Olsen, Dennis (2026) The algorithmic gaze: AI, attention and the ethics of brand perception. Journal of Digital Media & Interaction. ISSN 2184-3120 (In Press)

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Abstract

This article critically examines how AI-supported visual evaluation tools – particularly predictive attention modelling software – are reshaping brand perception and design decision-making in hyperdigital environments. Drawing on a two-phase qualitative study involving practitioners and subject expert, it introduces the concept of the algorithmic gaze to interrogate how these systems simulate, encode and prescribe normative visual hierarchies. The analysis reveals that while such tools offer operational efficiency, they often obscure cultural nuance, misrepresent audience en-gagement and displace human interpretive agency. Practitioner interviews highlight tensions be-tween usability and trust, especially among junior professionals, while expert reflections situate these dynamics within broader discourses of epistemic authority, ethical design and algorithmic bias. These insights are contextualised by the rhetorical framing of AI tools as scientifically author-itative, which shapes practitioner expectations and contributes to a culture of deference to data. The article synthesises its findings through the Interpretive Stewardship heuristic – a model com-prising three interlinked dimensions that offer a scaffold for ethical engagement with AI tools in branding. It argues that branding must be reframed as a site of cultural negotiation rather than computational optimisation and calls for regulatory, institutional and design-level commitments to transparency, inclusivity and reflexive practice. These findings contribute to emerging debates in branding, media theory and AI ethics.

Item Type:	Article
Keywords:	Algorithmic gaze, AI ethics, Infosphere, Interpretive Stewardship, Feminist data ethics, Brand percep-tion
Date Deposited:	18 Mar 2026
URI:	https://repository.uwl.ac.uk/id/eprint/14769
Sustainable Development Goals:	Goal 9: Industry, Innovation, and Infrastructure

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