Topic: Trustworthy AI

Jin Zhu examines statistical approaches to identifying text produced by large language models. The increasing availability of fluent generated writing raises questions about misinformation, academic integrity and the authenticity of digital content. Although detection has attracted substantial machine-learning research, the talk argues that its statistical foundations remain underdeveloped. Zhu presents recent work on principled, computationally efficient detection methods, including approaches reported at NeurIPS and ICLR. An interactive demonstration accompanies the research, illustrating on

ETH AI Center is recruiting approximately 8–12 doctoral fellows to propose and pursue interdisciplinary AI research, with two supervisors from different fields. Projects can address AI foundations or connect them with application areas. Fellows are based at the centre in Zurich and can pursue optional industry or entrepreneurship experience. Employment normally lasts three years, with a possible fourth year subject to progress; the usual start is September 2027. Published annual salaries are CHF 73,100, CHF 78,300 and CHF 83,500 in the first three years. Applicants need a relevant master’s deg

ETH AI Center offers approximately 8–12 postdoctoral fellowships for interdisciplinary AI research, with equal supervision by two principal investigators from different fields. Fellows develop their own projects spanning AI foundations and applications, join research exchanges and events, and may explore industry or entrepreneurial tracks. The appointment normally lasts two years, usually beginning in September 2027. Published salaries are CHF 92,500 in year one and CHF 97,200 in year two. A relevant doctorate must be completed at least three months before starting, and by June 2027 at the lat

NSF support for interdisciplinary collaborations developing mathematical and theoretical foundations for explainable, reliable, sustainable and trustworthy artificial intelligence.