In our weekly recap on Sunday, we, as editors, look back at the past seven days. We do this at the suggestion of our cartoonist Albert Jan Rasker. He chooses a subject, makes a drawing, and we take it from there. If you'd like to receive this weekly recap directly in your mailbox every Sunday morning, just subscribe here. Artificial Intelligence (AI) has come to control our lives step by step.

Definitions of the term'Artificial Intelligence' tend to fit one of the following categories: While all of these options are similar in that they deal with'intelligent behavior' in computers, they are also quite different. The first refers to a research discipline, while the second and third describe what that research discipline seeks to create. The ways in which the term'AI' can be used depend on which of these definitions you consider valid. For instance, news articles often have titles to the effect of "Google's new AI learned X" or "A new AI can do Y," such as: But, such usage ("An AI Developed", "AI can now", etc.) is only valid with that third'intelligent entity' definition. If the first'field of research' definition is chosen instead, these titles would have to be rewritten as "Google's new AI algorithm learned X" or "A new AI system can do Y."

This is an updated version. Turing Award Winner and Facebook Chief AI Scientist Yann LeCun has announced his exit from popular social networking platform Twitter after getting involved in a long and often acrimonious dispute regarding racial biases in AI. Unlike most other artificial intelligence researchers, LeCun has often aired his political views on social media platforms, and has previously engaged in public feuds with colleagues such as Gary Marcus. This time however LeCun's penchant for debate saw him run afoul of what he termed "the linguistic codes of modern social justice." It all started on June 20 with a tweet regarding the new Duke University PULSE AI photo recreation model that had depixelated a low-resolution input image of Barack Obama into a photo of a white male.

Machine learning is revolutionising healthcare provision and delivery, from mobilising previously inaccessible data sources to generating increasingly powerful algorithmic constructs for prognostic modelling. However, it is becoming increasingly obvious that if we do not learn from the mistakes of our past, that we are doomed to repeat them; if it isn't already too late… In this (irreverent and misleadingly titled) talk, Dr. Bilal Mateen will discuss the importance of definitions, revisit a series of hard truths, and share the story of the world's most complex and protracted game of 20 questions, all in an effort to highlight the importance of being able to tell the difference between good (data) science and a multi-million-dollar advertising campaign.

I mean it.Because a few days ago I saw a discussion on Twitter (*) that ran more or less like this: The "enormous moral issues" described in that Twitter thread are one instance of the "thought experiment in ethics" known as "Trolley Problem", also defined, by the source for the image above, "the Internet's Most Philosophical Meme": The problem is that, when speaking of driverless cars, the whole "trolley problem" approach consists, in a very non-negligible part, of barking up the wrong tree. The problem is not that the "moral issues that can never be understood by an AI" are not enormous. "how can we keep buying and using PRIVATE, or even shared, driverless cars in the SAME cities as today? The same cities that every serious forecast says will host a larger percentage of human population every year?" That is not a question, or a problem, worth of high priority.

I suppose I could sit here and fret over a day in the not-too-distant future when a robot powered by artificial intelligence(AI) will spit out newspaper columns like this one, rendering redundant columnists like me. After all, there have been reports that computers can already churn out news reports that read almost as well as those written by journalists, and in a fraction of the time taken. The thought of being replaced by software is depressing and, I might add, self-defeating. That is why I disagree with the way technological advances and the future of work are all too often framed in either-or terms: either robot or human worker, either AI or human brain. Here are a few recent examples of headlines in local media that fall into this category: "AI may replace a third of graduate jobs: Study", published on April 6; "Evidence that robots are winning the race for American jobs", published on March 30; and "Robots may take over 10 million jobs in Britain in 15 years", published on March 25. Such reports reflect how automation and AI are more often than not viewed - not just in Singapore but in other parts of the world too - as threats to jobs and human well-being.