CoChat
Sign Up
Cited by 69Ethics and Social Impacts of AIArtificial Intelligence ApplicationsDigitalization, Law, and Regulation

The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index.

Artificial Intelligence Incidents & Ethics A Narrative Review

Open access
Nasim, Syeda Faiza, Muhammad Rizwan Ali, Umme Kulsoom·2022·International Journal of Technology, Innovation and Management (IJTIM)
DOI 10.54489/ijtim.v2i2.80
Open this paper in CoChat — free accountOpen PDF

Abstract

There has been a lot of media debate about “Artificial Intelligence (AI) Ethics” nowadays and many scientists and researchers have shared their views on this topic. As technology is evolving, security issues are also emerging in new forms. Machines should be ethical, and the “Build and Design” of such machines should be based on ethics. Infact, AI must have Ethics as a part of design within the software code, just like security measures are encoded within. In this review paper, statistics of AI incidents and areas are presented along with the social impact. Using the online AI Incident Database, some areas of AI applications have been identified, which shows unethical use of AI. Applications like Language and Computer vision models, intelligent robots and autonomous driving are in top ranking. Ethical issues also appear in various forms like incorrect use of technology, racism, non-safety and malicious algorithms with biasness. Data collection has helped to identify the AI ethical issues based on Time, Geographic Locations, Application Areas, and Classifications

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.54489/ijtim.v2i2.80

Cites

34 of 34 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Flagged first, then by citations

Research works printed but not linked: 2

  1. [23]23. M. T. Alshurideh et al., "Fuzzy assisted human resource management for supply chain management issues," Ann. Oper. Res., pp. 1-19, 2022.
  2. [33]33. V. Victoria, "IMPACT OF PROCESS VISIBILITY AND WORK STRESS TO IMPROVE SERVICE QUALITY: EMPIRICAL EVIDENCE FROM DUBAI RETAIL INDUSTRYIMPACT OF PROCESS VISIBILITY AND WORK STRESS TO IMPROVE SERVICE QUALITY: EMPIRICAL EVIDENCE FROM DUBAI RETAIL INDUSTRY," Int. J. Technol. Innov. Manag., vol. 2, no. 1, 2022.

Cited by

Sorted by citations

Related

Metadata

Authors
Nasim, S. F., Ali, M. R., & Kulsoom, U.
Affiliations
NED University of Engineering and Technology (PK)
ORCID
Venue
International Journal of Technology, Innovation and Management (IJTIM)
Publisher
Global Academic Forum on Technology, Innovation And Management (GAFTIM)
Published
2022-10-27
Volume
2
Issue
2
ISSN
2789-777X (ISSN-L)
DOI
10.54489/ijtim.v2i2.80
OpenAlex
W4310547838
Cited by
69
References
34
Citations by year
2026: 12 · 2025: 10 · 2024: 39 · 2023: 8
FWCI
2.72
Type
journal article
Language
en
Open access
Locations
International Journal of Technology Innovation and Management (IJTIM) (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
  • Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
  • Social Sciences › Law › Digitalization, Law, and Regulation
Keywords
AI ethics, AI incidents, AI Incident Database, algorithmic bias, societal impact of AI, language models, computer vision models, intelligent robots, autonomous driving, racism, AI safety

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review