Expecting algorithms to perform perfectly might be asking too much of ourselves.
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A legal loophole could grant computer systems many legal rights people have – threatening human rights and dignity and setting up some real legal and moral problems.
As Google turns 20, a look at how the company has grown – and what the next two decades might bring for the company.
It could seem attractive to try to teach computers to detect harassment, threats and abusive language. But it's much more difficult than it might appear.
New research has uncovered a previously unknown weakness in smart city systems: devices that trust each other. That could lead to some pretty terrible traffic, among other problems.
A branch of AI research promises to deliver computers that evolve their own software but the tech industry has yet to catch on.
We have far more to worry about from outdated science that embodies dubious prejudices than we do from deep learning networks.
We prefer to go with our guts.
Computers today are fast and powerful but they still can't think like a human when it comes to some tasks we find easy. That's why tech companies are turning to neuroscience for help.
A European Union law will require human-understandable explanations for algorithms' decisions. A team of researchers has found a way to provide that, even for complex calculations.
Despite its promises, people analytics has serious ethical implications and can adversely affect organisations and how people are treated at work.
Unrestricted access to information is vital to a vibrant democracy.But if this information is inaccurate, biased or falsified, the fundamental freedom of informed choice is denied.
Changes in news media distribution and the impartiality of news sources provide good reason to be concerned. However, digital inequality is not the way to understand or measure it.
Algorithms can discriminate, even when their designers don't intend that to happen. But they also can make detecting bias easier.
Math isn’t prejudiced, goes the argument. But these arithmetic programs can learn bias from the data fed into them by human beings, leading to unfair treatment and discrimination.
If we want students to be well prepared for the 21st century, then we should be teaching coding in school.
If machines run by artificial intelligence take over the world it's only because we programmed them to do so. So how can fuzzy logic help us prevent that?
When the English football fixtures were announced in June, many fans would have studied them from their own perspective. Are the fixtures fair to their team? Why do they have to travel the full length…
Top contributors
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Professor of Computer Science and Provost/CEO/PVC, University of Nottingham
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Professor Emeritus, Swinburne University of Technology
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Associate Professor of Computer Engineering and Computer Science, University of Louisville
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Principal Research Fellow, RMIT University
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Lecturer in Mathematics, Deakin University
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Bernard A. Galler Collegiate Professor of Electrical Engineering and Computer Science, University of Michigan
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Professor of Neuroscience and Mathematics, The University of Queensland
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PhD Student in Mathematics, University of Illinois at Chicago
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Professor and Head of Department of Political and Conflict Studies, Nelson Mandela University
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Associate Professor of Philosophy, Australian National University
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Associate Professor in Business Information Systems, University of Sydney
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Associate Professor of Computer Science and Electrical and Computer Engineering, Carnegie Mellon University
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Emeritus Professor of Management Science, University of Bath
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Research Associate, IMD Business School
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Associate Professor of Computer and Information Science, University of Oregon
