In a time of fast and unprecedent technological change, this research critically
examines how image generative systems such as Midjourney reproduce and amplify
racial bias. Based in Australia and centring Critical Race Theory (CRT), this thesis
interrogates the intersections of race, representation, and technology, highlighting
how visual outputs sustain Eurocentric ideals and structural inequalities.
Rather than focusing on the mechanics of AI, this thesis foregrounds the
permanence of racism, antiblackness, and evolving notions of Australianness,
examining how these are encoded into datasets and reflected in generated imagery.
Through semi-structured interviews with six Australian university students, it explores
lived experiences that reveal tensions between dominant visual narratives and
personal realities, from depictions of white femininity as ideal beauty to portrayals of
Aboriginal men shaped by colonial and racist stereotypes. This work does not merely
highlight the failings of artificial intelligence as we have it today; it is an invitation to
engage with critical race theory as well as a call upon developers, policymakers, and
educators to interrogate the structures that allow these biases to persist.