In the world of technology, thousands, millions or - in the case of the new large language models - billions of variables are often optimized in parameter spaces. In contrast, our society is the result of a centuries-long power struggle between sometimes incompatible and sometimes complementary principles. These relatively few principles, including the fundamental rights of freedom, equality, justice, human dignity and self-determination, by their very nature cannot all be realized simultaneously, nor can there be an appropriate, lasting balance between them. Rather, Western democracies, through the rule of law, separation of powers and within democratic systems, are in a constant balancing process that becomes a solution through the process itself. This process requires participation, deliberation and autonomy on an individual, group, and societal level. In this talk, we will look at the potential impact that algorithmic decision-making and new AI-supported processes, especially from the field of generative AI, can have on human thought and action and what this can mean for the basic principles of Western democracies.

This lecture explores the intersection of digitalization and sustainability in environmental monitoring. It begins with an introduction to the possibilities of environmental monitoring on the ground, highlighting its importance and impact and presenting networks such as LTER and GLEON as well as a concrete example of an ecological monitoring program at Lunzersee. This is followed by an in-depth look at the digitalization of environmental monitoring, covering key technologies, citizen science initiatives, sustainable computing practices, and case studies such as the SWAIN Project. The session concludes with a discussion on bridging the gap between information technology and environmental science, addressing interdisciplinary approaches, ethical considerations, and strategies for effective collaboration.

Digital Identity Systems are on the rise worldwide. While global majority countries already have ample experience with their pitfalls and human rights implications, Europe just concluded its big digital identity reform without any concern for the experiences of other regions. Thomas Lohninger works for Austrias biggest digital rights NGO epicenter.works and has shaped the 2,5 year negotiations for the new EU law. This presentation will showcase realistic use-cases of the technology from age verification, online identification, customer tracking up to replacing CAPTCHAs. We will discuss essentials safeguards that attempt to make such systems of government certified personal data exchanges less dangerous in a world of surveillance capitalism and rising authoritarianism.

The speaker lead the NGO coalition of privacy watchdogs that advocated for strong human rights safeguards in the EU legislation. He since became Chair of the UN DPI-safeguards Governance Working Group, advices the EU Commission on the technical specification of the new system, is in the Jury of the German government about their Wallet implementation. This talk tries to bridge the technical, legal and social implications of such systems and how society might be shaped by what some are calling the operating system of modern society.

Recent advances in Artificial Intelligence are nothing short of a revolution in computing technologies. They have become triggers of significant innovation opportunities that many entrepreneurs seek to explore and exploit for commercial success. AI poses enormous challenges regarding the ethical design of these innovations, both at the level of the individual and regarding their impact on society. In my presentation, I review calls for ethical AI and the challenges they pose for the entrepreneur. We take a closer look at AI principles that have been proposed to address the problem of ethical AI systems. While laudable, principles suffer from a lack of operational practicability. I present ways to address some of the issues systematically and discuss how to learn from the examples of other high-risk industry such as pharmaceutics, aeronautics, or medicine that successfully established practices of managing significant and residual risks.

The digital economy has been the focus of the most intense scrutiny in the competition law context in recent years, by both scholars and enforcers. Unilateral conduct by the ‘tech giants’ is the most acute area of interest: with claims being made both for a more aggressive/innovative application of the existing competition rules and for a need for revision or augmentation of the current legal framework to address pressing problems that lie outside its boundaries. In this lecture, we will discuss, first, the distinctive dynamics of digital economy markets; second, a number of theories of harm that have arisen with frequency in this context; and third, various forms of platform regulation (DMA, DMCCA) that are aimed at providing a complementary regulatory framework for Big Tech companies. These new regulatory instruments are clearly modelled on but also going beyond the existing scope of Article 102. Many of the cases we will discuss lie at the ‘frontier’ of competition enforcement. Hence it is worth considering whether they represent the necessary evolution of competition law in its attempt to address competition issues within the digital economy – or, conversely, whether they might represent an overreaching by competition enforcers, with potentially problematic consequences in the longer term. In such circumstances, is legislation preferable, and even inevitable? What form should this legislation should it take and how it should complement competition law?

In the first part of the lecture, basic concepts and methods of machine learning are introduced with a focus on image classification and generative approaches. Typical misconceptions and pitfalls of data driven AI methods are illustrated and discussed. In the second part of the lecture, specific approaches for trustworthy AI are introduced with a focus on explainable AI methods, making use of knowledge to guide model induction and adaptation, and human-in-the-loop approaches.