Digitalization: Rethinking AI for Just and Sustainable Futures’ research project, a collaboration between the Universities of Bonn and Cambridge, funded by Stiftung Mercator. In these lectures, the respective Mercator Visiting Professors give an insight into their work and current issues in the research of desirable AI and digitization.
Mercator Lectures for AI in the Human Context
Prof. Monojit Choudhury
Turing Test 2.0 — Reimagining the Goals of Artificial Intelligence in the Post-GenAI World (02.06.2026)
Since its inception, the Turing Test - the seemingly audacious vision of machines that speak with such fluency that they blur the boundary between human and artificial minds - has served as the north star of language understanding and AI. In the era of large language models, this vision feels tantalizingly close, yet increasingly hollow, as AI systems now routinely surpass humans not only in language-related tasks but across a variety of complex domains. This has led to a growing sense that we may be approaching, or have already glimpsed, the rise of Artificial General Intelligence (AGI) or even superintelligence. But this impression is misleading. Current systems excel at specific benchmarks, yet these tests often capture only narrow slices of what it means to truly understand language.
In this talk, Monojit Choudhury will argue that the real frontier lies elsewhere. Language is not a monolith but a living mosaic of individual voices, shaped by context, culture, and experience. To reduce it to a generic, averaged “human-like” performance is to miss its essence. He proposes a reframing, Turing Test 2.0, as the ability to model not an arbitrary human, but a specific individual. This shift echoes philosophical traditions that locate meaning in use, interaction, and lived reality. In doing so, it gestures toward a more ambitious and enduring vision: not merely to generate fluent text, but to engage with the human condition that language both reflects and constructs. Further he will argue that Turing Test 2.0 not only provides a theoretically grounded notion of generalization in machine learning, but also holds transformative potential for education, cognitive and psychological therapies, and social science research, among other domains.
Prof. Neda Atanasoski
AI Between Annihilation and Life (01.07.25)
This talk examines seemingly opposed perspectives surrounding Artificial General Intelligence (AGI): its framing as a "New Manhattan Project" driven by geopolitical competition and fears of annihilation, and its reinterpretation by some as an expansion of the definition of life itself. The presentation argues that both narratives, despite their apparent opposition, are deeply intertwined with and perpetuate racial capitalist and colonial relations. By tracing the historical legacy of the original Manhattan Project, including land appropriation and environmental devastation, the talk reveals how existing infrastructures are being repurposed for AI development, exacerbating energy consumption and climate concerns. Ultimately, the talk suggests that the push for AGI, whether for global supremacy or a redefinition of life, obscures ongoing exploitation and reinforces existing power structures, underscoring the need for alternative understandings of life and living.
Shoukei Matsumoto
Human Literacy in the Age of AI: Dissolving Anthropocentric Perspective through Buddhist-Posthuman Dialogue (16.06.2025)
As artificial intelligence increasingly shapes human experiences and interactions, our conventional anthropocentric perspective faces profound challenges. This lecture explores how Buddhist philosophy, particularly its non-dualistic view of life and interconnectedness, offers valuable insights for transcending human-centered thinking. By engaging in a dialogue between Buddhism and posthumanist perspectives, we can cultivate a new kind of human literacy—one that embraces coexistence and interdependence with AI and the broader ecological system.
Prof. Dr. Walther Ch. Zimmerli
ARTIFICIAL INTELLIGENCE - Hype or Myth? (15.04.2024)
Since Chat GPT we are witnessing another global AI hype. In his public Mercator-lecture Swiss philosopher Walther Ch. Zimmerli tries to unveil the hidden mechanism behind the undeniable success stories of AI by reconstructing its history of recurring hype cycles beginning with what he calls the „Dartmouth Conspiracy“ and Turing’s „rehabilitation of deception“. The underlying suggestive power of the idea of AI, however, must be attributed to its mythical character as is demonstrated both by contrasting the Gartner hype-cycle theory with the philosophy of myth (Blumenberg) and by semiotically explaining it in terms of analogies and metaphors as well as contrasting it with the Singularity- and the Posthumanism-Myth (Kurzweil).
Prof. Dr. Maurizio Ferraris
Webfare: Digital Equity (09.06.23)
Are We as consumers, as homo consumens qua homo valens, have become a source of a new kind of capital. Until recently the vast majority of human acts did not translate into capitalizable data. This new-found capital represents a new world heritage in a radical sense. Ontologically, it has nothing to do with common goods, which are part of nature. This is about culture and society. Epistemologically, it is a treasure trove of finally reliable knowledge about humankind. Economically, it is infinitely renewable capital, since one can use the data as often as one likes. Finally, from a political point of view, it is radically democratic, since it is produced in equal measure by the richest, most educated, poorest, and most uneducated human beings, provided they are connected to the Web. This capital does not differentiate between rich and poor, because even those who have no money at all
(provided they are connected) generate data in abundance. Instead of being a sign of the divine election of the individual, as in the Calvinist origin of bourgeois capitalism, this new humanistic capital is only valuable insofar as it is shared among all humans, regardless of wealth, intelligence, race or faith. So far, the two options to regulate the environment in which this capital is produced have been either to privatize or to collectivize the data economy.
As part of his lecture, Prof. Dr. Maurizio Ferraris discusses a third humanistic option for a future data market that allows not only equality but true equity: Webfare as a redistribution of capital.
Prof. Dr. Jocelyn Maclure
AI Ethics: A Deflationary yet Cautionary View (15.05.23)
Recent advances in AI research and development are raising a host of difficult ethical questions related to the impacts of AI technologies on human life. Although the project of building “moral machines” is not new, AI Ethics is now a vibrant field of research and public policy. One could hardly be blamed for being bewildered by the state of the public discussion on AI. Maclure defends what he calls a deflationary view about the future development of AI and the moral status of advanced AI systems. Maclures view is nonetheless cautionary because the narrow and limited machine learning algorithms that we currently have are already wreaking havoc in some crucial spheres of human life and disrupting established social practices; think, for instance, of generative AI such as ChatGPT. He shows that AI ethics, done properly, has the conceptual resources to help us move beyond the lofty realm of principles and contribute to the judicious regulation of AI technologies.
Prof. Dr. Olivia Erdélyi
Regulating Artificial Intelligence: A True Team Effort (04.11.2022)
Artificial intelligence increasingly determines our everyday life. In order to do justice to AI technologies and their regulation, it is necessary to look at legal, economic, social and anthropological contexts in equal measure. Dr. Olivia Erdélyi, in her talk on "Regulating Artificial Intelligence: A True Team Effort", addresses the question of the importance of interdisciplinary and multi-stakeholder cooperation in AI regulation. Her talk focuses on the following questions: which demands and desires clash in the development and implementation of AI regulation? How can communication between disciplines and between different stakeholders succeed? What is the role of international cooperation and transnational consistency? How straightforward is the practical implementation of AI regulatory requirements? In these and other questions, AI does not stand alone but is one of many examples in the history of technological innovation and its impact on our society. Only when AI technologies are understood as a nexus of different perspectives can we adequately address its challenges.