When good isn't good enough.

By John R. Clark. 2014

70 citations recorded by the source corpus.

Subfields: Emergency Medical Services, Medical Laboratory Technology, Pharmacy, AI Ethics, Fairness & Society

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Citations in the corpus

Language (Technology) is Power: A Critical Survey of “Bias” in NLP (2020, background): “whether they should be built at all, and (b) keeping development and deployment decisions in the hands of technologists (Bennett and Keyes, 2019; Cifor et al., 2019; Green, 2019; Katell et al., 2020).”
MERLOT RESERVE: Neural Script Knowledge through Vision and Language and Sound (2022, background): “On the other hand, this broad research agenda, and perhaps all of computer vision for that matter, might enable large actors to do just that [132]; which might not be addressable through purely technical solutions [51].”
MERLOT: Multimodal Neural Script Knowledge Models (2021, background): “It seems unlikely that purely technological fixes and defenses – which themselves can be problematic [33] – could resolve these dynamics.”
The Values Encoded in Machine Learning Research (2021, background): “Although a plethora of work exists on sources of harm that can arise in relation to ML research [7, 15, 25, 28, 60], we observe that these discussions are ignored in these influential conference publications.”
Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence (2020, methodology): “2016a; Benjamin 2019; Buolamwini and Gebru 2018; Lum and Isaac 2016; Noble 2018; Eubanks 2018), exploitative or extractive data practices (Gray and Suri 2019), and applications of AI that dispossess the identity and resources of vulnerable populations (Green 2019; Keyes 2018; Hanna et al. 2019; Star”
Evaluating CLIP: Towards Characterization of Broader Capabilities and Downstream Implications (2021, background): “We need to expand our deﬁnitions of ‘better’ models to also include their possible downstream impacts, uses etc. [10], [21] We believe one step forward is community exploration to further characterize models like CLIP and holistically develop qualitative and quantitative evaluations to assess the…”
Give Me Convenience and Give Her Death: Who Should Decide What Uses of NLP are Appropriate, and on What Basis? (2020, background): “The conversation of what social good is, though, remains an open one (Green, 2019).”
Just What do You Think You're Doing, Dave?' A Checklist for Responsible Data Use in NLP (2021, background): “While the NLP community ideally aims to improve the world, the real world is far more complex than the binary categories of ‘good’ and ‘bad’ (Green, 2019).”
TuringAdvice: A Generative and Dynamic Evaluation of Language Use (2021, background): “There are almost certainly better non-technical solutions to ensure mentorship and legal advice for all (Green, 2019).”