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International Conference on Next Generation Wired/Wireless Networking

Conference on Internet of Things and Smart Spaces

NEW2AN 2019, ruSMART 2019: Internet of Things, Smart Spaces, and Next Generation Networks and Systems pp 113–124Cite as

Decision Support Based on Human-Machine Collective Intelligence: Major Challenges

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Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 11660))

Abstract

The paper discusses a novel class of decision support systems, based on an environment, leveraging human-machine collective intelligence. The distinctive feature of the proposed environment is support for natural self-organization processes in the community of participants. Most of the existing approaches for leveraging human expertise in a computing system rely on a pre-defined rigid workflow specification, and those very few systems that try to overcome this limitation sidestep current body of knowledge of self-organization in artificial and natural systems. The paper outlines the general vision of the proposed environment, identifies main challenges that has to be dealt with in order to develop such environment and describes ways to address them. Potential applications of such decision support environment are ubiquitous and influence virtually all areas of human activities, especially in complex domains: business management, environment problems, and government decisions.

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References

  1. Retelny, D., Bernstein, M.S., Valentine, M.A.: No workflow can ever be enough: how crowdsourcing workflows constrain complex work. In: Proceedings ACM Human-Computer Interact, vol. 1, no. 2, article 89 (2017)

    Article  Google Scholar 

  2. Valentine, M.A., et al.: Flash organizations. In: 2017 CHI Conference on Human Factors in Computing Systems – CHI 2017, pp. 3523–3537. ACM Press, New York (2017)

    Google Scholar 

  3. Viroli, M., Audrito, G., Beal, J., Damiani F., Pianini D.: Engineering resilient collective adaptive systems by self-stabilisation. J. ACM Trans. Model. Comput. Simul. 28(2) (2018). Article 16

    Article  MathSciNet  Google Scholar 

  4. Dustdar, S., Nastic, S., Scekic, O.: Smart Cities: The Internet of Things, People and Systems. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-60030-7

    Book  Google Scholar 

  5. Schall, D.: Service-Oriented Crowdsourcing: Architecture, Protocols and Algorithms. Springer, New York (2012). https://doi.org/10.1007/978-1-4614-5956-9

    Book  Google Scholar 

  6. Schall, D.: Service oriented protocols for human computation. In: Michelucci, P. (ed.) Handbook of Human Computation, pp. 551–559. Springer, New York (2013). https://doi.org/10.1007/978-1-4614-8806-4_42

    Chapter  MATH  Google Scholar 

  7. Tranquillini, S., Daniel, F., Kucherbaev, P., Casati, F.: Modeling, enacting, and integrating custom crowdsourcing processes. ACM Trans. Web 9(2), 7:1–7:43 (2015)

    Article  Google Scholar 

  8. Little, G.: Exploring iterative and parallel human computation processes. In: Extended Abstracts on Human Factors in Computing Systems, ser. CHI EA 2010, pp. 4309–4314. ACM (2010)

    Google Scholar 

  9. Franklin, M.J., Kossmann, D., Kraska, T., Ramesh, S., Xin, R.: CrowdDB: answering queries with crowdsourcing. In: Proceedings 2011 ACM SIGMOD International Conference on Management of Data, ser. SIGMOD 2011, pp. 61–72. ACM (2011)

    Google Scholar 

  10. Barowy, D.W., Curtsinger, C., Berger, E.D., McGregor, A.: AUTOMAN: a platform for integrating human-based and digital computation. SIGPLAN Not. 47(10), 639–654 (2012)

    Article  Google Scholar 

  11. Kulkarni, A.P., Can, M., Hartmann, B.: Turkomatic: automatic recursive task and workflow design for mechanical turk. In: CHI 2011 Extended Abstracts on Human Factors in Computing Systems, ser. CHI EA 2011, pp. 2053–2058. ACM (2011)

    Google Scholar 

  12. Ahmad, S., Battle, A., Malkani, Z., Kamvar, S.: The jabberwocky programming environment for structured social computing. In: Proceedings 24th Annual ACM Symposium on User Interface Software and Technology (UIST 2011), pp. 53–64. ACM (2011)

    Google Scholar 

  13. Minder, P., Bernstein, A.: CrowdLang: a programming language for the systematic exploration of human computation systems. In: Aberer, K., Flache, A., Jager, W., Liu, L., Tang, J., Guéret, C. (eds.) SocInfo 2012. LNCS, vol. 7710, pp. 124–137. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-35386-4_10

    Chapter  Google Scholar 

  14. Bozzon, A., Brambilla, M., Ceri, S., Mauri, A., Volonterio, R.: Pattern-based specification of crowdsourcing applications. In: Casteleyn, S., Rossi, G., Winckler, M. (eds.) ICWE 2014. LNCS, vol. 8541, pp. 218–235. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-08245-5_13

