article · Humanities and Social Sciences Communications
Artificial intelligence tools in the cosmetics sector often promise personalisation but risk standardising beauty norms and erasing traditional, vernacular knowledge. An examination of traditional olive oil skin care in Morocco demonstrates that beauty practices rely on sensory, affective, tactile, and relational intelligence rather than abstract data extraction. In an experiment testing four large language models with increasingly rich contextual prompts regarding Moroccan olive oil routines, the systems generated culturally informed answers yet consistently failed to capture embodied and sensory dimensions. This shows an ontological divide between algorithmic computation and situated human knowledge. To counter algorithmic bias and digital reductionism, AI systems in beauty technology should be co-designed with local communities as fragile bridges. Such designs must record local conditions, allow contestability, and explicitly acknowledge the practical limitations of algorithmic processing.
As beauty technology expands, algorithms risk replacing nuanced, community-held heritage with generic commercial standards. Recognising traditional care practices as valid forms of everyday data science ensures that cultural knowledge is preserved rather than flattened by digital tools. It also challenges superficial claims of technological personalisation by highlighting the inherent limits of algorithmic recommendation engines.
This early-stage conceptual and empirical research applies to beauty technology developers, cosmetics brands, and algorithmic designers exploring personalised skin care tools. Rather than attempting full digital translation of traditional care practices, the proposed fragile bridges framework suggests building software that documents local context, includes contestability mechanisms, and avoids exaggerated claims of personalisation. Practical adoption remains distant, as existing models require substantial architectural rethinking to respect situated and embodied traditions.
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This article develops a critical reflection on the growing integration of artificial intelligence (AI) in the cosmetics industry, drawing on the philosophy of technology, the sociology of situated knowledge, and an analysis of the heritage of body care practices. Using the emblematic example of the traditional use of olive oil in skin care practices in Morocco, it questions how AI systems, under the guise of personalization, reproduce standardized aesthetic norms and contribute to the erasure of perceptual, affective, and vernacular knowledge, while revealing algorithmic biases. Beauty is understood as a form of knowledge rooted in cultures, carried by knowledge transmitted through attention to the body, narratives, and sociocultural contexts. This perspective is part of an epistemology of the sensory and the relational, which highlights the roots of these practices in local forms of validation and regulation, far removed from the logic of abstraction inherent in contemporary technologies. Whereas AI operates by extracting pixels, textures, or hues, traditional cosmetics mobilize tactile, memory-based, and relational intelligence. To put these claims to empirical test, a prompting experiment was conducted with four large language models, asking them to advise on Moroccan olive oil-based care practices with progressively richer contextual information. The results reveal that even when models produce culturally informed responses, they remain structurally incapable of accessing the embodied, relational, and sensory dimensions of these practices, confirming that the gap between algorithmic knowing and situated knowledge is ontological rather than technical. We advocate for a more equitable, localized AI in cosmetics that is attentive to local contexts, co-constructed with communities, respectful of ecologies, and open to invisible voices. Rather than attempting to translate vernacular knowledge into digital protocols, we propose the concept of fragile bridges: AI systems designed to document the conditions under which situated practices emerge, to integrate contestability mechanisms, and to remain transparent about what algorithmic formalization cannot carry. We propose three conceptual shifts, namely reading cosmetics as embodied intelligence; recognizing locally rooted feminine knowledge as a form of everyday data science; and conducting a systemic critique of the AI washing logic that structures beauty tech.
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DOI: 10.1057/s41599-026-08720-9
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