AI and the Peripheries

As we program AI, can we ensure that today’s inequalities don’t become entrenched in algorithmic biases?

CAIDE’s AI and the Peripheries research theme focuses on the people pushed to the side in the digital world. The harms and benefits of AI are not equally distributed, and without careful consideration, AI and technology can be used to further discriminate against already marginalised communities.

Engagement and Policy

CAIDE, supported by the Department of Foreign Affairs and Trade (DFAT) through the Cyber and Critical Technology Cooperation Program and by the Menzies Foundation through the Ninian Stephen Law Program visited Hanoi, Viet Nam three times in 2023, with the intention of giving lawyers in Viet Nam the capacity to deal appropriately with emerging and critical technologies.

CAIDE have also worked with the National Academy of Legal Studies and Research University in India, and Ikigai Law, to establish ethical policy frameworks for AI and machine learning tools in digital healthcare, as part of an Indo-Australian partnership.

Susie Sheldrick’s research on advanced technology and rural small- and medium-sized enterprises (SMEs) was presented at the Oxford Internet Institute at the University of Oxford.

Dr Marc Cheong also spoke at BRIDGES-2023, the Second International Workshop on Bridging the Divides with Globally Engineered Software, in Papua New Guinea. Marc spoke specifically about diversity and inclusion with a focus on the PNG higher education sector.

Research

CAIDE’s research covers lots of examples of algorithmic bias, and deals with many marginalised communities. Some examples of such research include:

  • Tim Miller’s 2023 research regarding the efficacy of a mobile app for addressing the emotional needs of people experiencing homelessness
  • Tim Miller’s research directly on automation bias and artificial intelligence
  • Dr Simon Coghlan’s research regarding the interactions between AI and animals
  • CAIDE have also researched on the impact of AI on rural small- and medium-sized enterprises (SMEs), which was discussed at the Pacific Asia Conference on Information Systems.

Teaching

CAIDE’s undergraduate subject, AI, Ethics and the Law, taught by Prof Jeannie Marie Paterson, features many discussions of the peripheries in AI, especially regarding algorithmic bias. Specific examples included the bias in facial recognition technology to more accurately recognise white, male faces, than the faces of women or people of colour. Discussions centred around how these biases can be built into algorithms, or trained into algorithms by the specific data sets machines ‘learn’ from.

Research Projects