The shortcuts made when AI was being developed can guide society’s responses to the technology.
Articles on Machine learning
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Artificial intelligence tools are making waves in almost every aspect of life, and astronomy is no different. An astronomer explains the history and future of AI in understanding the universe.
if a machine can ascribe intent to the events and experiences befalling it, this raises the question of identity and what it means to be aware of oneself and others
Machine learning is becoming an indispensable tool in astronomy by sorting through enormous datasets from telescopes.
Pausing AI development will give our governments and culture time to catch up with and steer the rush of new technology.
Machine learning may not seem to have much connection with wildlife, but it’s starting to play a central role in bird conservation.
Our tendency to view machines as people and become attached to them points to real risks of psychological entanglement with AI technology.
An automatic system to determine political ideology from online posts could be a powerful tool against online radicalisation.
The technology exists to build autonomous weapons. How well they would work and whether they could be adequately controlled are unknown. The Ukraine war has only turned up the pressure.
There won’t be an easy tech fix for the questions about authorship raised by ChatGPT and other text generators.
Can artificial intelligence transform the search for alien intelligence?
AI’s ability to identify ‘technosignatures’ missed by classical algorithms is an exciting step forward for radio astronomers.
AI models are increasingly being used to make important decision about people’s lives – just take Robodebt. Yet the complexity of these systems means we hardly understand them.
People often struggle to distinguish between real faces and artificial ones made by a computer.
The majority of flood-related deaths involve vehicles in water. What if flood models could warn of the risks street by street using real-time storm forecasts? Machine learning can make it possible.
To understand the potential for machine learning to transform medicine, we must go back to the controversial origins of data use in healthcare
Now that AI systems can generate realistic images and convincing prose, are creative and knowledge workers endangered or poised for productivity gains? A panel of experts says it’s not so clear-cut.
From ChatGPT to Lensa, it feels like AI is here to take over. But despite some impressive results, such systems still have plenty of limitations.
After Brazil’s exit, who might be on course to win in 2022? Experts crunch 150 years of big data to predict the winner.
The newest OpenAI text-generator is a marked improvement over its predecessor – but it still has its pitfalls.
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, 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