Scientists are arguing over how YouTube might help turn people into extremists.
Quantum computing would signify an immense shift in processing power, but how close are we to achieving it?
A paper published by researchers at Google claimed that they had achieved computing quantum supremacy, but leaks and counter-claims have created a stir.
Emotion recognition technology, an outgrowth of facial recognition technology, continues to advance quickly.
A report calls for banning the use of emotion recognition technology. An AI and computer vision researcher explains the potential and why there’s growing concern.
When algorithms make decisions with real-world consequences, they need to be fair.
A machine learning expert predicts a new balance between human and machine intelligence is on the horizon. For that to be good news, researchers need to figure out how to design algorithms that are fair.
Alongside doctors, AI could be a useful tool for providing better diagnosis.
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An AI trained to look at heart scans was able to successfully predict risk of death. But one expert cautions we still need to be careful about designing – and using – AI for medical diagnosis.
Manipulating our own personal data can allow us to manipulate capitalism.
Personal data is valued primarily because data can be turned into a private asset. That has significant implications for political and societal choices.
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Some initiatives aim to develop more ethical and equitable models.
YouTube uses a wide range of tools to keep viewers watching.
Algorithms can amplify toxic content, but the problems start in human communities.
Researchers used a statistical algorithm to analyse written texts between 1820-2009 in four Western countries.
Of the countries we looked at, all have seen an increase in subjective happiness since the 1970s.
Algorithms can reinforce existing biases in society.
The fundamental problem with AI is it is often riddled with society’s existing biases and prejudices.
It can be tricky to make it look like people are doing things they never did.
A key element of the battle between truth and propaganda has nothing to do with technology. It has to do with how people are much more likely to accept something if it confirms their beliefs.
Scientists are working with artificial intelligence in hopes of being able to better detect cancer.
Artificial intelligence holds great promise for medicine, but safeguards are needed to ensure it does not harm patients.
Bias in, bias out: many algorithms have inherent design problems.
Mathematician Hannah Fry has called for tech and data scientists to make an ethical pledge, as medical doctors do. But the same result might be delivered by simply asking people to mind their bias.
A new test which capitalises on existing knowledge and technology will increase diagnoses, speed up the process and save the NHS millions of pounds.
In an attempt to address the growing problem of fake news online, an algorithm that identifies patterns in language may help distinguish between factual and inaccurate news articles.
Using machine learning and natural language processing, researchers are developing an algorithm that can distinguish between real and fake news articles.
An algorithm is just following rules designed either directly or indirectly by a human.
Algorithms are only human (well, designed by humans) but we need to trust they’ll do what they’re supposed to do. And that means we need a better way to test them.
Machines see better than you think.
The Creative Exchange/Unsplash.
Instead of trying to explain the mystifying mathematics behind how algorithms work, this researcher started looking at how they actually ‘see’ the world we live in.
One former member of Australia’s government review tribunal has described robo-debt as a form of ‘extortion’.
A new legal framework for automated decision making is critical to protect citizens in the digital age.
Online gambling algorithims and blurred lines on what constitutes an advert on social media mean advertising principles are being flouted.
I’m safe, but you should be more careful online.
People know about Facebook’s problems, but assume they are largely immune – even while they imagine that everyone else is very susceptible to influence.