    Chapter  Google Scholar 

  15. Kulkarni, A., Can, M., Hartmann, B.: Collaboratively crowdsourcing workflows with turkomatic. In: Proceedings of the ACM 2012 Conference on Computer Supported Cooperative Work, Seattle, Washington, USA (2012)

    Google Scholar 

  16. Dale, R., Fusaroli, R., Duran, N.D., Richardson, D.C.: The self-organization of human interaction. Psychol. Learn. Motiv. 59, 43–95 (2013)

    Article  Google Scholar 

  17. Kogan, M.: Digital traces of online self-organizing and problem solving in disaster. In: Proceedings of the 19th International Conference on Supporting Group Work - GROUP 2016, pp. 479–483. ACM Press (2016)

    Google Scholar 

  18. Gorodetskii, V.I.: Self-organization and multiagent systems: I. Models of multiagent self-organization. J. Comput. Syst. Sci. Int. 51(2), 256–281 (2012)

    Article  MathSciNet  Google Scholar 

  19. Kamar, E.: Directions in hybrid intelligence: complementing ai systems with human intelligence. IJCAI Invited Talk: Early Career Spotlight Track (2016)

    Google Scholar 

  20. Nushi, B., Kamar, E., Horvitz, E., Kossmann, D.: On human intellect and machine failures: Troubleshooting integrative machine learning systems. In: 31st AAAI Conference on Artificial Intelligence, pp. 1017–1025 (2017)

    Google Scholar 

  21. Verhulst, S.G.: AI & Society 33(2), 293–297 (2018)

    Google Scholar 

  22. Dai, P., Mausam, Weld, D.S.: Decision-theoretic control of crowd-sourced workflows. In: National Conference on Artificial Intelligence – AAAI (2010)

    Google Scholar 

  23. Dai, P., Mausam, Weld, D.S.: Artificial intelligence for artificial artificial intelligence. In: The 25th AAAI Conference on Artificial Intelligence, pp. 1153–1159 (2011)

    Google Scholar 

  24. Yuen, M-Ch., King, I., Leung, K.-S.: TaskRec: a task recommendation framework in crowdsourcing systems. Neural Process. Lett. 41(2), 223–238 (2015)

    Article  Google Scholar 

  25. Abbeel, P., Ng, A.: Apprenticeship learning via inverse reinforcement learning. In: 21st International Conference on Machine Learning (ICML) (2004)

    Google Scholar 

  26. Settles, B.: Active Learning Literature Survey. Computer Sciences Technical Report 1648. University of Wisconsin–Madison. http://pages.cs.wisc.edu/~bsettles/pub/settles.activelearning.pdf. Accessed 5 July 2019

  27. Felfernig, A., et al.: Configuration knowledge representations for Semantic Web applications. Artif. Intell. Eng. Des. Anal. Manuf. 17, 31–50 (2003)

    Article  Google Scholar 

  28. Liao, Y., Lezoche, M., Panetto, H., Boudjlida, N.: Semantic annotations for semantic interoperability in a product lifecycle management context. Int. J. Prod. Res. 54, 5534–5553 (2016)

    Article  Google Scholar 

  29. Forsyth, D.R.: Decision making. In: Group Dynamics, 5th edn., pp. 317–349. Cengage Learning (2006)

    Google Scholar 

  30. Smirnov, A., Shilov, N.: Service-based socio-cyberphysical network modeling for guided self-organization. Procedia Comput. Sci. 64, 290–297 (2015)

    Article  Google Scholar 

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Acknowledgements

The research is funded by the Russian Science Foundation (project # 19-11-00126).

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Authors and Affiliations

  1. St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences, 14th Line 39, St. Petersburg, Russian Federation

    Alexander Smirnov & Andrew Ponomarev

Authors
  1. Alexander Smirnov
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  2. Andrew Ponomarev
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Corresponding author

Correspondence to Andrew Ponomarev .

Editor information

Editors and Affiliations

  1. Tampere University, Tampere, Finland

    Olga Galinina

  2. Tampere University, Tampere, Finland

    Sergey Andreev

  3. FRUCT Oy, Helsinki, Finland

    Sergey Balandin

  4. Tampere University, Tampere, Finland

    Yevgeni Koucheryavy

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Smirnov, A., Ponomarev, A. (2019). Decision Support Based on Human-Machine Collective Intelligence: Major Challenges. In: Galinina, O., Andreev, S., Balandin, S., Koucheryavy, Y. (eds) Internet of Things, Smart Spaces, and Next Generation Networks and Systems. NEW2AN ruSMART 2019 2019. Lecture Notes in Computer Science(), vol 11660. Springer, Cham. https://doi.org/10.1007/978-3-030-30859-9_10

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  • DOI: https://doi.org/10.1007/978-3-030-30859-9_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-30858-2

  • Online ISBN: 978-3-030-30859-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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