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Inclusion in AI: Is there a Singapore Model?
29 Sep 2022

In support of its mandate to stimulate discussion and research at the intersection of science, technology, and national security, the Future Issues and Technology (FIT) research cluster at RSIS organised a webinar on the challenges for artificial intelligence (AI) arising from inclusion. Inclusion here refers not only to the representativeness of data used to train AI-based systems, but also within the field itself, whether in terms of age, gender, and ethnicity, among other dimensions.

The webinar, which took place on 20 ... more

In support of its mandate to stimulate discussion and research at the intersection of science, technology, and national security, the Future Issues and Technology (FIT) research cluster at RSIS organised a webinar on the challenges for artificial intelligence (AI) arising from inclusion. Inclusion here refers not only to the representativeness of data used to train AI-based systems, but also within the field itself, whether in terms of age, gender, and ethnicity, among other dimensions.

The webinar, which took place on 20 October 2022, was the second in a series organised by FIT with support from the Centre of Excellence for National Security, RSIS. The previous webinar, held in July 2022, focused on obstacles to scaling AI. The panel comprised Dr Dorien Herremans, Assistant Professor, Singapore University of Technology and Design; and Dr Hallam Stevens, Professor of Interdisciplinary Studies, James Cook University, Australia. Dr Tamara Nair, Research Fellow, Centre for Non-Traditional Security Studies, RSIS, was the moderator.

The webinar’s premise followed from data highlighting that Singapore had one of the smallest gender gaps in AI, with women comprising around 28% of the AI workforce, which was higher than the global average. Is there a “Singapore model” that could be offered to the world, not just in terms of closing the gender gap but also for greater inclusion in AI?

The panellists discussed the knock-on impact for AI from limited representation in science, technology, engineering, and mathematics (STEM) education, tracing the challenge to the early childhood level and deliberating the role played by societal norms and the mindsets of parents.

The panel members also explored if Singapore could offer a space to develop a more inclusive alternative to the culture seen in technology companies and startups in the West. Although this seemed a worthwhile goal, the panellists noted that it would be difficult to shape the cultural context for people working in AI to make it more inclusive.

Regarding potential risks arising from greater inclusion, the panellists highlighted that trying to promote inclusion superficially could lead to hiring individuals without the right skills. This could reinforce negative stereotypes and work against building an inclusive culture.

Finally, the value of extending inclusion to society at large was discussed. A potential challenge in the Singapore context was that inclusion primarily focused on education and training, whereas it could be extended to address community participation and raising societal awareness.

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