How AI can be a force for good

By Mariarosaria Taddeo, Luciano Floridi. 2018

623 citations recorded by the source corpus.

An ethical framework will help to harness the potential of AI while keeping humans in control Artificial intelligence (AI) is not just a new technology that requires regulation. It is a powerful force that is reshaping daily practices, personal and professional interactions, and environments. For the well-being of humanity it is crucial that this power is used as a force of good. Ethics plays a key role in this process by ensuring that regulations of AI harness its potential while mitigating its risks.

Subfields: Artificial Intelligence, Safety Research

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Citations in the corpus

The Ethics of AI Ethics: An Evaluation of Guidelines (2019, background): “This implies that the purposes for which AI systems are developed and applied are not in accordance with societal values or fundamental rights such as beneficence, non-maleficence, justice, and explicability (Taddeo and Floridi 2018; Pekka et al.”
Recommender systems and their ethical challenges (2020, background): “…individual users’ autonomy, by providing recommendations that nudge users in a particular direction, by attempting to “addict” them to some types of contents, or by limiting the range of options to which they are exposed (Burr et al. 2018; de Vries 2010; Koene et al. 2015; Taddeo and Floridi 2018).”
The ethics of AI in health care: A mapping review. (2020, background): “If harnessed effectively, such AI-clinician cooperation, where AI is used to provide comprehensive evidence-based clinical decision-support to the clinician (AI-Health), could offer great opportunities for the improvement of healthcare services and ultimately patients' health (Taddeo and Floridi, 20”
From What to How. An Overview of AI Ethics Tools, Methods and Research to Translate Principles into Practices (2019, methodology): “…DotEveryone’s Consequence Scanning Event: https://doteveryone.org.uk/project/consequence-scanning/ policymakers, citizens, developers and designers (Taddeo & Floridi, 2018) to foster the development of: (1) common knowledge and understanding; and (2) a common goal to be achieved from the…”
The global landscape of AI ethics guidelines (2019, background): “This focus is corroborated by a greater emphasis on preserving privacy, dignity, autonomy and individual freedom in spite of advances in AI rather than on actively promoting these principles 124 .”
Artificial Intelligence Regulation: A Meta-Framework for Formulation and Governance (2020, methodology): “Considering all those risks, establishing best practices for delegating and defining new moral responsibility attribution models is crucial in order to leverage the opportunities created by AI [7].”
The AI gambit: leveraging artificial intelligence to combat climate change—opportunities, challenges, and recommendations (2021, background): “A second set of risks concerns the erosion to human autonomy that some climate-focused AI systems may pose (Floridi and Cowls 2019; Taddeo and Floridi 2018).”
Evaluating the Quality of Machine Learning Explanations: A Survey on Methods and Metrics (2021, background): “…medicine and personalised medicine; in agriculture, ML can detect crop disease, and spray pesticide to crops with pinpoint accuracy and can help to save our forest ecosystems [1–4]; and, in scientiﬁc research, ML can fuse heterogeneous bibliographic information to efﬁciently extract knowledge [5].”
Exploring AI Ethics of ChatGPT: A Diagnostic Analysis (2023, background): “The objective of our study is not to provide a flawless, quantitative, and deterministic solution for designing a responsible language model application, echoing the history of scientific advancement[30, 31].”
A Systematic Literature Review of User Trust in AI-Enabled Systems: An HCI Perspective (2022, background): “…and maintaining user trust is the key to calibrating the user-AI relationship (Jacovi et al., 2021; Shin, 2021), achieving trust-worthy AI (Smith, 2019), and further unlocking the potential of AI for society (Bughin et al., 2018; Cheatham et al., 2019; Floridi et al., 2018; Taddeo & Floridi, 2018).”
How to Design AI for Social Good: Seven Essential Factors (2020, background): “Privacy is not a novel problem, but the centrality of personal data to many AI (and AI4SG) applications heightens its ethical significance and creates issues around consent (Taddeo and Floridi 2018a).”