(Re)framing Built Heritage through the Machinic Gaze

TL;DR

This paper explores how machine learning and vision technologies create a new 'machinic gaze' that reinterprets and reshapes the visual representation of built heritage, revealing underlying assumptions and artifices of traditional perspectives.

Contribution

It introduces the concept of the 'machinic gaze' to analyze how AI-driven image processing reconfigures heritage representation, combining media theory with practical image analysis of UNESCO sites.

Findings

The machinic gaze exposes the artificiality of traditional heritage representations.

AI models introduce new distortions and perspectives in heritage imagery.

The approach reveals underlying cultural assumptions in heritage visualization.

Abstract

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.