We need to do more than teach machines to learn. We need to overcome the barriers that separate machines from us – and us from them.
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Articles on Machine learning
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Business Briefing: why the future is workless
The Conversation18.1 MB (download)
We need to embrace a future where machines do our jobs for us and the government gives us a basic income as a safety net, author Tim Dunlop says.
New HBO series reimagines a group of life-like robots programmed with hope but marred in violence. They might be more human than we think.
Auto-translation software has been pretty frustrating to use. But news of vast improvements to Google’s translation software raises the prospect that websites will soon be browsable in any language.
Algorithms that learn from large data sets can pick up inherent social biases. That could perpetuate the biases, or even worsen them.
Computer-aided decision-making has been shown to help in clinical contexts. But winning over doctors and patients is a different matter.
The Australian census is just one way to gather data on people. We also freely give out information in other ways that can be used to study many things, and maybe even predict an election result.
Artificial intelligence gives technology the ability to learn and adapt. But they can learn a lot more if they can share their learning with other smart devices.
Machine learning is being used to see if it’s possible to predict whether someone will commit a crime some time in the future. But does this risk condemning people for a crime they haven’t committed?
The technological goals are lofty. But fitting the new tech into the social and political landscape might pose the bigger challenge.
The rise of online ‘chatbots’ shows how artificial intelligence is becoming a part of daily life. But how do you stop them talking like a really bad PA?
Computers must master football if they are to demonstrate that they can be our equal.
We’re just at the beginning of working out the tasks machines will make us better at.
Pairing more powerful computers with increasingly sensitive scanners can yield many benefits in medicine and other fields.
Big data is all well and good, but if we want medical breakthroughs, we’ll need big theory too.
If a machine can write a speech for a politician, why not go the next step and replace the elected human with a programmed robot?
Google’s artificial intelligence made a surprise move in the recent Go challenge that has some people worried about what happens when AI makes a non-human decision that we could not anticipate.
Computers are getting better and better at the jobs that previously made sense for researchers to outsource to citizen scientists. But don’t worry: there’s still a role for people in these projects.
What happens if we let growing artificial intelligence make all of our decisions for us?
Our data-driven model was able to create a reasonably accurate assessment of justices’ views on issues, predict their alignments on cases and identify who might be a swing vote.
Top contributors
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Research Fellow in AI Accountability, Queensland University of Technology
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Professor of Information Systems, Michigan State University
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Associate Professor in Behavioral Data Science, University of Technology Sydney
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Professor in Robotics, Queensland University of Technology
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Research Assistant Professor of Industrial & Systems Engineering, University of Southern California
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Head of the Marketing Innovation and Distribution Program at EMLV, Pôle Léonard de Vinci
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Associate research scientist Cambridge Judge Business School and lecturer GEM, Grenoble École de Management (GEM)
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Assistant Professor of Integrative Biology & Computer Science and Engineering, Michigan State University
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Professor of Machine Learning, University of Sheffield
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Professor of Marketing and Consumer Behaviour, Queensland University of Technology
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Professor of Computer Science and Director of the Art & AI Lab, Rutgers University
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Professor, ESCP Business School
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Associate Professor
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Professor of Neuroscience and Mathematics, The University of Queensland
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Professor of AI, Research Group Leader, UNSW Sydney
