Its government released an AI strategy in 2018, identifying areas of focus in agriculture, health and education. The money will support projects in fundamental AI research, translational research, and industry– research collaborations. 17 Its goal is to propel ‘Singapore as a leader in developing and deploying scalable, impactful AI solutions, in key sectors of high value and relevance to our citizens and businesses.’ The Singaporean Government has supported the strategy with funding totalling S$680 million (~A$695 million). Singapore released its National AI Strategy in 2019. 16 The strategy includes nine plans to drive advancements in the AI ecosystem, AI use and people-centred AI. In South Korea, the government allocated ₩1.7 trillion (~A$1.1 billion) in 2020 for data, networks and AI under its National Strategy for Artificial Intelligence. 15 It released its National AI Strategy in September 2021-a ‘10-year plan to make Britain a global AI superpower’.
In 2018, the UK pumped nearly £1 billion (~A$1.87 billion) into AI research. 14 The strategy sets ambitious goals to attract and retain world-class AI researchers, nurture a collaborative AI ecosystem, support national AI initiatives, and contextualise AI work in its ethical and societal implications. The Canadian Government announced a national AI plan in 2017, investing C$125 million (~A$137 million) to support the Pan-Canadian Artificial Intelligence Strategy. While exact government funding amounts aren’t known, it’s clear that China is significantly upping its game in research activity, with very steep growth in publications on AI. It has a key focus on technologies such as unpiloted aerial vehicles and voice and image recognition. 12Ĭhina’s strategy, announced in 2017, aims to make China an AI leader by 2030. 11 In 2021, the National Artificial Intelligence Initiative Office was launched to play a coordinating role for all AI research and policymaking across academia, government and industry. The US Government’s investment in AI projects amounted to around US$5 billion in 2020. The strategy recognises the importance of international collaboration, while striving to put the US at the front of global AI research. 10 It drives the safe development, testing and deployment of AI technologies. The American National AI Initiative was unveiled in 2019. The biggest players in the AI game are the US and China. Other countries are investing, and investing big. 9 Those diverse fields highlight the potential breadth of AI applications in widely divergent aspects of our lives. 8 If we don’t, we’ll be left behind-and our children and grandchildren will miss out on vast opportunities.Īustralia’s Artificial Intelligence Roadmap cites three pivotal areas in which AI has the potential to shape our nation: natural resources and the environment health, ageing and disability and cities, towns and infrastructure. So why should Australia invest in AI R&D? If we want to secure the economic opportunities that will flow from AI, and shape those frontier technologies as they evolve, we must invest in a specialised, skilled workforce and advances in key technologies. Adaptive management has already seen the population in one wetland increase from 50 to 1,800 birds. Strong numbers of magpie geese indicate that the country is healthy. AI is used to scan hours of video footage to identify para grass-an introduced fodder crop that’s displacing the native grasses, which are a key habitat for magpie geese. 6 Under the direction of Indigenous rangers, drone footage collects data over areas of the national park that are difficult to access. Indigenous owners are working with researchers to support ecosystem resilience through a combination of Indigenous knowledge, technology and AI.
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5 However, these game-changing possibilities need more work and more investment to reach their full lifesaving potential.Ī uniquely Australian example can be found in Kakadu National Park. 4 Analysis of patient data has helped to predict and prevent falls among at-risk patients.
3 Many parts of health care stand to benefit from a data-driven approach, including image analysis to improve the detection and diagnosis of disease. In medicine and health care, the potential of AI is enormous, but yet to be truly realised.
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