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Explainability for Public Communication of Expert Knowledge: Translating AI Explainability Research to Public Communication in Complex Crises on the Example of COVID-19 (additional Corona related funding)

Grant number: unknown

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Key facts

  • Disease

    COVID-19

  • Funder

    Volkswagen Stiftung

  • Principal Investigator

    Prof Dr-Ing and Prof Dr and Prof PhD Jasminko Novak, Enny Das, Martha Larson, Kalina Drenska
    …

  • Research Location

    Germany

  • Lead Research Institution

    European Institute for Participatory Media e. V.

  • Research Priority Alignment

    N/A

  • Research Category

    Policies for public health, disease control & community resilience

  • Research Subcategory

    Communication

  • Special Interest Tags

    N/A

  • Study Type

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Not Applicable

  • Vulnerable Population

    Not applicable

  • Occupations of Interest

    Not applicable

Abstract

This project module investigates how research on explainability of AI systems could be translated and applied to public communication of expert knowledge in complex crisis situations such as the COVID-19 pandemic. Both AI systems and expert recommendations of COVID-19 measures present people with results of what they perceive as intransparent, complex systems whose reasoning processes are neither directly observable, nor readily understandable. The goal is to examine which AI explanation techniques could be applied to increase public understanding of expert knowledge and decisions in such situations (e.g. combining contrastive and counterfactual explanations with persuasive communication). This could provide experts and decision-makers with novel methods for improving their communication and increasing public acceptance of their recommendations (e.g. COVID-19 containment measures, vaccination).