George Metakides plans to introduce a “democracy leitmotif”, detail abstract is forthcoming.

P in RLHF. Reinforcement learning from human feedback has emerged as one of the primary mechanisms for aligning large language models. In this framework, (human) workers report their preferences over possible responses to a query, and their reports are used to fine-tune the model. This process collects feedback from multiple raters, and therefore implicitly aggregates the raters' preferences. In this tutorial, we will discuss voting methods that underpin popular RLHF approaches, and investigate whether tools of social choice can be used to design better fine-tuning procedures.

Excursion to the Austrian Parliament.

Groups of 4-5 students select one of several use cases.

Planned reception at the City Hall of Vienna.

Abstract forthcoming

Abstract: Inspired by the political trilemma of the world economy that Dani Rodrik put forward about 20 years ago, this lecture explores a modified trilemma for the age of AI: geopolitics, democracy, and tech-driven economics are fundamentally incompatible. Is it true that, at best, we can have two but not three? The lecture first explores the underlying thinking from a structural perspective. We will then, interactively with the students, explore public policy options if we want to ensure that democracy is not the one left out.

Political communication is how political actors (such as political parties and governments), media/journalists, and citizens create and exchange messages about politics. AI is rapidly transforming this process through data-driven, emotionally targeted communication, offering new opportunities for engagement while raising risks of manipulation, polarization, and fragmented public discourse. This lecture connects empirical insights from political and communication research with the principles of Digital Humanism, asking how democratic politics can effectively communicate in the age of AI.

Reserved time to work on your students projects and the presenation on Friday afternoon.

Information fortcoming

Abstract forthcoming

Abstract forthcoming

Abstract forthcoming

The ongoing process of digitalization makes the realization of a fully direct democracy—one in which all political decisions are made directly by the people—appear increasingly feasible, even in large and populous states. This might suggest that majority decisions, determined through general, direct, free, equal, and secret elections and referenda, constitute the sole defining feature of democratic decision-making. However, democracy is more than majority rule. This talk explores what democracy presupposes beyond voting procedures. Democracy entails human rights, the separation of powers, and the role of expert consultation, which must not be undermined by digital participation tools. It also requires cooperation: it cannot function if a minority defeated in a vote obstructs the implementation of the decision made by the majority or if citizens act solely as self-interest-maximizing agents. Moreover, in a democracy, political debates cannot be reduced to the assertion of the interests of various lobby and interest groups, but also involve the articulation of political positions put forward with a claim to truth (while remaining open to the possibility of error). Finally, from a philosophical perspective, the freedom and equality of citizens constitute normative preconditions of democracy.

Very honored to lecture at the 5th ACM Europe Digital Humanism Summer School, I propose to divide my lecture into three parts under the general rubric of foundational issues.

My specific AI-related interest and expertise is twofold: the impact of generative AI in several aspects of the legal field and secondly, honing in on the cultural field, the challenges faced by performing artists in the wake of AI.

Further, if lecture time allows, I would welcome the chance to delve into several case studies related to AI: the Anthropic-US Pentagon fallout and recent member state rulings concerning Deliveroo and other platforms accused of worker exploitation and the Streamz case.

Abstract forthcoming

A common critique of AI systems is their reduced transparency (“black boxes"), which often raises a critical challenge for ensuring that they function in a principled and fair way while complying with legal regulations. To address this issue we work on representing the internal structure of AI systems in detail. Additionally, we develop methods and tools for Auditing AI systems for several criteria, including some of those listed as requirements by the EU AI Act. An important question remains how input from social science (e.g., philosophy) can be infused in our work as part of the broader area of Digital Humanism

AI systems increasingly affect society, yet questions of democratic control remain largely unresolved. At present, many consequential choices in the development of AI systems — from data collection to deployment — are made by a small number of decision-makers, with little public input or oversight. Current debates on democratic AI governance tend to focus on institutional and regulatory frameworks at the macro level. In this talk, I complement this perspective with an approach grounded in social choice theory, the mathematical study of how conflicting preferences can be aggregated into collective decisions. I argue that opportunities for meaningful collective input arise at many stages of the machine learning development pipeline, yet are rarely recognised as such. Social choice theory provides both a modelling language to make these decision points explicit and principled criteria - drawing on notions such as fair representation, participation, and efficiency - to evaluate mechanisms for incorporating collective input. The talk aims to provide an accessible introduction to social choice theory in the context of AI governance, requiring no prior background in either area.

Project Presentations