In addition to the peer-reviewed program, the Technology, Mind, and Society conference featured four keynote presentations. Cynthia Breazeal (Massachusetts Institute of Technology) spoke on her extensive work in the creation of social robots that, through their verbal, nonverbal, and emotive expressions, meaningfully engage with people in support of their goals. Eric Horvitz (Microsoft Research) discussed his work modeling psychological processes like intention and cognition that inform the development of interactive systems that complement human intellect. Finally, Alex "Sandy" Pentland (Massachusetts The Technology, Mind, and Society conference Institute of Technology) discussed his work on provided an interdisciplinary venue for reporting social physics and the ways in which big data can be and assessing current efforts to understand and shape used to accurately predict and shape human behavior. Human-Centered Vehicle Automation: Lessons and The conference was organized around four Questions from the Real World, with panelists Chuck broad themes: basic research.

The second annual workshop on Naval Applications of Machine Learning (NAML) was held February 13-15, 2018, at the Space and Naval Warfare (SPAWAR) Systems Center Pacific (SSC Pacific), a U.S. Navy research laboratory in San Diego, California, USA. The workshop events included invited speakers, demonstrations, discussion sessions, and oral and poster presentations. The workshop cochairs were Josh Harguess and Katie Rainey, both from SSC Pacific. The poster presentations were coordinated by Chris Ward also from SSC Pacific. This article discusses the motivation, goals, and impact of the workshop and highlights some of the topics covered.

This year's conference broke a number of traditions set in America, HCOMP 2018 returned to Europe, where the very first HCOMP workshop had taken place in 2009. Besmira Nushi, Ece Kamar, and Eric interdisciplinary communities, we fostered new connections Horvitz were also singled out with an honorable among collective intelligence, crowdsourcing, mention for their paper "Towards Accountable AI: and human computation scholars and practitioners, Hybrid Human-Machine Analyses for Characterizing across diverse fields including humancomputer System Failure." Finally, Vikram Mohanty, David interaction (HCI), artificial intelligence, Thames, and Kurt Luther's presentation, "Are 1,000 economics, business, and design. Features Worth A Picture? Combining Crowdsourcing HCOMP was started by researchers from diverse and Face Recognition to Identify Civil War Soldiers," fields who wanted a high-quality scholarly venue for was given the Best Poster / Demo Presentation the review and presentation of the highest quality award. For this, we invited previous AAAI HCOMP conferences (and four submissions to a Works-in-Progress (WIP) and HCOMP workshops before that) to promote the most Demonstrations track, co-organized by Alessandro rigorous and exciting scholarship in this fast-emerging, Bozzon (Delft University of Technology) and Matteo multidisciplinary area.

ICWSM-18 and HCOMP-if any spots remain open.The organizers Munich, Germany. For information 18 were both successful, with increases of the AAAI/ACM SIGAI Job Fair are about paper submissions, as well as the in attendance. Smith noted that John Dickerson (University of Maryland, planned program, please refer to although we budgeted for a deficit of USA) and Chris Amato (Northeastern icwsm.org/2019.

One of NIST's research areas has been the quantification of Each team's system is faced with challenges such as The goal of ARIAC is to solidify the shown in figure 1. The organizers chose kitting field of robot agility, while also progressing the state because of its similarity to assembly. Teams were tasked with assembling a robotic system's (robot, controller, and sensors) ability kit both from bins of stationary parts and from a to respond to a dynamic environment. After the robotic system finished dynamic response includes handling errors like the kit, the kit was placed on an autonomous guided dropped parts or responding to changes in orders, all vehicle (AGV) and taken away. Teams were faced with such challenges as forced The competition addresses the aspect of robot dropped parts and in-process order changes.

The Thirty-First International Florida Artificial Intelligence Research Society Conference (FLAIRS-31) was held May 21-23, 2018, at the Crowne Plaza Oceanfront in Melbourne, Florida, USA. The conference events included invited speakers, special tracks, and presentations of papers, posters, and awards. The conference chair was Zdravko Markov from Central Connecticut State University. The program co-chairs were Vasile Rus from the University of Memphis and Keith Brawner from the Army Research Laboratory. The special tracks were coordinated by Roman Barták from Charles University in Prague.

Inertial confinement fusion (ICF) experiments are designed using computer simulations that are approximations of reality, and therefore must be calibrated to accurately predict experimental observations. In this work, we propose a novel nonlinear technique for calibrating from simulations to experiments, or from low fidelity simulations to high fidelity simulations, via "transfer learning". Transfer learning is a commonly used technique in the machine learning community, in which models trained on one task are partially retrained to solve a separate, but related task, for which there is a limited quantity of data. We introduce the idea of hierarchical transfer learning, in which neural networks trained on low fidelity models are calibrated to high fidelity models, then to experimental data. This technique essentially bootstraps the calibration process, enabling the creation of models which predict high fidelity simulations or experiments with minimal computational cost. We apply this technique to a database of ICF simulations and experiments carried out at the Omega laser facility. Transfer learning with deep neural networks enables the creation of models that are more predictive of Omega experiments than simulations alone. The calibrated models accurately predict future Omega experiments, and are used to search for new, optimal implosion designs.

Donald Trump's $1.5 trillion tax cut has increased incentives to replace workers with robots, contradicting his campaign promise to restore well-paying manufacturing jobs in the nation's heartland. The Trump tax bill permits "U.S. corporations to expense their capital investment, through 2022. So, if a U.S. corporation buys a robot for $100 thousand, it can deduct the $100 thousand immediately to calculate its U.S. taxable income, rather than recover the $100 thousand over the life of the robot, as under prior law," Steven M. Rosenthal, a senior fellow at the Urban Institute and a specialist in tax policy, wrote me by email. I have addressed the impact of robotics on Trump voters in previous columns, but today I want to explore these developments in greater detail as tools to gather and analyze information have improved. One of the most striking developments in recent decades is the ongoing decline in work force participation among men, from 88.7 percent in July, 1947 to 68.7 percent in September, 2010, according to the Federal Reserve. This drop in participation has been sharpest for men without college degrees.

Google CEO Sundar Pichai, head of one of the world's leading artificial intelligence companies, said in an interview this week that concerns about harmful applications of the technology are "very legitimate" - but the tech industry should be trusted to responsibly regulate its use. Speaking with The Washington Post on Tuesday afternoon, Pichai said that new AI tools - the backbone of innovations such as driverless cars and disease-detecting algorithms - require companies to set ethical guardrails and think through how the technology can be abused. "I think tech has to realise it just can't build it, and then fix it," Pichai said. "I think that doesn't work." Tech giants have to ensure that artificial intelligence with "agency of its own" doesn't harm humankind, Pichai said.

This technology is anything but new, but it's never gotten as much attention as it does today. In recent years, AI has not only shown real technological progress but also shows how it can be used for political purposes. While the current AI race cannot really be compared to the nuclear race of yesteryear, we can nevertheless see that the major powers are seeking to control it in order to have an economic, social and military advantage over other countries. The USA and China are at the forefront of this race, of course, and the EU is well aware of this. It has therefore decided to react to better equip itself.