"Wait a minute, wait a minute. You ain't heard nothing yet." So went the first line of audible dialogue in a feature film, 1927's The Jazz Singer. It was one of the first times that mass media had conveyed the sight and sound of a scene together, and the audience was enthralled. There have been improvements since: black and white has become colour, frame rates and resolutions have increased and sound quality has improved, but the media we consume still caters overwhelmingly, if not exclusively, to our eyes and ears.

A multiagent system can be viewed as a society of autonomous agents, whose interactions can be effectively regulated via social norms. In general, the norms of a society are not hardcoded but emerge from the agents' interactions. Specifically, how the agents in a society react to each other's behavior and respond to the reactions of others determines which norms emerge in the society. We think of these reactions by an agent to the satisfactory or unsatisfactory behaviors of another agent as communications from the first agent to the second agent. Understanding these communications is a kind of social intelligence: these communications provide natural drivers for norm emergence by pushing agents toward certain behaviors, which can become established as norms. Whereas it is well-known that sanctioning can lead to the emergence of norms, we posit that a broader kind of social intelligence can prove more effective in promoting cooperation in a multiagent system. Accordingly, we develop Nest, a framework that models social intelligence in the form of a wider variety of communications and understanding of them than in previous work. To evaluate Nest, we develop a simulated pandemic environment and conduct simulation experiments to compare Nest with baselines considering a combination of three kinds of social communication: sanction, tell, and hint. We find that societies formed of Nest agents achieve norms faster; moreover, Nest agents effectively avoid undesirable consequences, which are negative sanctions and deviation from goals, and yield higher satisfaction for themselves than baseline agents despite requiring only an equivalent amount of information.

Most robots are designed to do work. As such, not a lot of time, effort, or money is spent on making them able to communicate with humans, because they're usually just doing their own thing. This is starting to change a bit, though, as robots become versatile enough that it's reasonable to have humans working with them more directly, and it's becoming more important that those humans have some idea what the robot is up to. Some robots manage this with sounds, or lights, or screens with faces on them, but there are many systems for which hardware modifications like that aren't a good option. In one of best papers from all of HRI 2018 (seriously, they won a best paper award), roboticists from the University of Colorado Boulder explore how using augmented reality to help robots communicate with humans can make the bots feel safer, more efficient, and more part of a collaborative team.

It is believed that nonverbal visual information including facial expressions, facial micro-actions and head movements plays a significant role in fundamental social communication. Unfortunately it is regretful that the blind can not achieve such necessary information. Therefore, we propose a social assistant system, Lookine, to help them to go beyond this limitation. For Lookine, we apply the novel techniques including facial expression recognition, facial action recognition and head pose estimation, and obey barrier-free principles in our design. In experiments, the algorithm evaluation and user study prove that our system has promising accuracy, good real-time performance, and great user experience.

In a world-first, scientists have genetically engineered ants to lack their sense of smell, affecting the animals' ability to communicate. Scientists used the controversial CRISPR technology to disrupt the ants' ability to communicate, forage or compete to be a queen, as their antennae and brain circuits failed to fully develop. While the system has not yet been tested in humans, the researchers believe that it could one day be used to treat conditions that affect social communication, including schizophrenia and depression. In a world-first, scientists have genetically engineered ants to lack their sense of smell, affecting the animals' ability to communicate Crispr technology precisely changes small parts of genetic code. Unlike other gene-silencing tools, the Crispr system targets the genome's source material and permanently turns off genes at the DNA level.

This paper describes the Intelligent Engine (IE) of ECHOES, a serious game built for helping young children with Autism Spectrum Conditions acquire social communication skills. ECHOES IE's main component is an autonomous virtual agent that acts as a credible social partner for children with autism by engaging them in interactive learning activities. The other IE components are a user model, a drama manager and a social communication engine. We discuss how AI technology allows us to satisfy the requirements for the design of the agent and the learning activities that we identified through consultations with children and carers and a review of best practices for autism intervention. We present experimental results pertaining to the agent's effectiveness, which show encouraging improvements for a number of children.