Beyond the individual: governing AI's societal harm

By Nathalie A. Smuha. 2021

131 citations recorded by the source corpus.

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Subfields: Artificial Intelligence, Cognitive Neuroscience, Safety Research, Safety, Robustness & Interpretability

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Su Lin Blodgett
2. Alexandra Sasha Luccioni
3. Irene Solaiman
4. Zeerak Talat
5. Dylan Baker
6. Margaret Mitchell
7. Yacine Jernite
8. Negar Rostamzadeh

In Cognitive Neuroscience

1. Irene Solaiman
2. Zeerak Talat
3. Su Lin Blodgett
4. Margaret Mitchell
5. Sara Hooker

In Safety Research

1. Irene Solaiman
2. Andrew Smart
3. Marie-Therese Png
4. Zeerak Talat
5. Yacine Jernite
6. Negar Rostamzadeh
7. Alexandra Sasha Luccioni
8. Su Lin Blodgett

In Safety, Robustness & Interpretability

1. Irene Solaiman
2. Su Lin Blodgett
3. Dylan Baker
4. Zeerak Talat
5. Negar Rostamzadeh
6. Kathryn Henne
7. Andrew Smart
8. Marie-Therese Png

Citations in the corpus

• Evaluating the Social Impact of Generative AI Systems in Systems and Society (2023, background): “Smuha [226] proposes accountability and monitoring mechanisms at a public oversight level, for example mandatory impact assessments of AI systems which incorporates opportunities for societal feedback.”
• Sociotechnical Harms: Scoping a Taxonomy for Harm Reduction (2022, background): “Scholars in human-computer interaction (HCI), machine learning, Science and Technology Studies (STS), and related disciplines have identified various harms from digital technologies (e.g., [9, 104, 169, 170, 182]).”
• Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reduction (2022, background): “More generally, these harms may erode democracy [97], through election interference or censorship [207].”