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Dr. Léa Steinacker
I am a journalist, entrepreneur, and social scientist with a PhD in the social dimensions of artificially intelligent systems (AI). My work focuses on how technology interacts with people, practices, and the planet.
I have published on topics like automated facial recognition, synthetic voice generation, quantum computing, and my original framework of Code Capital. With my expertise in emerging technologies and their wide-ranging effects, I am a lecturer at the University of St. Gallen, Switzerland, teaching courses such as "Social and Economic Impacts of Artificial Intelligence".
In 2018, I co-founded and am the Chief Innovation Officer of ada Learning, a learning and development community that equips leaders from diverse organizations for the future through content, live experiences, and practical innovation projects. Since its inception, ada has connected and worked with thousands of fellows from DAX organzations, SMEs, governments and NGOs.
Previously, I served as the Chief Innovation Officer of WirtschaftsWoche, Germany's leading business magazine, where I covered the future of work and socio-technological change. Prior to joining Handelsblatt Media Group, I worked with social justice NGOs in Bosnia-Hercegovina, Rwanda, and the Democratic Republic of Congo. I was selected as a Forbes 30 Under 30 leader, one of Medium Magazine’s Top 30 Under 30 journalists, a BCG Thought Leader, and an Atlantik Brücke Young Leader. In 2011, I was awarded the Henry Richardson Labouisse Prize for independent research.
I hold degrees from Princeton University (A.B.), the Harvard Kennedy School of Government (MPP), and the University of St. Gallen (PhD).
by Stephanie Pistel
I regularly share my expertise in keynotes and lectures, enabling the audience to think deeply about the impact of transformative technologies. With a focus on the implications of artificial intelligence, I provide wide-ranging insights on the field's foundations, ethics, and business implications. I explore how automation is transforming different industries and emphasize how a more socially conscious approach to research and development can ensure that AI is deployed in a responsible and equitable manner.
For speaking inquiries, please use the contact form below.
Steinacker, L. (2022). Code Capital: A Sociotechnical Framework to Understand the Implications of Artificially Intelligent Systems from Design to Deployment. Nomos Verlag.
Rietsche, R., Dremel, C., Bosch, S., Steinacker, L., Meckel, M., & Leimeister, J. M. (2022). Quantum computing. Electronic Markets, 1-12.
Kostka, G., Steinacker, L., & Meckel, M. (2022). Under big brother's watchful eye: Cross-country attitudes toward facial recognition technology. Government Information Quarterly, 101761.
Suter, V., Meckel, M., Shahrezaye, M., & Steinacker, L. (2022, January). AI Suffrage: A four-country survey on the acceptance of an automated voting system. In Proceedings of the 55th Hawaii International Conference on System Sciences.
Kostka,G.; Steinacker, L.; Meckel, M. (2021). Between Security and Convenience: Facial recognition technology in the eyes of citizens in China, Germany, the United Kingdom, and the United States. Public Understanding of Science.
Steinacker, L; Meckel, M.; Kostka, G. & Borth, D. (2020). Facial Recognition: A cross-national Survey on Public Acceptance, Privacy, and Discrimination. Proceedings of the 37th International Conference on Machine Learning Law and ML Workshop, Vienna.
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