Ethical AI in Unregulated Environments: A Qualitative Empirical Study
(2025) AMICS 2025- Abstract
- This study investigates the incentives and barriers influencing AI ethics adoption in unregulated environments, drawing on semi‐structured interviews with AI professionals in Bangladesh. Our findings reveal that external pressures, such as international client requirements, drive companies to implement ethical measures, yielding both economic benefits and enhanced reputation. Conversely, tight deadlines, short-term ROI pressures, and weak local oversight hinder ethical practices, often leading to entrenched insecure methods that create negative algorithmic imprints. Our research empirically validates aspects of the Holistic Return on Ethics (HROE) framework, showing that ethical investments produce tangible and
intangible returns. The... (More) - This study investigates the incentives and barriers influencing AI ethics adoption in unregulated environments, drawing on semi‐structured interviews with AI professionals in Bangladesh. Our findings reveal that external pressures, such as international client requirements, drive companies to implement ethical measures, yielding both economic benefits and enhanced reputation. Conversely, tight deadlines, short-term ROI pressures, and weak local oversight hinder ethical practices, often leading to entrenched insecure methods that create negative algorithmic imprints. Our research empirically validates aspects of the Holistic Return on Ethics (HROE) framework, showing that ethical investments produce tangible and
intangible returns. The study also highlights that, in resource‐constrained settings, personal moral duty and managerial leadership significantly affect ethical decision-making. Our findings contribute to the literature by shedding light on how, in low-regulation contexts, AI practitioners pragmatically translate abstract ethical principles into operational practices shaped by incentives and constraints. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/edab5a2a-8cb4-4875-bc58-59d48baf9608
- author
- Elahi, Tawfique ; Srinivasa, Hema and Emruli, Blerim LU
- organization
- publishing date
- 2025
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- AMCIS 2025 Proceedings
- article number
- 1144
- publisher
- Americas Conference on Information Systems (AMCIS)
- conference name
- AMICS 2025
- conference location
- Montreal, Canada
- conference dates
- 2025-08-14 - 2025-08-16
- language
- English
- LU publication?
- yes
- id
- edab5a2a-8cb4-4875-bc58-59d48baf9608
- alternative location
- https://aisel.aisnet.org/amcis2025/sig_odis/sig_odis/25/
- date added to LUP
- 2025-09-08 10:56:46
- date last changed
- 2025-09-10 08:31:32
@inproceedings{edab5a2a-8cb4-4875-bc58-59d48baf9608,
abstract = {{This study investigates the incentives and barriers influencing AI ethics adoption in unregulated environments, drawing on semi‐structured interviews with AI professionals in Bangladesh. Our findings reveal that external pressures, such as international client requirements, drive companies to implement ethical measures, yielding both economic benefits and enhanced reputation. Conversely, tight deadlines, short-term ROI pressures, and weak local oversight hinder ethical practices, often leading to entrenched insecure methods that create negative algorithmic imprints. Our research empirically validates aspects of the Holistic Return on Ethics (HROE) framework, showing that ethical investments produce tangible and<br/>intangible returns. The study also highlights that, in resource‐constrained settings, personal moral duty and managerial leadership significantly affect ethical decision-making. Our findings contribute to the literature by shedding light on how, in low-regulation contexts, AI practitioners pragmatically translate abstract ethical principles into operational practices shaped by incentives and constraints.}},
author = {{Elahi, Tawfique and Srinivasa, Hema and Emruli, Blerim}},
booktitle = {{AMCIS 2025 Proceedings}},
language = {{eng}},
publisher = {{Americas Conference on Information Systems (AMCIS)}},
title = {{Ethical AI in Unregulated Environments: A Qualitative Empirical Study}},
url = {{https://aisel.aisnet.org/amcis2025/sig_odis/sig_odis/25/}},
year = {{2025}},
}