Responsible Artificial Intelligence - How to Develop and Use AI in a Responsible Way
By Virginia Dignum. Artificial Intelligence: Foundations, Theory, and Algorithms, 2019
705 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/bcc71fad6b7184084ef4439419da50f676d48a13
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- Vafa Ghazavi
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Citations in the corpus
- Beyond the individual: governing AI's societal harm (2021, unknown): “The former covers techniques that rely primarily on the codification of symbols and rules, based on which the system ‘reasons’ (using a top-down approach to design the system’s behaviour), whereas the latter covers techniques that rely primarily on large amounts of data, based on which the system ‘l”
- The Challenge of Value Alignment: from Fairer Algorithms to AI Safety (2021, background): “This instrumental conception of intelligence represents only one view drawn from a family of definitions one might endorse (Dignum, 2019; Cave, 2020).”
- A Framework for Evaluating and Disclosing the ESG Related Impacts of AI with the SDGs (2021, background): “Efforts to examine the ethical and social implications of AI, for example work on responsible AI [32] and AI4People [33], are also clearly related to the social and governance related SDGs.”
- Transparency in artificial intelligence (2020, background): “Thus, the interplay between AI technologies and societal values – the applied ethics, social and legal norms – underscores the importance of combining social scientific and contributions from the humanities to computer scientifically based AI research (see Dignum, 2019).”
- AI literacy and its implications for prompt engineering strategies (2024, background): “Consequently, equipping users with AI literacy might become a key factor in successfully integrating AI into higher education and future learning endeavors, enabling individuals to participate and act autonomously in a AI-infused world (Dignum, 2019).”