Learnings from Human Perception
Scientists have long explored the different sensory inputs to better understand how humans perceive the world and control their bodies. Many of the great discoveries about the human perceptual system were first found through laboratory experiments that stimulated inbound sensory inputs as well outbound sensory predictions. These aspects of cognitive neuroscience have important implications when building technologies, as we learn to transfer abilities that are natural to humans to leverage the strengths of machines. Machines can also be used to learn further about human perception, because technology allows scientists to reproduce impossible events and observe how humans would respond and adapt to those events. This loop from human to machine and back again can help transfer what we learn from our evolutionary intelligence to future machines and AI. This session will address progress and challenges in applying human perception to machines, and vice versa.
- Date:
- Speakers:
- Mar Gonzalez-Franco; Olaf Blanke; Mel Slater; Ana Tajadura-Jiménez
- Affiliation:
- Microsoft; Ecole Polytechnqiue de Lausanne; University of Barcelona; Universidad Loyola Andalucía & University College London
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Mar Gonzalez Franco
Principal Researcher
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