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Every year since 2002, Massachusetts Institute of Technology (MIT) has published its list of the ten technologies it predicts will have the greatest innovative impact long-term.

For 2019, these are: Robot Dexterity, New-Wave Nuclear Power, Predicting Preemies, Gut Probe in a Pill, Custom Cancer Vaccines, The Cow-Free Burger, Carbon Dioxide Catcher, An ECG on your Wrist, Sanitation without Sewers, and Smooth-Talking AI Assistants.

Such lists are created annually; some technologies prove to be just bubbles, others exceed all expectations eliciting challenging societal debates such as the current ones about energy transition technologies, e-mobility or Industry 4.0. However, one issue is beyond all question:

Technology changes society, and, vice versa, societal institutions and organisations shape and influence technologies as „social projects“ by fostering, funding, enabling, producing, limiting and preventing them.

Connecting technologies to application, utilisation, deployment and exploitation contexts, i.e. what we call innovation, provides additional social dynamics. Besides technological innovation targeting new commercial products and processes, social innovation applying new organisational structures gains in increasing importance. Often, technological innovation and social innovation meet such as with digitalising public sector services. New technologies and innovations are „radical game-changers“: they have the potential of changing the world we live in quickly and drastically. However, as future objects they are neither predictable nor accessible; with these characteristics they challenge the institutions concerned with societal planning, policymaking and coordination.

This is the area where the team of our Chair for Sociology of Technology and Innovation, founded in 2017 at JGU, engages in research, teaching and knowledge transfer. Analysing social phenomena around the production, the structures and the consequences of technologies and innovations, helps to understand, describe and explain the complex dynamics in technology and innovation. For research, these complexity aspects require a computer-based lab research infrastructure, which supports a mix of quantitative and qualitative empirical methods combined with innovative methodological approaches from Computational Social Science such as social simulation.