Separating the Art from the Algorithm: Detecting Moral Decoupling in Consumer Discourse About Generative AI

Onuchukwu Joseph Chimezie, Julius Sechang Mboli
Proceedings of the Fourth UK AI Conference 2026, PMLR 348:31-41, 2026.

Abstract

Some consumers who learn that a generative AI tool was trained on creative work taken without consent condemn the practice and stop using it. Others condemn it and keep using it. The second response is moral decoupling: separating judgements about wrongdoing from judgements about usefulness. The construct is established in laboratory research but has not been measured in naturally occurring discourse. We present a stance detection study of 7,371 Reddit posts from three professional communities differently exposed to generative AI. Each post is human-annotated on two axes, stance toward AI content and type of justification, with decoupling operationalised as a supportive stance co-occurring with explicit ethical acknowledgement. Across five calibration rounds, two annotators reached Cohen’s kappa of 0.654 on stance and 0.621 on argument type; GPT-4o, given the same guidelines, reached 0.058 and 0.209 and never used the MIXED label. Fine-tuned RoBERTa reached macro-F1 of 0.63 and 0.82. Moral positions differ sharply across communities (V = 0.23), and among engaged posts the decoupling-coupling balance differs too (V = 0.15). Marketers rarely engage morally at all, whereas artists produce most moral reasoning and resolve it against the tools three times in four. Involvement governs primarily whether ethical evaluation happens; secondarily, which way it falls.

Cite this Paper

BibTeX
@InProceedings{pmlr-v348-chimezie26a, title = {Separating the Art from the Algorithm: Detecting Moral Decoupling in Consumer Discourse About Generative AI}, author = {Chimezie, Onuchukwu Joseph and Mboli, Julius Sechang}, booktitle = {Proceedings of the Fourth UK AI Conference 2026}, pages = {31--41}, year = {2026}, editor = {Benford, Alistair and Büyükateş, Baturalp and Cabrera, Christian and Kiden, Sarah and Salili-James, Arianna and Zakka, Vincent and Zhou, Feng}, volume = {348}, series = {Proceedings of Machine Learning Research}, month = {29--30 Sep}, publisher = {PMLR}, pdf = {https://raw.githubusercontent.com/mlresearch/v348/main/assets/chimezie26a/chimezie26a.pdf}, url = {https://proceedings.mlr.press/v348/chimezie26a.html}, abstract = {Some consumers who learn that a generative AI tool was trained on creative work taken without consent condemn the practice and stop using it. Others condemn it and keep using it. The second response is moral decoupling: separating judgements about wrongdoing from judgements about usefulness. The construct is established in laboratory research but has not been measured in naturally occurring discourse. We present a stance detection study of 7,371 Reddit posts from three professional communities differently exposed to generative AI. Each post is human-annotated on two axes, stance toward AI content and type of justification, with decoupling operationalised as a supportive stance co-occurring with explicit ethical acknowledgement. Across five calibration rounds, two annotators reached Cohen’s kappa of 0.654 on stance and 0.621 on argument type; GPT-4o, given the same guidelines, reached 0.058 and 0.209 and never used the MIXED label. Fine-tuned RoBERTa reached macro-F1 of 0.63 and 0.82. Moral positions differ sharply across communities (V = 0.23), and among engaged posts the decoupling-coupling balance differs too (V = 0.15). Marketers rarely engage morally at all, whereas artists produce most moral reasoning and resolve it against the tools three times in four. Involvement governs primarily whether ethical evaluation happens; secondarily, which way it falls.} }
Endnote
%0 Conference Paper %T Separating the Art from the Algorithm: Detecting Moral Decoupling in Consumer Discourse About Generative AI %A Onuchukwu Joseph Chimezie %A Julius Sechang Mboli %B Proceedings of the Fourth UK AI Conference 2026 %C Proceedings of Machine Learning Research %D 2026 %E Alistair Benford %E Baturalp Büyükateş %E Christian Cabrera %E Sarah Kiden %E Arianna Salili-James %E Vincent Zakka %E Feng Zhou %F pmlr-v348-chimezie26a %I PMLR %P 31--41 %U https://proceedings.mlr.press/v348/chimezie26a.html %V 348 %X Some consumers who learn that a generative AI tool was trained on creative work taken without consent condemn the practice and stop using it. Others condemn it and keep using it. The second response is moral decoupling: separating judgements about wrongdoing from judgements about usefulness. The construct is established in laboratory research but has not been measured in naturally occurring discourse. We present a stance detection study of 7,371 Reddit posts from three professional communities differently exposed to generative AI. Each post is human-annotated on two axes, stance toward AI content and type of justification, with decoupling operationalised as a supportive stance co-occurring with explicit ethical acknowledgement. Across five calibration rounds, two annotators reached Cohen’s kappa of 0.654 on stance and 0.621 on argument type; GPT-4o, given the same guidelines, reached 0.058 and 0.209 and never used the MIXED label. Fine-tuned RoBERTa reached macro-F1 of 0.63 and 0.82. Moral positions differ sharply across communities (V = 0.23), and among engaged posts the decoupling-coupling balance differs too (V = 0.15). Marketers rarely engage morally at all, whereas artists produce most moral reasoning and resolve it against the tools three times in four. Involvement governs primarily whether ethical evaluation happens; secondarily, which way it falls.
APA
Chimezie, O.J. & Mboli, J.S.. (2026). Separating the Art from the Algorithm: Detecting Moral Decoupling in Consumer Discourse About Generative AI. Proceedings of the Fourth UK AI Conference 2026, in Proceedings of Machine Learning Research 348:31-41 Available from https://proceedings.mlr.press/v348/chimezie26a.html.

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