Evidence map›Paper›PMID 30767109›Full record

SynthesisScience and engineering ethics2020

Artificial Intelligence Crime: An Interdisciplinary Analysis of Foreseeable Threats and Solutions.

Thomas C King, Nikita Aggarwal, Mariarosaria Taddeo, Luciano Floridi

Abstract readSystematic Review
In one paragraph

Synthesis in Science and engineering ethics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
–field-weighted citation impact
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

19 citing papers in PubMed.

  1. Article
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  3. Review
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  7. Article
  8. Hammering with the telescope.Frontiers in artificial intelligence · 2022
    Article
  9. Article
  10. Article
  11. Bad machines corrupt good morals.Nature human behaviour · 2021
    Review
  12. The automaton as a surgeon: the future of artificial intelligence in emergency and general surgery.European journal of trauma and emergency surgery : official publication of the European Trauma Society · 2021
    Review
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
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

4 authors.

Thomas C KingOxford Internet Institute, University of Oxford, 1 St Giles, Oxford, OX1 3JS, UK.ORCID 0000-0001-6610-8098
Nikita AggarwalOxford Internet Institute, University of Oxford, 1 St Giles, Oxford, OX1 3JS, UK.
Mariarosaria TaddeoOxford Internet Institute, University of Oxford, 1 St Giles, Oxford, OX1 3JS, UK.
Luciano FloridiOxford Internet Institute, University of Oxford, 1 St Giles, Oxford, OX1 3JS, UK. luciano.floridi@oii.ox.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) research and regulation seek to balance the benefits of innovation against any potential harms and disruption. However, one unintended consequence of the recent surge in AI research is the potential re-orientation of AI technologies to facilitate criminal acts, term in this article AI-Crime (AIC). AIC is theoretically feasible thanks to published experiments in automating fraud targeted at social media users, as well as demonstrations of AI-driven manipulation of simulated markets. However, because AIC is still a relatively young and inherently interdisciplinary area-spanning socio-legal studies to formal science-there is little certainty of what an AIC future might look like. This article offers the first systematic, interdisciplinary literature analysis of the foreseeable threats of AIC, providing ethicists, policy-makers, and law enforcement organisations with a synthesis of the current problems, and a possible solution space.

Indexed as

Social MediaArtificial IntelligenceCommerceCrimeDrug TraffickingForecastingFraudHumansInterdisciplinary ResearchLiability, LegalSex OffensesAI and lawAI-CrimeArtificial intelligenceDual-useEthicsMachine learning

Identifiers

PMID30767109
PMCPMC6978427

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.