Late last year, a Google engineer named Blake Lemoine felt certain he'd found something special. For months, Lemoine, who worked with the company's ethical AI division, had been testing Google's Language Model for Dialogue Applications, or LaMDA, from the living room of his San Francisco home. LaMDA is a hugely sophisticated chatbot, trained on trillions of words hoovered up from Wikipedia entries and internet posts and libraries' worth of books, and Lemoine's job was to ensure that the exchanges it produced weren't discriminatory or hateful. He posed questions to LaMDA about religion, ethnicity, sexual orientation and gender. The machine had some bugs -- there were a few ugly, racist impressions -- which Lemoine dutifully reported.

You might not notice it, but you've likely adopted artificial intelligence into your daily life. It can be as simple as personalizing your news feeds, searching for products on shopping sites or voice-to-text conversion on smartphones. It can also be applied to more sophisticated tasks like predicting court outcomes in cases involving employment law or used for robotic welding applications. The transformative power of AI is also an economic growth driver, which is why the Canadian government has given the green light to advancing the country's AI strategy. According to a recent announcement from Minister of Innovation, Science and Industry François-Philippe Champagne, more than $443 million in Budget 2021 is designated for the second phase of the pan-Canadian Artificial Intelligence Strategy.

Three years ago, a Georgia Tech study uncovered a major flaw in self-driving vehicles: they find it much harder to see darker-skinned pedestrians. The researchers were testing how accurately the vehicles' artificial intelligence–based object detection models noticed pedestrians of different races. But no matter what variables they changed -- how big the person was in the image, whether they were partially blocked, what time of day it was -- the imbalance remained, raising fears that in real-life applications, racialized people could be at higher risk of being hit by a self-driving car. It's just one of far too many examples showing how AI can be biased and, as a result, harm already-marginalized groups. "Think of something like melanoma detection," says Shingai Manjengwa, director of technical education at the Vector Institute for Artificial Intelligence.

Researchers from the Netherlands have developed a new machine learning method that's capable of distinguishing sponsored or otherwise paid content within news platforms, to an accuracy of more than 90%, in response to growing interest from advertisers in'native' advertising formats that are difficult to distinguish from'real' journalistic output. The new paper, titled Distinguishing Commercial from Editorial Content in News, comes from researchers at Leiden University. The authors observe that though more serious publications, which can more easily dictate terms to advertisers, will make a reasonable effort to distinguish'partner content' from the general run of news and analysis, the standards are slowly but inexorably shifting to increased integration between editorial and commercial teams on an outlet, which they consider an alarming and negative trend. 'The ability to disguise content, willingly or unwillingly, and the probability that advertorials are not recognized as such even if properly labelled is significant. Marketers call it native [advertising] for a reason.'

Two things can be said about human beings: we like building machines, and we tend to freak out about the machines we build. The Luddites of 19th-century England, an oath-based secret society, looked to the industrial era and saw not liberation but destitution. The most radical among them formed paramilitary groups to raid textile factories and destroy knitting machines and mechanical looms -- devices that would replace workers. Their political descendants include the lamplighters of early-20th-century New York who went on strike to protest the advent of electric streetlights, and the switchboard operators of Bloomington-Normal, Illinois, who in the 1930s took action against the rotary dial system. Did predictions of automation and mass joblessness come true?

It's a myth that Artificial Intelligence is just for large corporations. Robotics and automation are transforming the workplace for smaller businesses as the technology becomes ever cheaper and more accessible. There are many reasons to be optimistic about AI. An Accenture report suggests that it could bring an additional £814 billion to the UK economy by 2035, whist research firm Gartner reports that in 2020, AI will create 2.3 million jobs. General AI-based productivity tools are becoming more readily available and increasingly affordable – sometimes even free.