17 October 2019, Statenzaal Maastricht University

On 17 October, a conference will be organized on "The Future of AI in Law", and on 18 October we will host an Oxford Union-style debate on the meaning of intelligence, humans and machines.

The conference will start with an overview of the history of AI and Law in legal publications: which topics have been discussed in the field of AI in Law? This introduction is followed by presentations, which are guided by four questions:

Panel 1. What can AI mean for the Law?
Panel 2: How to conduct AI in Law research?
Panel 3: Case studies beyond case law
Panel 4: Value-driven AI in Law research

Presenters will use their research on prediction, text mining, machine learning, and legal forecasting to illustrate what AI in Law research can mean, what the potential is, and what are the limitations of AI in Law research. The examples will be about court cases (Panel 2) as well as other application domains (Panel 3), for example consumer protection and law enforcement. Ethical aspects and fair algorithmic decision making will be discussed from a computational perspective.

The Keynote will address re-identification in datasets. In a recent publication, it was found that 99.98% of Americans would be correctly re-identified in any dataset using 15 demographic attributes. The results raise questions whether GDPR requirements can be met and seriously challenge the technical and legal adequacy of de-identification.

The conference features an All-Star lineup, which includes presenters who have published in Nature and who are ERC grant recipients.

At Maastricht University, the Lab works closely with the European Center for Privacy and Cybersecurity, the Department of Knowledge Engineering, the Institute of Data Science and Studio Europa (Maastricht Working on Europe), in promoting a European agenda of doing innovative research and education, as well as developing computer infrastructure.

18 October 2019, Sint Janskerk, Maastricht

Moderator: Gijs van Dijck
Team FOR: Jaap Hage/Kody Moodley
Team AGAINST: Willem Loof/Sally Wyatt

In the summer of 1956, American computer scientist John McCarthy organised the Dartmouth Conference, at which the term ‘Artificial Intelligence’ (AI) was coined. The researchers of the day were confident that it would only take a generation for AI to become reality. This initial enthusiasm faded away when it became clear that a mountain of obstacles guarded the way towards machine intelligence. However, in the last decades, AI has exploded. The current state of AI is such that it can analyse large amounts of disorganised images, documents, numbers and words at an astonishing speed and it has led to a number of breakthrough technologies.

In 2011, IBM’s Watson competed on ‘Jeopardy!’ against legendary champions Brad Rutter and Ken Jennings, and won; self-driving cars are now closer than ever to becoming fully operational; just last year, an AI-generated portrait has been sold for over $400.000 at an art auction; in Estonia, a ‘robot judge’ is being designed to settle small claims disputes. Computers thus seem increasingly capable of performing tasks that normally require human intelligence with less and less supervision, and a 2017 McKinsey report on the effects of automation on jobs, skills and wages for the period ending in 2030 even estimated that 50% of current work activities are technically automatable by adapting currently demonstrated technologies.

In this context, regulators everywhere are trying to take charge of the wave of change in order to ensure its constructiveness. In April 2018, the European Commission published a European Strategy on Artificial Intelligence, which sets out to, among others, prepare the society for socio-economic changes brought about by AI, and the new president of the Commission is prioritizing artificial intelligence on the European public policy agenda.

What are the concerns related to using AI in society? Are fears of AI ‘taking over’ justified? Are we on the verge of ‘general AI’ - the intelligence of a machine that has the capacity to understand or learn any intellectual task that a human being can? Or, rather, are some traits irreducibly human?

Join the debate organised by the Maastricht Law & Tech Lab, Studio Europa and Ambassador Lectures and find out what AI can(not) and should (not) achieve in our society.