Dr. Léa Steinacker is an award-winning journalist, researcher, and entrepreneur. She is the Co-Founder and Chief Operations Officer of ada learning, a training and development community that equips workers from across organisations for the future. With her expertise in emerging technologies and their wide-ranging effects, she is a Lecturer at the University of St. Gallen, Switzerland, teaching courses such as "Social and Economic Impacts of Artificial Intelligence". Previously, Léa served as the Chief Innovation Officer of WirtschaftsWoche, Germany's leading business magazine, where she covered the future of work and socio-technological change. 

Prior to joining Handelsblatt Media Group, Léa worked with social justice NGOs in Bosnia-Hercegovina, Rwanda, and the Democratic Republic of Congo. She was selected as a Forbes 30 Under 30 leader, one of Medium Magazine’s Top 30 Under 30 journalists, and an Atlantik Bruecke Young Leader. In 2011, she was awarded the Henry Richardson Labouisse Prize. 


Léa holds degrees from Princeton University (A.B.), the Harvard Kennedy School of Government (MPP), and the University of St. Gallen (PhD). 

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Steinacker, L. (2022). Code Capital: A Sociotechnical Framework to Understand the Implications of Artificially Intelligent Systems from Design to Deployment. Nomos Verlag.

Abstract: To assess how artificial intelligence impacts us in multidimensional ways, the novel notion of code capital serves as an account of the sociotechnical features that shape each system. Combining the evolution of capital towards a repository of socialised leverage with the history of technology studies, this concept facilitates analysis along four dimensions: conception, operations, data and environment. In this book, two case studies on facial recognition and synthetic speech generation demonstrate how code capital can act as a form of shared ontology for interdisciplinary stakeholders to anticipate and manage the effects of applied AI.


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.

Abstract: Governments have begun to employ technological systems that use massive amounts of data and artificial intelligence (AI) in the domains of law enforcement, public health, or social welfare. In some areas, shifts in public opinion increasingly favor technology-aided public decision-making. This development presents an opportunity to explore novel approaches to how technology could be used to reinvigorate democratic governance and how the public perceives such changes. The study therefore posits a hypothetical AI voting system that mediates political decision-making between citizens and the state. We conducted a four-country online survey (N=6043) in Greece, Singapore, Switzerland, and the US to find out what factors affect the public’s acceptance of such a system. The data show that Singaporeans are most likely and Greeks least likely to accept the system. Considerations of the technology’s utility have a large effect on acceptance rates across cultures whereas attitudes towards political norms and political performance have partial effects.

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.

Abstract: How does the public perceive facial recognition technology and how much do they accept facial recognition technology in different political contexts? Based on online surveys resembling the Internet-connected population in China, Germany, the United Kingdom, and the United States, our study finds that facial recognition technology enjoys generally highest acceptance among respondents in China, while acceptance is lowest in Germany, and the United Kingdom and the United States are in between. A closer examination through the lens of an integrated technology acceptance model reveals interesting variations in the selected four countries based, among other factors, on socio-demographic factors as well as perceived consequences, usefulness, and reliability of facial recognition technology. While previous research has pointed out that facial recognition technology is an instrument for state surveillance and control, this study shows that surveillance and control are not foremost on the minds of citizens in China, Germany, the United Kingdom, and the United States, but rather notions of convenience and improved security.

Shahrezaye, M., Meckel, M., Steinacker, L., & Suter, V. (2021, April). COVID-19’s (mis) information ecosystem on Twitter: How partisanship boosts the spread of conspiracy narratives on German speaking Twitter. In Future of Information and Communication Conference (pp. 1060-1073). Springer, Cham.
Abstract: In late 2019, the gravest pandemic in a century began spreading across the world. A state of uncertainty related to what has become known as SARS-CoV-2 has since fueled conspiracy narratives on social media about the origin, transmission and medical treatment of and vaccination against the resulting disease, COVID-19. Using social media intelligence to monitor and understand the proliferation of conspiracy narratives is one way to analyze the distribution of misinformation on the pandemic. We analyzed more than 9.5M German language tweets about COVID-19. The results show that only about 0.6% of all those tweets deal with conspiracy theory narratives. We also found that the political orientation of users correlates with the volume of content users contribute to the dissemination of conspiracy narratives, implying that partisan communicators have a higher motivation to take part in conspiratorial discussions on Twitter. Finally, we showed that contrary to other studies, automated accounts do not significantly influence the spread of misinformation in the German speaking Twitter sphere. They only represent about 1.31% of all conspiracy-related activities in our database.

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.

Abstract: With rapid advances in machine learning (ML), more of this technology is being deployed into the real world interacting with us and our environment. One of the most widely applied application of ML is facial recognition as it is running on millions of devices. While being useful for some people, others perceive it as a threat when used by public authorities. This discrepancy and the lack of policy increases the uncertainty in the ML community about the future direction of facial recognition research and development. In this paper we present results from a cross-national survey about public acceptance, privacy, and discrimination of the use of facial recognition technology (FRT) in the public. This study provides insights about the opinion towards FRT from China, Germany, the United Kingdom (UK), and the United States (US), which can serve as input for policy makers and legal regulators.

Suter, V., Steinacker, L., & Meckel, M. (2020). Networked Panoptic Power: Effects of Transparency on State-Citizen Relations in China’s Social Credit System. Presented at the International Communication Association ICA 2020. - Gold Coast, Australia. 

Abstract: This article examines China’s Social Credit System to illustrate how information and communication technologies bring forth new forms of interaction between the state and citizens. In particular, it asks how the transparency generated by the Social Credit System enables new forms of social control, trust, and self-regulation. For this purpose, the study frames the analysis with Foucault’s model of disciplinary power and provides an empirical description of the Social Credit System that focuses on the system’s basic design elements and on the political intentions behind its implementation. The article then suggests a heuristic framework of transparency as an analytical structure to chart the emerging configuration of government-citizen relations. The study finds that the system increases the control of the single-party state over society, likely diminishes trust, and reduces the freedom to act. However, compared to the clientelism and arbitrary decision-making of previous decades, the precise and depersonalized standards of the Social Credit System can be seen as an improvement that enables the capacity of individual actors to self-regulate. This theoretical and analytical approach thus adds to the debate about how government through algorithms rearranges practices of state power and control.


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