CoChat
Sign Up
Cited by 245Ethics and Social Impacts of AIArtificial Intelligence ApplicationsImpact of AI and Big Data on Business and Society

The DOI matches its Crossref record; 0 of the 27 references it cites were found in a registry or an index.

Beyond the promise: implementing ethical AI

Open access
Eitel-Porter, Ray·2021·AI and Ethics
DOI 10.1007/s43681-020-00011-6
Open this paper in CoChat — free accountOpen PDF

Abstract

Artificial Intelligence (AI) applications can and do have unintended negative consequences for businesses if not implemented with care. Specifically, faulty or biased AI applications risk compliance and governance breaches and damage to the corporate brand. These issues commonly arise from a number of pitfalls associated with AI development, which include rushed development, a lack of technical understanding, and improper quality assurance, among other factors. To mitigate these risks, a growing number of organisations are working on ethical AI principles and frameworks. However, ethical AI principles alone are not sufficient for ensuring responsible AI use in enterprises. Businesses also require strong, mandated governance controls including tools for managing processes and creating associated audit trails to enforce their principles. Businesses that implement strong governance frameworks, overseen by an ethics board and strengthened with appropriate training, will reduce the risks associated with AI. When applied to AI modelling, the governance will also make it easier for businesses to bring their AI deployments to scale.

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 · 10.1007/s43681-020-00011-6

Cites

0 of 27 references verified0 citation errors · 27 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

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

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

  • The Institute for Ethical AI & Machine Learning: The responsible machine learning principles. https://www.ethical.institute/principles.html. Accessed 27 July 2020

    (n.d.)

    Unresolved

  • UNI Global Union: Top 10 principles for ethical artificial intelligence. https://www.thefutureworldofwork.org/media/35420/uni_ethical_ai.pdf (2017). Accessed 27 July 2020

    (n.d.)

    Unresolved

  • Microsoft: Responsible AI. https://www.microsoft.com/en-us/ai/responsible-ai?activetab=pivot1:primaryr6/. Accessed 27 July 2020

    (n.d.)

    Unresolved

  • Organisation for Responsible Business: What is responsible business. https://www.orbuk.org.uk/what-is-responsible-business/. Accessed 27 July 2020 and Online document Global Initiatives. Responsible Business. https://www.responsiblebusiness.com/. Accessed 27 July 2020

    (n.d.)

    Unresolved

  • Gartner: Gartner says nearly half of CIOs are planning to deploy artificial intelligence. https://www.gartner.com/en/newsroom/press-releases/2018-02-13-gartner-says-nearly-half-of-cios-are-planning-to-deploy-artificial-intelligence (2018). Accessed 27 July 2020

    (n.d.)

    Unresolved

  • Kanioura, A., Lucini, F.: Ready. Set. Scale. Accenture. https://www.accenture.com/us-en/insights/artificial-intelligence/scaling-enterprise-ai?src=SOMS&c=acn_glb_scalingenterpriexacttarget_11099764&n=emc_0120 (2019). Accessed 27 July 2020

    (n.d.)

    Unresolved

  • Accenture: AI ethics and governance. https://www.accenture.com/us-en/services/applied-intelligence/ai-ethics-governance. Accessed 27 July 2020

    (n.d.)

    Unresolved

  • Marr, B.: Is artificial intelligence dangerous? 6 AI risks everyone should know about. Forbes.https://www.forbes.com/sites/bernardmarr/2018/11/19/is-artificial-intelligence-dangerous-6-ai-risks-everyone-should-know-about/#5920f7dc2404(2018). Accessed 27 July 2020

    (n.d.)

    Unresolved

  • Dastin, J.: Amazon scraps secret AI recruiting tool that showed bias against women. Reuters. https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G (2018). Accessed 27 July 2020

    (n.d.)

    Unresolved

  • Hunt, E.: Tay, Microsoft's AI chatbot, gets a crash course in racism from Twitter. https://www.theguardian.com/technology/2016/mar/24/tay-microsofts-ai-chatbot-gets-a-crash-course-in-racism-from-twitter (2016). Accessed 27 July 2020

    (n.d.)

    Unresolved

Show all 27 references

Cited by

Sorted by citations

Items 201–245 of 245

Related

See all

Metadata

Authors
Eitel-Porter, R.
Affiliations
Accenture (United Kingdom) (GB)
Corresponding author
Eitel-Porter, Ray
Venue
AI and Ethics
Publisher
Springer Science and Business Media LLC
Published
2020-10-06
Volume
1
Issue
1
Pages
73-80
ISSN
  • 2730-5953 (ISSN-L)
  • 2730-5961
DOI
10.1007/s43681-020-00011-6
OpenAlex
W3092263108
Cited by
245
References
27
Citations by year
2026: 37 · 2025: 62 · 2024: 72 · 2023: 37 · 2022: 25 · 2021: 12
Type
journal article
Language
en
Open access
Licence
Locations
AI and Ethics (publishedVersion, cc-by)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
  • Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
Keywords
ethical AI, AI governance, responsible AI, algorithmic bias, AI risk management, AI ethics principles, ethics boards, audit trail

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