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Artificial Intelligence Awareness in Work Environments

  • Hannu KarvonenEmail author
  • Eetu Heikkilä
  • Mikael Wahlström
Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 544)

Abstract

Based on the concepts of situation and automation awareness, we present a new concept called “artificial intelligence awareness”. We also examine in detail how these three phenomena relate to each other particularly in work environments. To open this discussion, we shortly go through the ideas behind these concepts and focus especially on artificial intelligence (AI) from the machine-learning perspective and on some related human-AI interaction issues. In addition, we present an illustration of a theoretical taxonomy where our understanding of the relationships between the three key awareness concepts is visualized. We conclude by giving pointers for further research and design regarding how to support automation and AI awareness of intelligent systems users in work environments.

Keywords

Artificial intelligence Work Automation Situation awareness AI transparency Intelligent systems Trust in automation Human factors 

References

  1. 1.
    Karvonen, H., Liinasuo, M., Lappalainen, J.: Assessment of automation awareness. In: Proceedings of Automaatio XXI Conference 2015, 44, Publication Series of the Finnish Society of Automation, Helsinki (2015)Google Scholar
  2. 2.
    Karvonen, H., Lappalainen, J., Liinasuo, M.: Automation awareness user interface study – preliminary results. In: Proceedings of the Man-Technology-Organisation Sessions at the 2014 Enlarged Halden Project Group Meeting, vol. 1, C2.4., OECD Halden Reactor Project, Norway (2014)Google Scholar
  3. 3.
    Karvonen, H., et al.: Studying automation awareness in nuclear power plants. In: Hämäläinen J., Suolanen, V. (eds.) The Finnish Research Programme on Nuclear Power Plant Safety 2010–2014, Final Report, VTT Technology 213, pp. 92–102. VTT, Espoo (2015)Google Scholar
  4. 4.
    Laitio, P., Savioja, P. Lappalainen, J.: Exploring automation awareness in nuclear power plant control rooms. In: Proceedings of the Man-Technology-Organisation Sessions at the 2013 Enlarged Halden Project Group Meeting, OECD Halden Reactor Project, Norway (2013)Google Scholar
  5. 5.
    Endsley, M.R.: Toward a theory of situation awareness in dynamic systems. Hum. Factors 37(1), 32–64 (1995)CrossRefGoogle Scholar
  6. 6.
    Whitlow, S.D., Dorneich, M.C., Funk, H.B., Miller, C.A.: Providing appropriate situation awareness within a mixed-initiative control system. In: Proceedings of the 2002 IEEE International Conference on Systems, Man and Cybernetics (2002)Google Scholar
  7. 7.
    Karvonen, H., Liinasuo, M., Lappalainen J.: Assessment of situation and automation awareness, VTT Technical Research Centre of Finland, VTT Research Report VTT-R-05997-14 (2014)Google Scholar
  8. 8.
    Nilsson, N. J.: The Quest for Artificial Intelligence. Cambridge University Press, Cambridge (2009)Google Scholar
  9. 9.
    Stone, P., et al.: Artificial Intelligence and Life in 2030. One Hundred Year Study on Artificial Intelligence: Report of the 2015–2016 Study Panel, Stanford University, Stanford, CA (2016)Google Scholar
  10. 10.
    Jordan, M.I., Mitchell, T.M.: Machine learning: trends, perspectives, and prospects. Science 349(6245), 255–260 (2015)MathSciNetCrossRefGoogle Scholar
  11. 11.
    Lee, J.H., Shin, J., Realff, M.J.: Machine learning: Overview of the recent progresses and implications for the process systems engineering field. Comput. Chem. Eng. 114(1), 111–121 (2018)CrossRefGoogle Scholar
  12. 12.
    Mnih, V., et al.: Human-level control through deep reinforcement learning. Nature 518(7540), 529–533 (2015)CrossRefGoogle Scholar
  13. 13.
    Theodorou, A., Wortham, R.H., Bryson, J.J.: Designing and implementing transparency for real time inspection of autonomous robots. Connection Sci. 29(3), 230–241 (2017)CrossRefGoogle Scholar
  14. 14.
    Pynadath, D.V., Barnes, M.J., Wang, N., Chen, J.Y.C.: Transparency communication for machine learning in human-automation interaction. In: Zhou, J., Chen, F. (eds.) Human and Machine Learning. HIS, pp. 75–90. Springer, Cham (2018).  https://doi.org/10.1007/978-3-319-90403-0_5CrossRefGoogle Scholar
  15. 15.
    Amnesty International: Trapped in the matrix: Secrecy, stigma, and bias in the Met’s Gangs Database (2018). Published online by Amnesty International at https://www.amnesty.org.uk/files/reports/Trapped%20in%20the%20Matrix%20Amnesty%20report.pdf
  16. 16.
    Medina-Mora, R., Winograd, T., Flores, R., Flores, F.: The action workflow approach to workflow management technology. Inf. Soc. 9(4), 391–404 (1993)CrossRefGoogle Scholar
  17. 17.
    Winograd, T.: Categories, disciplines, and social coordination. Comput. Support. Coop. Work (CSCW) 2(3), 191–197 (1993)CrossRefGoogle Scholar
  18. 18.
    Lee, J.D., See, K.A.: Trust in automation: designing for appropriate reliance. Hum. Factors 46(1), 50–80 (2004)CrossRefGoogle Scholar
  19. 19.
    Neisser, U.: Cognition and reality: Principles and implications of cognitive psychology. WH Freeman/Times Books/Henry Holt & Co (1976)Google Scholar
  20. 20.
    Sandom, C.: Situation awareness. In: Noyes, J., Bransby, M. (eds.) People in Control: Human Factors in Control Room Design. IET, Herts (2001)Google Scholar
  21. 21.
    Peirce, C.S.: The Essential Peirce, Selected Philosophical Writings. Indiana University Press, Indiana (1998)Google Scholar
  22. 22.
    Bainbridge, L.: Ironies of automation. Automatica 19(6), 775–779 (1983)CrossRefGoogle Scholar

Copyright information

© IFIP International Federation for Information Processing 2019

Authors and Affiliations

  • Hannu Karvonen
    • 1
    Email author
  • Eetu Heikkilä
    • 1
  • Mikael Wahlström
    • 1
  1. 1.VTT Technical Research Centre of Finland Ltd.EspooFinland

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