The Implications of AI for Science: Friend or Foe?

Alena Buyx is Professor of Ethics in Medicine and Health Technologies and Director of the Institute of History and Ethics in Medicine at Technical University of Munich.
Professor Buyx is a medical doctor with degrees in philosophy and sociology. Her research spans the whole field of biomedical and public health ethics and questions of solidarity and justice.

In addition to research and teaching, Professor Buyx is active in the political and regulatory aspects of biomedical ethics, sitting on several high-level national and international ethics bodies concerned with policy development and implementation. She is a member of the German Ethics Council since 2016 and has been its chair since 2020.

Benoit, X’s Chief Technology Officer, oversees a portfolio of early-stage project teams that dream up, prototype and derisk X’s next generation of moonshots. The scientists, technologists and self described general weirdos in Benoit’s team take out-there ideas for positive world changing technologies from “what if?” to early prototype. Some of the team’s current areas of exploration include investigating the next frontiers in computing, biochemistry, inverse design and clean energy sources. Originally from Belgium, Benoit has worked in Silicon Valley for over 30 years holding senior technical roles at Yahoo, Nokia, Be.Inc and holds more than 40 U.S. and international patents related to his work in hardware and software technology. Benoit is the father of two wonderful daughters and when he’s not working on moonshots he can be found on his roof, gazing at the beauty of the night sky through his homemade telescopes.

Bernhard Schölkopf’s scientific interests are in machine learning and causal inference. He has applied his methods to a number of different fields, ranging from biomedical problems to computational photography and astronomy. Bernhard studied physics and mathematics and earned his Ph.D. in computer science in 1997, becoming a Max Planck director in 2001. He has (co-)received the Berlin-Brandenburg Academy Prize, the Royal Society Milner Award, the Leibniz Award, the BBVA Foundation Frontiers of Knowledge Award, and the ACM AAAI Allen Newell Award. He is Fellow of the ACM and of the CIFAR Program “Learning in Machines and Brains”, a member of the German Academy of Sciences, and a Professor at ETH Zurich. He helped start the MLSS series of Machine Learning Summer Schools, the Cyber Valley Initiative, the ELLIS society, and the Journal of Machine Learning Research, an early development in open access and today the field’s flagship journal. In 2023, he founded the ELLIS Institute Tuebingen, and acts as its scientific director.

Henning Schoenenberger, Vice President Content Innovation at Springer Nature, is an accomplished leader in innovative research content solutions. With a strong background in product management and digital innovation, Henning has a track record of early adopting Artificial Intelligence in scholarly publishing. He pioneered the first machine-generated research book published at Springer Nature.

Cat Allman, VP, Open Source Research at Digital Science.
Since the 1980s her focus has been helping people and their communities develop and meet their goals. Along with 10+ years with the Google Open Source Programs Office, Cat has been co-organizer of Science Foo Camp for 12+ years & founder of the Alumni community. Past & present board/committee/jury service includes the FreeBSD Foundation, the IEEE Standards Association Open Source Committee (OSCom), the PSU Digital Cities Testbed Center Advisory Committee, USENIX.org, the Open Source Track @ Grace Hopper and Falling Walls Labs.

Sudeshna Das earned her PhD from the Centre of Excellence in Artificial Intelligence, Indian Institute of Technology Kharagpur, India. Her doctoral research concentrated on AI-driven Gender Bias Identification in Textbooks. She is currently a Postdoctoral Fellow at the Department of Biomedical Informatics, School of Medicine, Emory University, USA, where she is part of the Sarker Lab. Her research interests lie at the intersection of AI and Social Good, with a particular focus on gender equity in education and healthcare. Prior to her doctoral research, she studied computer science and engineering, leading to an MTech from the National Institute of Technology Durgapur, India, and a BTech from West Bengal University of Technology, India.

I want to build AI-based technologies for removing barriers in education and healthcare. I want this because we cannot afford to perpetuate socioeconomic inequities in the applications of AI-based technology. I can do this because I have extensive experience developing AI systems that address social biases and promote inclusivity.