Promoting Human Competences by Appropriate Modes of Interaction for Human-Centered-AI

Herrmann, Thomas

doi:10.1007/978-3-031-05643-7_3

Cited by 8 publications

(1 citation statement)

References 37 publications

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“…Concepts like "human-in-the-loop" (HITL) are getting established as mechanisms for AI systems that better serve human needs (Zanzotto, 2019). An HITL mechanism describes systems in which human involvement is integrated with automated processes to improve overall performance, reliability, and decision-making (Fu et al, 2021;Macher et al, 2021;Herrmann, 2022). Furthermore, several technology companies have defined their own sets of responsible AI guidelines with a human-centered foundation (Wright et al, 2020).…”

Section: Ai In Public Service Deliverymentioning

confidence: 99%

Exploring citizens’ stances on AI in public services: A social contract perspective

Schmager,

Grøder,

Parmiggiani

et al. 2024

Data & Policy

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This paper explores citizens’ stances toward the use of artificial intelligence (AI) in public services in Norway. Utilizing a social contract perspective, the study analyzes the government–citizen relationship at macro, meso, and micro levels. A prototype of an AI-enabled public welfare service was designed and presented to 20 participants who were interviewed to investigate their stances on the described AI use. We found a generally positive attitude and identified three factors contributing to this: (a) the high level of trust in government (macro level); (b) the balanced value proposition between individual and collective needs (meso level); and (c) the reassurance provided by having humans in the loop and providing transparency into processes, data, and model’s logic (microlevel). The findings provide valuable insights into citizens’ stances for socially responsible AI in public services. These insights can inform policy and guide the design and implementation of AI systems in the public sector by foregrounding the government–citizen relationship.

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