Machine Intelligence: Blessing or Curse? It Depends on Us!

  • Dirk HelbingEmail author


Artificial Intelligence (AI) can help us in many ways. Particularly when combined with robotics, AI can make our everyday life more comfortable (e.g. clean our home). It can perform hard, dangerous and boring work for us. It can help us to save lives and cope with disasters more successfully. It can support patients and elderly people. It can support us in our everyday activities, and it can make our lives more interesting. I believe that most of us would like to benefit from these unprecedented opportunities. So far, however, any technology came along with side effects and risks. As I will show, people may lose self-determination and democracy, companies may lose control, and nations may lose their sovereignty, if we do not pay attention. In the following, I describe a worst-case and a best-case scenario to illustrate that our society is at a crossroads. It is crucial now to take the right path.


Boring Work Citation Score Mass Surveillance European General Data Protection Regulation Powerful Machine Learning Algorithms 
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Further Reading

  1. Helbing, D.: Responding to complexity in socio-economic systems: How to build a smart and resilient society? see
  2. Helbing, D.: The Automation of Society is Next: How to Survive the Digital Revolution. CreateSpace, North Charleston (2015)Google Scholar
  3. Helbing, D.: Societal, economic, ethical and legal challenges of the digital revolution: From big data to deep learning, artificial intelligence, and manipulative technologies, jusletter IT (2015). see
  4. Helbing, D. et al.: Eine Strategie für das digitale Zeitalter, Spektrum der Wissenschaft 1/2015.
  5. Spiekermann, S.: Ethical IT innovation: A value-based system design approach. Auerbach (2015)Google Scholar
  6. van den Hoven, J. et al. (eds.): Responsible Innovation 1: Innovative Solutions for Global Issues. Springer, Dordrecht (2014)Google Scholar
  7. van den Hoven, J. et al. (eds.): Handbook of Ethics, Values and Technological Design. Springer, Dordrecht (2015)Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  1. 1.ETH ZurichZürichSwitzerland
  2. 2.TU DelftDelftNetherlands
  3. 3.Complexity Science HubViennaAustria

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