Artificial Intelligence has impacted almost every aspect of human life, leaving large amounts of manual jobs to computers, and allowing humans to pursue intelligent jobs. However, in the future, there may be a time when intelligent jobs are also done artificially. Even more unsettling is the possibility that machines will become more intelligent than humans. Although there is little consensus on this topic, such an event is almost certain to happen. We can only hope that we have found a way to make AI "friendly", or share humans interests beforehand.

Intelligent algorithms are used to create paintings, write poems, and compose music. According to a study by an international team of researchers from the Massachusetts Institute of Technology (MIT), and the Center of Humans and Machines at the Max Planck Institute for Human Development, whether people perceive artificial intelligence (AI) as the ingenious creator of art or simply another tool used by artists depends on how information about AI art is presented. The results were published in the journal iScience. In October 2018, a work of art by Edmond de Belamie, which was created with the help of an intelligent algorithm, was auctioned for 432,500 USD at Christie's Auction House. According to Christie's auction advertisement, the portrait was created by artificial intelligence (AI).

Recent progress in artificial intelligence provides the opportunity to ask the question of what is unique about human intelligence, but with a new comparison class. I argue that we can understand human intelligence, and the ways in which it may di er from artificial intelligence, by considering the characteristics of the kind of computational problems that human minds have to solve. I claim that these problems acquire their structure from three fundamental limitations that apply to human beings: limited time, limited computation, and limited communication. From these limitations we can derive many of the properties we associate with human intelligence, such as rapid learning, the ability to break down problems into parts, and the capacity for cumulative cultural evolution. Understanding Human Intelligence through Human Limitations Di erent Computational Problems, Di erent Kinds of Intelligence As machines begin to outperform humans on an increasing number of tasks, it is natural to ask what is unique about human intelligence. Historically, this has been a question that is asked when comparing humans to other animals. The classical answer (from Aristotle, via the Scholastics) is to view humans as "rational animals" - animals that think [18]. More modern analyses of human uniqueness emphasize the "cognitive niche" that humans fill, able to use their minds to outsmart the biological defenses of their competitors [43], or contrast this with the "cultural niche" of being able to accumulate knowledge across individuals and generations in a way that makes it possible to live in an unusually diverse range of environments [10, 25, 26]. Asking the same question of what makes humans unique, but changing the contrast class to include intelligent machines, yields a very di erent kind of answer. In this article I argue that even as we develop potentially superhuman machines, there is going to be a flavor of intelligence that remains uniquely human.

Benchmarks can be very misleading, says Douwe Kiela at Facebook AI Research, who led the team behind the tool. Focusing too much on benchmarks can mean losing sight of wider goals. The test can become the task. "You end up with a system that is better at the test than humans are but not better at the overall task," he says. "It's very deceiving, because it makes it look like we're much further than we actually are."

By Ratna Mehta Technological advancement is a double-edged sword; while it oils the wheels of advancement and innovation leading to breakthroughs that improve efficiency, rationalise cost and improve the quality of life, it has its fallouts, i.e. job losses, health issues and environmental pollution. Man vs Machine With the rise of AI, there is increasing anxiety around massive job displacement. This is substantiated by widespread research: - Accountants have a 95% chance of losing jobs - 29% of legal sector jobs could be automated in 10 years - Intelligent agents and robots could replace 30% of the world's current human labour Being a trader was an esteemed profession, but with AI systems that can analyse information from markets, social media, corporate filings and economic conditions to quickly decipher trades, these systems can trade better than any human. As per analysis firm Oxford Economics, up to 20 million manufacturing jobs around the world could be replaced with robots by 2030. Man and Machine Joining Forces How we use technology depends on our perspective; we can use it to'replace' humans or we can leverage it to'augment' humans.

Christie's made the headlines in 2018 when it became the first auction house to sell a painting created by AI. The painting, named Portrait of Edmond de Belamy, ended up selling for a cool $432,500, but more importantly, it demonstrated how intelligent machines are now perfectly capable of creating artwork. It was only a matter of time, I suppose. Thanks to AI, machines have been able to learn more and more human functions, including the ability to "see" (think facial recognition technology), speak and write (chatbots being a prime example). Learning to create is a logical step on from mastering the basic human abilities.

Perhaps many people are like me in that hearing the word "machine learning" for the first time brings forth images of Skynet from The Terminator movies or Haley Joel Osment's character from the Steven Spielberg's film A.I. Artificial Intelligence. However, machine learning has now become a regular part of our vernacular when it comes to predictive modeling in many conditions. Ramgopal et al use machine learning methods to derive and validate a new prediction model for risk stratification of febrile infants 60 days of age. Using various machine learning approaches, the authors developed a prediction model with high sensitivity and specificity compared with recent prediction models for febrile infants. So, are machine learning models the new paradigm for risk stratification of febrile infants? The results are intriguing, particularly the high specificity of the model, but further work must be done, as explained nicely by Chamberlain et al in an accompanying commentary (10.1542/peds.2020-012203).

Despite only announcing the promotion on Wednesday morning, Chipotle Mexican Grill has already awarded all of the allotted prizes to the first 250,000 winning participants of an online "Chipotle IQ" quiz. THIS IS EACH STATE'S FAVORITE FAST-FOOD FRENCH FRY, STUDY CLAIMS The quiz, which promised digital buy-one-get-one coupons for winners, tasked participants with successfully answering 10 trivia questions about the chain's "sourcing, ingredients, recipes, and sustainability efforts." Some of the questions, such as, "What percentage of Chipotle bowls are made of compostable fiber?", seem quite obviously designed to tout the brand's sustainability measures (spoiler alert: it's 100%), while others, like "When is Chipotle's birthday," are a little more obscure. "There were 250K Chipotle brainiacs who came before you, so unfortunately we're fresh out of BOGO prizes," reads a message greeting visitors to the Chipotle IQ test. "Chipotle IQ allows our customers to discover Chipotle in a whole new way and rewards our most devoted brand experts," said Chris Brandt, Chipotle's chief marketing officer, in a press release. "We're introducing a test our fans will actually be excited to take."

Unless you're a machine and you're reading this, you are in fact a human being. You perceive, make sense of, adapt, and respond to what life presents you. In doing so, you come up with creative acts and solutions, thriving for stability or exciting new outcomes as you go. You do so even if you don't feel yourself to be all that creative. As humans, we make sense of, adapt, and respond to what life presents to us.

This week, host Isaac Butler traces the creative origins of Michael R. Jackson's Pulitzer-winning musical A Strange Loop. After the interview, Isaac and co-host June Thomas discuss Michael's distinction between an autobiographical work and a self-referential work. In Slate Plus, Michael talks about two celebrity encounters, one with Liz Phair, whose music inspired a lot of his work, and one with Tyler Perry, whose work was satirized ruthlessly in A Strange Loop. Send your questions about creativity and any other feedback to working@slate.com