About this Research Topic
A growing number of daily-life activities are surreptitiously outsourced to intelligent systems, powered by the latest advancements in the field of Artificial Intelligence (AI): from smart spam filters (e.g., Gmail) and online shopping recommendations (e.g., Amazon), to ride-sharing applications (e.g., Uber) and smart personal assistants (e.g., Alexa); a great deal of daily chores are streamlined by AI. In other words, we have already begun to trust AI in making decisions on our behalf about whose messages we receive, from whom we buy, with whom we share a ride, and even from where we inform ourselves. In fact, AI is set to automate increasingly fundamental daily-life facets, such as commuting (i.e., autonomous driving), and even law enforcement (e.g., “coplink”).
Consequently, the deeper AI weaves itself into the fabric of our societies, the greater the volume of training datasets that are required, and the more diverse and multidimensional they must be. However, certain training datasets are not immediately available; plus they have to be collected in an ecologically-valid fashion. For example, achieving fully autonomous driving (level 5), inevitably assumes the capacity of AI to perform ethical decision-making (i.e., The “Trolley Dilemma”). Data on ethical decision-making is scarce, and cannot simply be aggregated in an ecologically-valid manner by traditional means (e.g., surveys).
Virtual Reality (VR) emerges as a viable alternative for amassing diverse datasets for training future AI systems, offering a unique test-bed for simulating either common or extreme scenarios, such as an inescapable fatal collision. In fact, VR has the potential to provide the same cognitive modules as a real equivalent environmental experience, while it can host all the necessary means in terms of realism and control to experimentally study complex social interactions. Ultimately, the very nature of VR —realistically approximating almost any sort of settings and circumstances—may hold the key to achieving general-purpose AI.
We invite submissions that incorporate VR/AR/MxR for advancing human-AI interaction from a broad spectrum of applications.
Topics of interest include but are not limited to:
- VR and Ethics for training AI (e.g., autonomous cars, moral dilemmas, race/gender bias)
- VR and Robotics (e.g., humanoid robot training, human-robot interaction)
- VR and AI in Education (e.g. mutual learning, self-regulated learning)
- VR and AI in Entertainment (e.g. computer games, life-like autonomous agents)
- VR and AI in Health (e.g. rehabilitation training, virtual therapists, epidemics)
- User-studies & Ecologically-valid data collection (e.g., remote working during pandemics)
Keywords: Virtual Reality, Artificial Intelligence, Human-Computer Interaction, Human-Robot Interaction, Moral-Dilemmas, Ecologically-Valid Data
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
