  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 aglobal
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 its visual representation. We introduce the term
`machinic gaze' to conceptualise the reconfiguration of heritage representation
via 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.

Computers and Society