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The PSyKE Technology for Trustworthy Artificial Intelligence

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AIxIA 2022 – Advances in Artificial Intelligence (AIxIA 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13796))

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Abstract

Transparency is one of the “Ethical Principles in the Context of AI Systems” as described in the Ethics Guidelines for Trustworthy Artificial Intelligence (TAI). It is closely linked to four other principles – respect for human autonomy, prevention of harm, traceability and explainability – and involves numerous ways in which opaqueness can have undesirable impacts, such as discrimination, inequality, segregation, marginalisation, and manipulation. The opaqueness of many AI tools and the inability to understand the underpinning black boxes contradicts these principles as well as prevents people from fully trusting them. In this paper we discuss the PSyKE technology, a platform providing general-purpose support to symbolic knowledge extraction from different sorts of black-box predictors via many extraction algorithms. The extracted knowledge results are easily injectable into existing AI assets making them meet the transparency TAI requirement.

This work has been partially supported by the EU ICT-48 2020 project TAILOR (No. 952215) and by the European Union’s Horizon 2020 research and innovation programme under G.A. no. 101017142 (StairwAI project).

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Notes

  1. 1.

    https://scikit-learn.org/stable.

  2. 2.

    https://apice.unibo.it/xwiki/bin/view/PSyKE/.

  3. 3.

    https://github.com/tuProlog/2ppy.

  4. 4.

    https://archive.ics.uci.edu/ml/datasets/iris.

  5. 5.

    https://archive.ics.uci.edu/ml/datasets/combined+cycle+power+plant.

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Authors and Affiliations

  1. Alma AI – Alma Mater Research Institute for Human-Centered Artificial Intelligence, Alma Mater Studiorum—Università di Bologna, Bologna, Italy

    Roberta Calegari

  2. Department of Pure and Applied Sciences (DiSPeA), University of Urbino, Via S. Chiara, 27, 61029, Urbino, Italy

    Federico Sabbatini

Authors
  1. Roberta Calegari
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  2. Federico Sabbatini
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Correspondence to Federico Sabbatini .

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Editors and Affiliations

  1. University of Udine, Udine, Italy

    Agostino Dovier

  2. University of Udine, Udine, Italy

    Angelo Montanari

  3. National Research Council (CNR-ISTC), Rome, Italy

    Andrea Orlandini

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Calegari, R., Sabbatini, F. (2023). The PSyKE Technology for Trustworthy Artificial Intelligence. In: Dovier, A., Montanari, A., Orlandini, A. (eds) AIxIA 2022 – Advances in Artificial Intelligence. AIxIA 2022. Lecture Notes in Computer Science(), vol 13796. Springer, Cham. https://doi.org/10.1007/978-3-031-27181-6_1

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  • DOI: https://doi.org/10.1007/978-3-031-27181-6_1

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