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Built heritage has been both subject and product of a gaze that has been sustained through moments of colonial fixation on ruins and monuments, technocratic examination and representation, and fetishisation by a global tourist industry. We argue that the recent proliferation of machine learning and vision technologies create new scopic regimes for heritage: storing and retrieving existing images from vast digital archives, and further imparting their own distortions upon this gaze. We introduce the term ‘ machinic gaze’ to conceptualise the reconfiguration of heritage representation via artificial intelligence (AI) models. To explore how this gaze reframes heritage, we deploy an image-text-image pipeline that reads, interprets, and resynthesizes images of several UNESCO World Heritage Sites. Employing two concepts from media studies— heteroscopia and anamorphosis—we describe the reoriented perspective that machine vision systems introduce. We propose that the machinic gaze highlights the artifice of the human gaze and its underlying assumptions and practices that combine to form established notions of heritage.
Arora et al. (2024) studied this question.
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