The IJCAI distinguished paper awards recognise some of the best papers presented at the conference each year. This year, three articles received the accolade of distinguished paper, with a further article receiving an honourable mention. Learning generalized unsolvability heuristics for classical planning Simon Ståhlberg, Guillem Francès, Jendrik Seipp Recent work in classical planning has introduced dedicated techniques for detecting unsolvable states, that is, states from which no goal state can be reached. The authors approach the problem from a generalized planning perspective and learn first order-like formulas that characterize unsolvability for entire planning domains. On the relation between approximation fixpoint theory and justification theory Simon Marynissen, Bart Bogaerts, Marc Denecker Approximation Fixpoint Theory (AFT) and Justification Theory (JT) are two frameworks to unify logical formalisms.

Scientists have long aimed to discover meaningful equations which accurately describe data. Machine learning algorithms automate construction of accurate data-driven models, but ensuring that these are consistent with existing knowledge is a challenge. We developed a methodology combining automated theorem proving with symbolic regression, enabling principled derivations of laws of nature. We demonstrate this for Kepler's third law, Einstein's relativistic time dilation, and Langmuir's theory of adsorption, in each case, automatically connecting experimental data with background theory. The combination of logical reasoning with machine learning provides generalizable insights into key aspects of the natural phenomena.

Artificial intelligence tools in hiring have so far remained unregulated by U.S. civil rights agencies, despite growing use and potential discrimination risks. One EEOC official wants that to change. "What is unfair is if there are enforcement actions or litigation, both from the government and from the private sector, against those who are using the technologies, and the federal agency responsible for administering the laws has said nothing," Keith Sonderling, a Republican commissioner on the U.S. Equal Employment Opportunity Commission, told Bloomberg Law in an exclusive interview. The use of artificial intelligence for recruitment, resume screening, automated video interviews, and other employment tasks has for years been on the radar of federal regulators and lawmakers, as workers began filing allegations of AI-related discrimination to the EEOC. Attorneys have warned that bias litigation could soon be on the horizon.

We have a lot to be grateful for. The average life expectancy in Liverpool during the industrial revolution was 28 years old. Nowadays, we have extraordinary advances in technology that have resulted in artificial hearts and mRNA Covid vaccines; the internet, self-driving cars, and personal computing. Within the next decade, the AI (artificial intelligence) revolution will propagate through everything, and it is predicted by some that it will be a more dramatic shift in technology than the use of the personal computer. However, AI has become an over-hyped buzzword across many industries, and the design world is no exception.

As part of our series showcasing the plenary and keynote talks from the IEEE/RSJ IROS2020 (International Conference on Intelligent Robots and Systems), this week we bring you Nikolaus Correll (Associate Professor at the University of Colorado at Boulder) and Cynthia Breazeal (Professor of Media Arts and Sciences at MIT). Nikolaus' talk is on the topic of robot manipulation, while Cynthia's talk is about the topic of social robots. Bio: Nikolaus Correll is an Associate Professor at the University of Colorado at Boulder. He obtained his MS in Electrical Engineering from ETH Zürich and his PhD in Computer Science from EPF Lausanne in 2007. From 2007-2009 he was a post-doc at MIT's Computer Science and Artificial Intelligence Lab (CSAIL).

Deciding which of Netflix's thousands of shows and movies to grant your all-important click can be a paralyzing task for many of us, so there was something brilliant, or cynical--or in all likelihood, both--about the streaming service coming out with a show called Clickbait. It's announcing itself as potentially dishonest and exploitative and daring you to click anyway, and the gambit clearly worked: As of Tuesday, the limited series, which premiered on the streaming service last week, was topping Netflix's most-watched list. Whether you don't want to give Clickbait the satisfaction of your click or you've already clicked many times over, let's talk about it--and there is a lot to talk about--spoilers and all. In the first episode of the eight-episode series, a video surfaces online of Nick Brewer (Adrian Grenier), an improbably perfect husband and father, being held hostage and holding a series of signs: One says he abuses women. Another says that if the video gets to 5 million views, he will die.

Welcome to our August 2021 monthly digest where you can catch up with any AIhub stories you may have missed, get the low-down on recent events, and much more. In this edition we cover IJCAI 2021, find out about new grants for climate research, hear about RoboCupJunior, and celebrate a significant birthday. The big event this month was the International Joint Conference on Artificial Intelligence (IJCAI-21), held virtually from 19-26 August. Gathertown played host to proceedings and participants were treated to eight invited talks, panel discussions, poster sessions, and more. We're covering the invited talks in a series of articles.

Most of us followed the exciting introduction of the new iPhone X, and there you also saw in the press conference, it's all about machine learning now for face recognition, applied also, machine learning in face recognition to unlock your phone. So, I think we all experience it already with our smartphones, and going forward, we'll see much more of it. Michael Chui: What we're starting to see is these AI technologies underpinning a lot of the things, all the online and mobile services that we're now increasingly taking advantage of. So, for instance, in e-commerce or media, when systems are providing you with suggestions for things you might be interested in, things you might be interested in reading or things you might be interested in buying--the next-product-to-buy use case, as we describe it--increasingly, those types of systems are powered not only by statistical methods, but by some of these AI technologies as well, hopefully bringing consumers closer to the things that they'd be most interested in. Simon London: I'm going to throw one more into the pot there. I'm lucky enough to live in the city of Mountain View in Silicon Valley. There are a surprising number of self-driving cars out on the road.

Unlike most other organizations participating at the Google summer of code, I feel that ML4SCI is unique in both its methods and objectives. While most organizations look for developers to build up their code repositories, resolve bugs and update new features, the primary objective of ML4SCI is to solve open-ended research questions in basic sciences by developing/using free and open source software by using Machine Learning. This year the kind of projects ranged from deep learning in gravitational physics, astronomy, quantum machine learning, machine learning to fluid turbulence, novel quantum materials etc. I have compiled my work into a single open-source repository. Titled, "Decoding Quantum States with NMR", we have a set of tutorials to read, preprocess and extract features from the NMR simulation data.

During the last decades robots are transforming from simple machines to cognitive collaborators. The distance that has been covered is long, but there are still challenges, as well as opportunities that lie ahead. That was also the main topic of discussion in the agROBOfood event'Visioning the future of agri-food robotics' by a panel of experts of the domain. The topic was introduced by two inspiring presentations. The first one was by Jérôme Bandry, who shared the vision of CEMA (European Agricultural Machinery).