Both law and computation have been permeating our private and professional lives: the law has done so for thousands of years already by determining the social and economic structures in which we interact, while in comparison, digitalization only much more recently has been transforming our societal fabric. Understanding how the law can enable or constrain innovation within the broad domain of computation or digitalization is central for developers and engineers to determine how to shape future, responsible computing as well as regulatory environments. Within this course, we will analyze the regulatory toolkit at the disposition of policymakers and map legislations that emerged in Switzerland, Europe, and selected jurisdictions across the globe. We will analyze how the field of digital law has shifted over the years, more recently with a focus on data-driven computing and machine learning, and aiming to achieve trustworthy AI. We will critically reflect on the shortcomings of current legislation and envisage new approaches to address new risks that an ever-artificially intelligent world entails. This opens up the discussion to newer approaches and domains of law, that are focused on how computation and design can improve legal processes and access to law and justice. These new approaches are situated within the field of regulatory innovation, legal design, and computational law and combine the expertise of computer scientists, human-computer interaction designers, and legal scholars and are often driven by the quest to leverage interdisciplinary know-how to create more accessible legal processes.<\/p>\n\n\n\n
Artificial intelligence has been a critical topic on policymakers’ agenda: From the AI Act in the European Union to the Executive Order on AI in the US to the Bletchley Declaration on AI Safety worldwide, we are starting to determine how to approach the complex topic of AI. In Switzerland, there are also debates on how to regulate the risks of AI. We need to align our approach with European and global strategies to ensure AI development and deployment that benefits society in the long term. In this course, we look into AI governance by first understanding what AI technologies can do and the associated risks and second analyzing the regulatory landscape and legislation or international agreements that have emerged in recent years. We will look at concrete sectors and examples of how AI is being deployed and discuss how principles and guidelines can be applied within those sectors.<\/p>\n\n\n\n
With the increasing adoption of AI technologies in organisational processes, a strong understanding of the risks and opportunities and the applicable regulations is needed more than ever. Regulations such as the EU AI Act oblige private and public providers and deployers of AI systems to ensure a sufficient level of AI knowledge and skills (so-called AI literacy) among their staff and third parties dealing with the operation and use of AI systems on their behalf. In this intensive course you will learn and discuss questions such as: what are the practical implications of the AI Act in Europe and in Switzerland? How can AI technologies be evaluated and managed in compliance with new regulations? And how to develop AI literacy training programs and internal guidelines within your organisation?<\/p>\n\n\n\n