Evidence map›Paper›PMID 36305955›Full record

ArticleScience and engineering ethics2022

Global Catastrophic Risk and the Drivers of Scientist Attitudes Towards Policy.

Christopher Nathan, Keith Hyams

Open access · hybridAbstract read
In one paragraph

Article in Science and engineering ethics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 39% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 4 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Christopher NathanPolitics and International Studies, University of Warwick, Coventry, UK.
Keith HyamsPolitics and International Studies, University of Warwick, Coventry, UK. K.D.Hyams@warwick.ac.uk.ORCID http://orcid.org/0000-0003-3755-646X
University of Warwick · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An anthropogenic global catastrophic risk is a human-induced risk that threatens sustained and wide-scale loss of life and damage to civilisation across the globe. In order to understand how new research on governance mechanisms for emerging technologies might assuage such risks, it is important to ask how perceptions, beliefs, and attitudes towards the governance of global catastrophic risk within the research community shape the conduct of potentially risky research. The aim of this study is to deepen our understanding of emerging technology research culture as it relates to global catastrophic risks, and to shed new light on how new research governance mechanisms might be developed. We analyse in-depth interviews with leading AI and biotech researchers both from universities and the private sector. We develop new insights in terms of four salient themes. First, 'engineering mindset', which highlights the premium placed by many interviewees on pursuing interesting research about the physical world for its own sake. Second, 'self-government', which looks at how self-regulation of technological development currently occurs. Third, 'pure incentives', focussing on how career and other incentives shapes research. Fourth, 'norms and persuasion', which examines the role of moral considerations in guiding the research choices of scientists. We end by considering the implications of these findings for future research on governance of anthropogenic global catastrophic risk.

Indexed as

AttitudeGovernmentHumansPolicyPrivate SectorResearch PersonnelGlobal catastrophePolicyResearch cultureResponsible Research and InnovationRisk

Identifiers

PMID36305955
PMCPMC9614746
OpenAlexW4307839154

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.