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Technology Business Leaders Debate Future of Artificial Intelligence, Machine Learning

Technology Business Leaders Debate Future of Artificial Intelligence, Machine Learning

Ian Gardiner, Amazon Web Services’ Head of Startup Ecosystem Australia/New Zealand moderated panellists; Daniel Petre, investor, philanthropist and founder of AirTree Venture Capital; Arun Poojari, General Manager Asia-Pacific & Japan of SparkBeyond; Afiniti Managing Director Australia and former federal politician Wyatt Roy, and Dr. Catriona Wallace, founder and Chief Executive of ASX-listed fintech Flamingo Customer Experience. Watch a video of highlights from the discussion here.

SparkBeyond’s Arun Poojari outlined that the value of AI was its ability to deliver insights on business problems not possible by application of human intelligence alone. Humans are designed for creative uni-dimensional thinking, he said, while machines are designed for multi-dimensional thinking.

When asked what key tools an AI firm needs, Daniel Petre argued that algorithms are not the holy grail and are being democratised by the global technology giants. In his view, the key advantage comes rather from possession of exclusive datasets and effective use of these to solve problems. “Insights spiral away when you combine the best data with the best data scientist,” he said. Catriona Wallace agreed about the importance of unique datasets, noting that solutions like hers illustrated that they didn’t have to be ‘big’.

On the thorny topic of venture capital (VC) financing for AI firms, Arun Poojari said that “if we had taken VC money, the problems close to our heart may not have been solved”, and commented wryly that “at the end of the money is the big stick”. Catriona Wallace pointed out that she had been turned down, and that 95 percent of global VC funding went to male-led businesses. (Daniel Petre’s rejoinder was that 50 percent of his investments were in women-led companies.) For Wallace, capital markets had been a better road to funding for her business, and the fact that she had been able to raise $16 million over the past three years was a positive signal that Australian investors were now starting to meaningfully support AI.

The panel also canvassed the widely-discussed topic of how AI and machine learning are going to affect employment. Wyatt Roy pointed out that changes of the kind already taking place were not new; rather, the speed of change is now happening at a much greater pace than in previous periods. In his view, policymakers need to lead the conversation to build confidence in the community and remove the fear from the conversation.

“There’s no question there will be a time when software will do what a human can do” was Daniel Petre’s view – the key question was when. Acceleration in the speed of technological change would lead to a significantly greater bifurcation in the labour market, he said. A lot of middle-tier white-collar jobs were going to disappear, and society would be left with “a lot of good people who are unemployable”. He was concerned that unlike the United States, Australia was not creating global technology firms, and that politicians were “running away from the issue”.

He also highlighted the lack of research and development by Australian businesses and that there were not enough talented scientists and engineers. Wyatt Roy agreed that Australia should be aggressively trying to attract the best and brightest, and that business leaders needed to make the case for this, but noted how controversial this is with sections of the community. Arun Poojari pointed to the need to create a culture where it’s acceptable to challenge accepted norms and to fail.

“The exciting thing is we don’t know where we’re all going to go,” Catriona Wallace stated, summing up her view of the future of AI and its impact on Australia. “But we have the ability to create an agenda and a path for ourselves.”







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