Technological professionals are the first, and last, lines of defense against the misuse of technology.
Articles on Machine learning
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Machine learning is changing the world in ways that we are just beginning to appreciate. But could it change the way we do science and the reasons why we do science?
Testing new industrial chemicals is essential for public health and the environment. But animal testing is costly, and too many chemicals are left untested. A new AI tool may solve the problem.
With artificial intelligence, machines can now examine thousands of medical images for signs of disease. Will this technology replace doctors – or work side by side with them?
Project Debater looks like machines are ready to understand humans, but the reality is we’re still in the earliest days of AI.
We have developed a system that combines human intuition with machine learning to provide support for people making complex decisions.
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.
Information extracted from copyrighted material should not be seen as an infringement. Such analytical use is good for society.
Amazon, Google and Apple’s attempts to understand the tone of human voices can reflect human biases.
Google’s latest AI promises to help arrange your life by making appointment for you over the phone, but it’s limited by its rote learning of the simple tasks of everyday life.
Using AI to search for ET might help us find things we couldn’t even imagine we should look for, but to succeed we also have think critically about how we create and use that technology.
By 2022, people in developed countries may see more fake news than accurate information. Artificial intelligence may be to blame – but could also help people sort out the truth from lies.
AI seems able to answer questions at the heart of humanitarianism – questions such as who we should save, and how to be effective at scale.
Europe loses as many trees to storms each year as Poland produces in timber. Until now, the models for predicting which trees are at risk have not been good enough.
The report of the mathematician and deputy of Essonne Cédric Villani renders his report on artificial intelligence today.
An email from Aleksandr Kogan sheds light on exactly how much your Facebook data reveals about you, and what data scientists can actually do with that information.
The chatbot industry sees more data as the answer to building a truly conversational system. But the industry may be teaching chatbots the wrong thing.
A branch of AI research promises to deliver computers that evolve their own software but the tech industry has yet to catch on.
Can a computer model correctly predict the results of the first round in this year’s tournament? These mathematicians think so.
Machine learning isn’t reliable enough yet – and it’s short-sighted to only train this detection tech on jihadi content.
Top contributors
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Senior Research Fellow in AI Accountability, Queensland University of Technology
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Professor of Statistics and Professor of EECS, University of Michigan
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Professor of Information Systems, Michigan State University
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Professor in Robotics, Queensland University of Technology
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Professor of Chemistry, Connecticut College
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Professor of Artificial Intelligence, University of Bath
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Research Assistant Professor of Industrial & Systems Engineering, University of Southern California
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Professor of AI and Behavioral Data Science, University of Technology Sydney
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Head of the Marketing Innovation and Distribution Program at EMLV, Pôle Léonard de Vinci
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Professor of Computer Science, Queen Mary University of London
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Professor of Marketing and Consumer Behaviour, Queensland University of Technology
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Assistant Professor of Integrative Biology & Computer Science and Engineering, Michigan State University
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Associate Professor of Law and Analytics, Georgia State University
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Adjunct Senior Lecturer, Applied Ethics and CyberSecurity, Griffith University
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Professor of AI, Research Group Leader, UNSW