Algorithms certainly will be developed for social prompting or coaching, but they will have to be capable of flexibly handling this rapidly shifting and complex social environment. There could be a collaborative interaction between AI and the user. Using software including facial recognition, a user could input other people's identity (name and relationship, via prompted questions) and through monitoring interactions over time between the user and others, the AI program or device could help clarify understanding of the relationships. Perhaps the AI could offer personalized prompts for responding to interactions. It might recognize that the person seeming irritating is a friend, and prompt a question and then a supportive response about the bad day.

For those of us who have Asperger's or who are just really bad at reading social cues and emotions, it can be challenging to engage with others and carry on an interesting conversation. And even if you are not, we have all had those moments when you cannot tell if someone is being sincere or not when he tells some outlandish story or statement. To fix this problem, Mashable reported earlier this year that a pair of MIT researchers have developed a wearable "that could someday act as a real-time virtual social coach." The wearable comes with artificial intelligence (AI), which can analyze a person's speech patterns and vitals to determine what others are feeling. The MIT researchers used a Samsung Simband, which can run custom algorithms.

Our research aims at developing interactive, social agents that can coach people to learn new tasks, skills, and habits. In this paper, we focus on coaching sedentary, overweight individuals to exercise regularly. We employ adaptive goal setting in which the coach generates, tracks, and revises personalized exercise goals for a trainee. The goals become incrementally more difficult as the trainee progresses through the training program. Our approach is model-based - the coach maintains a parameterized model of the trainee's aerobic capability that drives its expectation of the trainee's performance. The model is continually revised based on interactions with the trainee. The coach is embodied in a smartphone application which serves as a medium for coach-trainee interaction. We show that our approach can adapt the trainee program not only to several trainees with different capabilities but also to how a trainee's capability improves as they begin to exercise more. Experts rate the goals selected by the coach better than other plausible goals, demonstrating that our approach is effective.

It's not always easy to interpret what people are saying. If you're particularly bad with social cues, you might find the help you need in the future with a wearable. According to researchers from MIT's Computer Science and Artificial Intelligence Laboratory and Institute of Medical Engineering and Science, the wearable features an artificially intelligent system capable of predicting if a conversation is sad, happy, or neutral based on an individual's vitals and speech patterns. Tuka Alhanai and Mohammad Ghassemi detailed their research in a paper [PDF] they will be presenting at the Association for the Advancement of Artificial Intelligence's conference in San Francisco next week. According to Alhanai, it might not be long before people can have AI social coaches in their pocket, but they believe their wearable is the first experiment to collect both physical and speech data in a passive yet robust manner, even while subjects are engaged in natural interactions.

For people living with Asperger's syndrome, every social interaction can be a battle. While high-functioning in some aspects, those suffering from the form of autism often struggle to engage with other people and topics outside of their own spheres of interest. Keeping up with conversations can be especially challenging then, since difficulty interpreting the meaning of nonverbal communication (like gestures and facial expressions) and modulations in the speech patterns of others is one of the hallmarks of the condition. A pair of MIT researchers have set out to make these interactions less harrowing. Using wearable tech and AI deep-learning systems, they've developed a tool that could someday act as a real-time virtual social coach.