Deep Learning Meets Deep Democracy: Deliberative Governance and Responsible Innovation in Artificial Intelligence

Alexander Buhmann, Christian Fieseler · 2022 · Business Ethics Quarterly

Summary. The paper argues that responsible AI innovation requires public deliberation involving industry, government, and civil society actors. It identifies opacity and knowledge gaps between experts and citizens as barriers to informed democratic debate about AI. The authors propose a deliberative governance framework that enables AI industry actors to engage effectively with experts and the public across different venues, building trust and enabling democratic oversight of AI systems.

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@article{buhmann-2022-deep-learning-meets-deep-democracy,
  title   = {Deep Learning Meets Deep Democracy: Deliberative Governance and Responsible Innovation in Artificial Intelligence},
  author  = {Alexander Buhmann and Christian Fieseler},
  journal = {Business Ethics Quarterly},
  year    = {2022},
  doi     = {10.1017/beq.2021.42},
  url     = {https://doi.org/10.1017/beq.2021.42}
}

TY  - JOUR
TI  - Deep Learning Meets Deep Democracy: Deliberative Governance and Responsible Innovation in Artificial Intelligence
AU  - Alexander Buhmann
AU  - Christian Fieseler
JO  - Business Ethics Quarterly
PY  - 2022
DO  - 10.1017/beq.2021.42
UR  - https://doi.org/10.1017/beq.2021.42
ER  - 

Details

DOI

10.1017/beq.2021.42

Countries

Norway

Regions

Europe

Categories

innovation-theory, policy, general-innovation

Added

2026-04-28