The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
The rising tide of artificial intelligence and business automation: Developing an ethical framework
Abstract
Recent advancements in robotics, artificial intelligence, machine learning, and sensors now enable machines to automate activities that once seemed safe from disruption—including tasks that rely on higher-level thinking, learning, tacit judgment, emotion sensing, and even disease detection. Despite these advancements, the ethical issues of business automation and artificial intelligence—and who will be affected and how—are less understood. In this article, we clarify and assess the cultural and ethical implications of business automation for stakeholders ranging from laborers to nations. We define business automation and introduce a novel framework that integrates stakeholder theory and social contracts theory. By integrating these theoretical models, our framework identifies the ethical implications of business automation, highlights best practices, offers recommendations, and uncovers areas for future research. Our discussion invites firms, policymakers, and researchers to consider the ethical implications of business automation and artificial intelligence when approaching these burgeoning and potentially disruptive business practices.
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.
Integrity signals
Registry
Cites
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.
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
Maslow, A. H. (1943) · Psychological Review · doi:10.1037/h0054346 · Cited by 21,563
The future of employment: How susceptible are jobs to computerisation?
Frey, C. B., & Osborne, M. A. (2017) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2016.08.019 · Cited by 8,727
Why Are There Still So Many Jobs? The History and Future of Workplace Automation
Autor, D. H. (2015) · Journal of Economic Perspectives · doi:10.1257/jep.29.3.3 · Cited by 3,917
Explaining Job Polarization: Routine-Biased Technological Change and Offshoring
Goos, M., Manning, A., & Salomons, A. (2014) · American Economic Review · doi:10.1257/aer.104.8.2509 · Cited by 2,111
Social contracts and marketing ethics
Dunfee, T. W., Smith, N. C., & Ross, W. T. (1999) · Journal of Marketing · doi:10.1177/002224299906300302 · Cited by 370
Katz, L., & Margo, R. (2013) · doi:10.3386/w18752 · Cited by 202
Cited by
The Ethical Implications of Using Artificial Intelligence in Auditing
Munoko, I., Brown-Liburd, H. L., & Vasarhelyi, M. (2020) · Journal of Business Ethics · doi:10.1007/s10551-019-04407-1 · Cited by 621
Artificial intelligence in business: State of the art and future research agenda
Loureiro, S. M. C., Guerreiro, J., & Tussyadiah, I. (2021) · Journal of Business Research · doi:10.1016/j.jbusres.2020.11.001 · Cited by 554
Ethical framework for Artificial Intelligence and Digital technologies
Ashok, M., Madan, R., Joha, A., & Sivarajah, U. (2022) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2021.102433 · Cited by 469
The Ethical Implications of Artificial Intelligence (AI) For Meaningful Work
Bankins, S., & Formosa, P. (2023) · Journal of Business Ethics · doi:10.1007/s10551-023-05339-7 · Cited by 448
Artificial Intelligence Regulation: A framework for governance
de Almeida, P. G. R., dos Santos, C. D., & Farias, J. S. (2021) · Ethics and Information Technology · doi:10.1007/s10676-021-09593-z · Cited by 395
Metadata
- Authors
- Wright, S. A., & Schultz, A. E.
- Venue
- Business Horizons
- Publisher
- Elsevier BV
- Published
- 2018-11
- Volume
- 61
- Issue
- 6
- Pages
- 823-832
- ISSN
- 0007-6813 (ISSN-L)
- OpenAlex
- W2891212971
- Cited by
- 246
- References
- 6
- FWCI
- 36.11
- Type
- journal article
- Language
- en
- Open access
- closed
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: The rising tide of artificial intelligence and business automation: Developing an ethical framework. https://app.cochat.ai/papers/10.1016/j.bushor.2018.07.001
- The paper
- Wright, S. A., & Schultz, A. E. (2018). The rising tide of artificial intelligence and business automation: Developing an ethical framework. Business Horizons. https://doi.org/10.1016/j.bushor.2018.07.001
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.