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SIENNA D5.4: Multi-stakeholder Strategy and Practical Tools for Ethical AI and Robotics

Authors: Anais Resseguier; Philip Brey; Brandt Dainow; Anna Drozdzewska;

SIENNA D5.4: Multi-stakeholder Strategy and Practical Tools for Ethical AI and Robotics

Abstract

After having conducted extensive ethical and legal studies and consulted a wide range of stakeholders on AI and robotics and the social implications of these technologies, the SIENNA project has developed practical ethical guidance documents for AI and robotics. Considering the numerous high-level guidance documents developed in the field over the last couple of years, including the High-Level Expert Group on Artificial Intelligence (AI HLEG), the SIENNA project, together with numerous stakeholders, identified the need for more operational guidance documents. The main objective of these documents is to provide practical ethics guidance to ensure AI and robotics are developed, deployed and used in ways that respect key ethical principles and values. SIENNA has developed six different guidance documents. The first guidance document is a Multi-stakeholder Strategy for Ethical AI and Robotics which is a comprehensive multi-stakeholder framework to ensure ethical AI and robotics. The others are: Ethics by Design and Ethics of Use for AI and Robotics Industry Education and Buy-In for AI Ethics Research ethics guidelines for Artificial Intelligence AI Ethics Education, Training and Awareness Raising Ethics at Attention to Context: Recommendations for AI ethics

Keywords

robotics, ethics tools, ethics by design, strategy for ethical AI and robotics, artificial intelligence, ethics

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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