To judge from the hype, artificial intelligence is inches away from ripping through the economy and destroying everyone's jobs--save for the AI scientists who build the technology and the baristas and yoga instructors who minister to them. But one critic of that view comes from within the tent of AI itself: Gary Marcus. From an academic background in psychology and neuroscience--rather than computer science--Mr Marcus has long been an AI gadfly. He relishes poking holes in the popular AI technique of deep-learning because of its inability to perform abstractions even as it does an impressive job at pattern-matching. Yet his unease with the state of the art didn't prevent him from advancing the art with his own AI startup, Geometric Intelligence, which he sold to Uber in 2016.

This is the third Synced year-end compilation of "Artificial Intelligence Failures." Despite AI's rapid growth and remarkable achievements, a review of AI failures remains necessary and meaningful. Our aim is not to downplay or mock research and development results, but rather to take a look at what went wrong with the hope we can do better next time. A leading facial-recognition system identified three-time Super Bowl champion Duron Harmon of the New England Patriots, Boston Bruins forward Brad Marchand, and 25 other New England professional athletes as criminals. Amazon's Rekognition software incorrectly matched the athletes to a database of mugshots in a test organized by the Massachusetts chapter of the American Civil Liberties Union (ACLU).

The year was 2008 and the Interop tech trade show in New York City was crammed full of booths. Sales reps offered trinkets as they hawked their next-gen software and hardware. I wondered through blinking displays and the noise of a thousand buzzwords. The brand name vendors – Microsoft, Intel, Oracle, IBM – had paid big bucks for booths the size of small houses. Staffers gave product lectures backed by full-size video screens. After touring these big outfits, I investigated the smaller booths hosted by mid-sized players. With minimal staff, they worked still harder to lure you to their pitch. In an era before "Booth Babes" were outlawed, some booths included twenty-something women in skimpy sequined outfits, handing out t-shirts or glow-in-the-dark key chains. Tiny booths staffed mostly by bare bones crews. There I saw a modest booth by an outfit called Amazon Web Services. A sole rep manned it, and he wasn't wearing a company shirt.

Is it possible that lakes and forests might have rights before robots? Voters in Toledo have granted "irrevocable rights for the Lake Erie Ecosystem to exist, flourish and naturally evolve" which, according to this story, would give it legal standing to file lawsuits to protect itself from polluters (through the mouthpiece of a human guardian). It's an amazingly bold statement that is rife with thorny questions. Humans have had say over nature ever since Adam and Eve, and most political and cultural uses or abuses have been based on the shifting perspectives of their progeny. Nature is something "out there" that only gains meaning or purpose when defined by us.

Year 2020 does have a sci-fi ring to it. Perhaps that's one reason AI has so many people nervous. From your smart phone to your Google search to your Netflix and Spotify recommendations, AI shapes modern US work and life in many ways. Despite its growing ubiquity, fear of AI remains. The 2019 Artificial Intelligence--American Attitudes and Trends report from the Future of Humanity Institute at the University of Oxford found that "more Americans think that high-level machine intelligence will be harmful to humanity" than those who think it will be beneficial.

Despite their names, artificial intelligence technologies and their component systems, such as artificial neural networks, don't have much to do with real brain science. I'm a professor of bioengineering and neurosciences interested in understanding how the brain works as a system – and how we can use that knowledge to design and engineer new machine learning models. In recent decades, brain researchers have learned a huge amount about the physical connections in the brain and about how the nervous system routes information and processes it. But there is still a vast amount yet to be discovered. At the same time, computer algorithms, software and hardware advances have brought machine learning to previously unimagined levels of achievement.

EU presidency extends access to free AI course across EU Jan Petter Myklebust 13 December 2019 European Union employment ministers have endorsed a proposal from Finland's Presidency of the Council of the EU to provide European citizens with free access to a successful online course on basic artificial intelligence (AI), developed and run by the University of Helsinki in partnership with private firm Reaktor. To achieve this, the course on "Elements of AI" will be made available in all official EU languages. The Finnish government will fund the project with €1.7 million (US$1.9 million) from Finland's Ministry of Economic Affairs and Employment as part of the EU Council presidency's effort to democratise awareness of AI and develop people's skills for jobs of the future. At the launch of the initiative in Brussels on 10 December, Finland's Minister of Employment Timo Harakka said: "Our investment has three goals: we want to equip EU citizens with digital skills for the future; we wish to increase practical understanding of what artificial intelligence is; and by doing so, we want to give a boost to the digital leadership of Europe." "As our presidency ends, we want to offer something concrete. It's about one of the most pressing challenges facing Europe and Finland today: how to develop our digital literacy," Harakka said.

The most exciting thing is that we are able to predict risk of new dementia diagnosis up to eight years in advance. BOSTON – A team of scientists from Massachusetts General Hospital (MGH) has developed a software-based method of scanning electronic health records (EHRs) to estimate the risk that a healthy person will receive a dementia diagnosis in the future. Their algorithm uses machine learning to first build a list of key clinical terms associated with cognitive symptoms identified by clinical experts. Next, they used national language processing (NLP) to comb through EHRs looking for those terms. Finally, they used those results to estimate patients' risk of developing dementia.

Computers have learned to see the world more clearly in recent years, thanks to some impressive leaps in artificial intelligence. But you might be surprised--and upset--to know what these AI algorithms really think of you. As a recent experiment demonstrated, the best AI vision system might see a picture of your face and spit out a racial slur, a gender stereotype, or a term that impugns your good character. Now the scientists who helped teach machines to see have removed some of the human prejudice lurking in the data they used during the lessons. The changes can help AI to see things more fairly, they say.

This rugged little robot takes a licking and keeps on ticking. When fretting about an imaginary robot apocalypse, it's customary to worry about large robots like Boston Dynamics' Atlas and Spot. But have you considered the potential peril of swarms of tiny, unsquishable robo-insects? The DEAnsect, a fly-swatter-defying soft robot, could inspire all sorts of sci-fi fun, but its creators foresee a helpful future where the tiny bots work together for inspections, repairs or as remote emissaries sent to study real insect colonies. A team at Ecole polytechnique fédérale de Lausanne (EPFL) in Switzerland developed the fast, agile robot. "DEAnsect is propelled by soft artificial muscles: It can be twisted, bent, squeezed, while retaining its functionality," EPFL said.