Spoken dialog researchers have recently demonstrated highly-interactive systems in several domains. This paper considers how to build on these advances to make systems more robust, easier to develop, and more scientifically significant. We identify key challenges whose solution would lead to improvements in dialog systems and beyond.

One particular challenge is to ground human language to robot internal representation of the physical world. Although copresent in a shared environment, humans and robots have mismatched capabilities in reasoning, perception, and action. A robot not only needs to incorporate collaborative effort from human partners to better connect human language to its own representation, but also needs to make extra collaborative effort to communicate its representation in language that humans can understand. This article gives a brief introduction to this research effort and discusses several collaborative approaches to grounding language to perception and action.

The Association for the Advancement of Artificial Intelligence, in cooperation with Stanford University's Department of Computer Science, presented the 2016 Spring Symposium Series on Monday through Wednesday, March 21-23, 2016 at Stanford University. The titles of the seven symposia were (1) AI and the Mitigation of Human Error: Anomalies, Team Metrics and Thermodynamics; (2) Challenges and Opportunities in Multiagent Learning for the Real World (3) Enabling Computing Research in Socially Intelligent Human-Robot Interaction: A Community-Driven Modular Research Platform; (4) Ethical and Moral Considerations in Non-Human Agents; (5) Intelligent Systems for Supporting Distributed Human Teamwork; (6) Observational Studies through Social Media and Other Human-Generated Content, and (7) Well-Being Computing: AI Meets Health and Happiness Science.

The 29th International Florida Artificial Intelligence Research Society Conference (FLAIRS-29) was held May 16-18, 2016, at the Hilton Key Largo Resort in Key Largo, Florida, USA. The conference events included invited speakers, special tracks, and presentations of papers, posters, and awards. The conference chair was Bill Eberle from Tennessee Technological University. The special track were coordinated by Vasile Rus from University of Memphis.

This issue of AI Magazine brings together a collection of articles on challenges, mechanisms, and research progress in turn-taking and coordination between humans and machines.

The rules of the game called psychological science.

Machine Learning is not new, but its application across memory-optimized distributed systems has led to an explosion in both the number and capability of its uses. Pandora develops personalized content recommendations with machine learning algorithms, Tesla has produced the first widely distributed autonomous vehicle, and Amazon uses autonomous robots to move packages within its warehouses and even deliver packages. When coupled with real-time data, advanced analytics approaches like machine learning and deep learning create immediate business opportunities. Machine learning has never been more accessible--if your data pipelines support real-time analysis. Attendees will learn tools and techniques for integrating machine learning models across industries and organizations.

Artificial Intelligence (AI) is used everywhere today, from self-driving cars, space travel to financial investments. So, when we think about the most exciting application for AI, we can't help but think of using AI to tell us how to make money in the currency markets (which has a $5 trillion a day turnover). More than 80% of trades in the currency markets are made by computers using AI. Big investment banks/trading firms use AI extensively. However, to build an AI system, a very strong background in Computer Science and Advanced Mathematics is essential.

LinkedIn cofounder Reid Hoffman, Omidyar Network, and John S. and the James L. Knight Foundation have today joined forces to create the Ethics and Governance of Artificial Intelligence Fund. The research fund will focus on AI for the public good and will bring a more diverse range of voices, like faith leaders and policymakers, to AI research and development. Issues the fund may address include ethical design, potential harmful and beneficial impacts of AI, and AI that works in the public interest. "Artificial intelligence and complex algorithms, fueled by big data and deep-learning systems, are quickly changing how we live and work -- from the news stories we see, to the loans for which we qualify, to the jobs we perform," the group said in a statement provided to VentureBeat. "Because of this pervasive but often concealed impact, it is imperative that AI research and development be shaped by a broad range of voices -- not only by engineers and corporations, but also by social scientists, ethicists, philosophers, faith leaders, economists, lawyers and policymakers."

It's been more than a decade since an international team of scientists sequenced the human genome. But the genomics revolution is only just beginning, Color Genomics CEO Othman Laraki says. "Each one of us, we have a torrent of data in our bodies," Laraki said on the latest episode of Recode Decode, hosted by Kara Swisher. "We're generating a tremendous amount of data, and today, we make use of almost none of that." He said most health data used to be recorded by hand and stored at the hospital.