I believe that 2018 is going to be a fundamental moment in the history of technology, where we are able to unleash the power of IT to increase productivity and mercifully release bottlenecks that liberate people to focus on what they do best. In Part 2 of my technology predictions for 2018 (read Part 1 here), I explore the opportunities that lie in Augmented Reality (AR) and how our reliance on machines will increase. "Emerging technologies over the next decade have the potential to solve some of the intractable problems that humanity has faced for so long." It won't be long until the lines between'real' reality and augmented reality blur entirely. In fact, we are already starting to witness disruptions in some industries; DAQRI's state-of-the-art devices can bring AR to medical training facilities by helping plan surgeries before they happen through detailed 3D visualizations, and they are also revolutionizing the manufacturing industry through their ability to display control room information in real-time and visualize thermal data to pinpoint congestion issues deep within a pipe.
Humans make decisions and act alongside other humans to pursue both short-term and long-term goals. As a result of ongoing progress in areas such as computing science and automation, humans now also interact with non-human agents of varying complexity as part of their day-to-day activities; substantial work is being done to integrate increasingly intelligent machine agents into human work and play. With increases in the cognitive, sensory, and motor capacity of these agents, intelligent machinery for human assistance can now reasonably be considered to engage in joint action with humans---i.e., two or more agents adapting their behaviour and their understanding of each other so as to progress in shared objectives or goals. The mechanisms, conditions, and opportunities for skillful joint action in human-machine partnerships is of great interest to multiple communities. Despite this, human-machine joint action is as yet under-explored, especially in cases where a human and an intelligent machine interact in a persistent way during the course of real-time, daily-life experience. In this work, we contribute a virtual reality environment wherein a human and an agent can adapt their predictions, their actions, and their communication so as to pursue a simple foraging task. In a case study with a single participant, we provide an example of human-agent coordination and decision-making involving prediction learning on the part of the human and the machine agent, and control learning on the part of the machine agent wherein audio communication signals are used to cue its human partner in service of acquiring shared reward. These comparisons suggest the utility of studying human-machine coordination in a virtual reality environment, and identify further research that will expand our understanding of persistent human-machine joint action.