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Technology and Regulation, 2023 The EU has proposed harmonized rules on artificial intelligence (AI Act) and a directive on adapting non-contractual civil liability rules to AI (AI liability directive) due to increased demand for trustworthy AI.
Jacob Livingston Slosser +2 more
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Editorial: Trustworthy AI for healthcare [PDF]
Frontiers in Digital HealthOleg Agafonov +3 more
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From theory to practice: Harmonizing taxonomies of trustworthy AI [PDF]
Health Policy OpenThe increasing capabilities of AI pose new risks and vulnerabilities for organizations and decision makers. Several trustworthy AI frameworks have been created by U.S. federal agencies and international organizations to outline the principles to which AI
Christos A. Makridis +5 more
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Advocating for trust in and trustworthy AI to transform evidence synthesis [PDF]
Environmental EvidenceThe global demand for high-quality, robust and up-to-date evidence to guide decision-making has never been higher. The vast quantity of scientific literature being produced and made accessible presents an unparalleled opportunity for evidence-based ...
Isabel K. Fletcher
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The unmet promise of trustworthy AI in healthcare: why we fail at clinical translation [PDF]
Frontiers in Digital HealthArtificial intelligence (AI) has the potential to revolutionize healthcare, for example via decision support systems, computer vision approaches, or AI-based prevention tools. Initial results from AI applications in healthcare show promise but are rarely
Valerie K. Bürger +6 more
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Commentary: Trustworthy and ethical AI in digital mental healthcare – wishful thinking or tangible goal? [PDF]
Internet InterventionsThe use of AI in digital mental healthcare promises to make treatments more effective, accessible, and scalable than ever before. At the same time, the use of AI opens a myriad of ethical concerns, including the lack of transparency, the risk of bias ...
Ellen Svensson +2 more
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A trustworthy AI reality-check: the lack of transparency of artificial intelligence products in healthcare [PDF]
Frontiers in Digital HealthTrustworthy medical AI requires transparency about the development and testing of underlying algorithms to identify biases and communicate potential risks of harm. Abundant guidance exists on how to achieve transparency for medical AI products, but it is
Jana Fehr +9 more
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Environmental Data Science, 2022 Given the growing use of Artificial intelligence (AI) and machine learning (ML) methods across all aspects of environmental sciences, it is imperative that we initiate a discussion about the ethical and responsible use of AI. In fact, much can be learned
Amy McGovern +3 more
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Environmental Data Science, 2023 Complex machine learning architectures and high-dimensional gridded input data are increasingly used to develop high-performance geoscience models, but model complexity obfuscates their decision-making strategies.
Evan Krell +4 more
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Machine Learning with Applications, 2021 The reduction of visibility adversely affects land, marine, and air transportation. Thus, the ability to skillfully predict fog would provide utility.
Hamid Kamangir +6 more
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