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Trust-Based Human-Machine Collaboration Mechanism for Predicting Crimes

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Advanced Information Networking and Applications (AINA 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1151))

Abstract

In today’s world, with the shifting nature of artificial intelligence (AI) to explainable AI, which involves humans and machines working and complementing each other, there is a need for a mechanism to govern their collaboration. We have proposed a trust-based mechanism to manage collaboration between them. Our trust-based mechanism has the ability to quantify human trust into a mathematical model. The proposed trust-based framework will facilitate decision making when humans and machines are involved in a process. This framework will ensure that either of them never under trust or over trust each other by computing trust information based on their history. To validate our proposed framework, experiments are performed on Indianapolis Crime Data which contains actual crime information, machine predictions, and police feedback. Results have shown that how the trust of both entities can impact the decision making of the police towards machine predictions.

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Acknowledgements

This work was partially supported by the National Science Foundation under Grant No. 1547411 and by the U.S. Department of Agriculture (USDA) National Institute of Food and Agriculture (NIFA) (Award Number 2017-67003-26057) via an interagency partnership between USDA-NIFA and the National Science Foundation (NSF) on the research program Innovations at the Nexus of Food, Energy and Water Systems.

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Authors and Affiliations

  1. Department of Computer and Information Science, Indiana University Purdue University, Indianapolis, IN, USA

    Davinder Kaur, Suleyman Uslu, Arjan Durresi & George Mohler

  2. Paul H. O’Neill School of Public and Environmental Affairs, Indiana University Purdue University, Indianapolis, IN, USA

    Jeremy G. Carter

Authors
  1. Davinder Kaur
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  2. Suleyman Uslu
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  3. Arjan Durresi
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  4. George Mohler
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  5. Jeremy G. Carter
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Corresponding author

Correspondence to Arjan Durresi .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Faculty of Information Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

  2. Department of Electrical Engineering and Information Technology, University of Naples “Frederico II”, Naples, Italy

    Flora Amato

  3. Department of Political Science, University of Campania “Luigi Vanvitelli”, Caserta, Italy

    Francesco Moscato

  4. Faculty of Business Administration, Rissho University, Tokyo, Japan

    Tomoya Enokido

  5. Department of Advanced Sciences, Faculty of Science and Engineering, Hosei University, Tokyo, Japan

    Makoto Takizawa

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Kaur, D., Uslu, S., Durresi, A., Mohler, G., Carter, J.G. (2020). Trust-Based Human-Machine Collaboration Mechanism for Predicting Crimes. In: Barolli, L., Amato, F., Moscato, F., Enokido, T., Takizawa, M. (eds) Advanced Information Networking and Applications. AINA 2020. Advances in Intelligent Systems and Computing, vol 1151. Springer, Cham. https://doi.org/10.1007/978-3-030-44041-1_54

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