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Rechtswissenschaftliche Fakultät Lehrstuhl Hermstrüwer

Vergangene Veranstaltungen | Past Events

Podiumsdiskussion - Künstliche Intelligenz in der Rechtsbranche: Auswirkungen, Chancen und Risiken

Wie hat KI die Rechtsbranche bereits verändert? Wie wenden Sie persönlich KI bereits an? Wo bestehen Vorteile, wo Nachteile der Technologie? Was ist rechtlich, wirtschaftlich, ethisch zu bedenken? Wie wird sich die Branche durch den Einsatz von KI verändern?

Diesen Fragen sind LegalTech-Expert:innen an einer vom Jusstudierendenverein SLTA Student Chapter Zurich organisierten Podiumsdiskussion nachgegangen. 

Termin: 17. April 2024

Zeit: 18:30 – 19:40 (Diskussion), 19:40 – open ended (Apéro)

Ort: „kleine Aula“ UZH, RAA-G-01, Rämistrasse 59, 8001 Zürich

Diskutant:innen:

  • Prof. Dr. Dr. Yoan Hermstrüwer, Lehrstuhl für Legal Tech, Law and Economics und Öffentliches Recht, Universität Zürich
  • Dr. Alexander Wherlock, RA, Associate bei Homburger
  • Paula Reichenberg, RA, CEO & Gründerin Neur.on AI, Vizepräsidentin der Swiss LegalTech Association
  • Roxana Sharifi, RA, Associate bei CMS Schweiz

Impressionen

Having Your Day in Robot Court: The Psychology of Procedural Justice and Artificial Intelligence

New York State Bar Association

January 25, 2024, 19:00-20:30 CET (Webinar)

Should machines be judges? One powerful reason to say “no" concerns procedural justice. Citizens would see robot-led legal proceedings as procedurally unfair. Prior research has established that people obey the law in part because they see it as procedurally just, and the introduction of “robot judges” powered by artificial intelligence (“AI”) could undermine sentiments of justice and legal compliance if citizens view machine-adjudicated proceedings as less fair than the human-adjudicated status quo. We conducted two original experiments that show that ordinary people share this intuition: There is a perceived “human-AI fairness gap.” 

However, the studies also show that it is also possible to reduce — and perhaps even eliminate — this fairness gap through “algorithmic offsetting.” Affording litigants a hearing before an AI judge and enhancing the interpretability of AI decisions reduce the human-AI fairness gap. Our experiments support a common and fundamental objection to robot judges: There is a concerning human-AI fairness gap. Yet, at the same time, the results also indicate that the public may not believe that human judges possess irreducible procedural fairness advantages. In some circumstances, people see a day in a robot court as no less fair than a day in a human court.

Link to the Webinar