Commercialization
SRI’s investment, innovation, partnership, and product professionals work with federal and commercial clients to inform and accelerate deep-tech innovation through commercial R&D, IP licensing, startup support, and so much more.
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Measuring R&D knowledge diffusion through large databases
Combining SRI International’s expertise in machine learning and science policy to answer hard questions
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Building a new generation of leaders to bridge the growing gap in the energy engineering workforce
Creating a technology talent pipeline with better measurement of energy engineering statistics
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Converting groundbreaking research into practical applications starts with effective management
Enabling research and development professionals to extract more value from breakthrough research
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Facilitating aging in place through the practical use of advanced technology
Researchers at SRI International created the Studio on Aging to develop technologies that help caregivers anticipate adverse health conditions for seniors in order to reduce preventable hospitalizations or transitions to nursing homes.
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Ethical questions and the implications for policy
Data privacy and transparency in data usage, equity and access, and more.
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Fostering reskilling, upskilling, and lifelong learning
Increased responsibility by firms for training, improved access to training, new modes of delivery for training material, refining matching workers to skills, and new definitions for worker credentials.
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Exploring the Human-Technology partnership
Decision-making in blended human-machine hierarchies, new ways of assigning and distributing tasks, new jobs for a new economy, making space for new technologies.
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Restructuring the physical and virtual workspace
Distribution of physical and virtual presence: Teleservices will increase, especially in education and health.
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Design for Trust: Principle #3
When building trust, motivation is more powerful than demonstration or explanation.
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Design for Trust: Principle #2
Trust is a dynamic relationship. It is tentatively granted, then tested over time.
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Design for trust: principle #1
User expectations and perceived risks drive trust requirements.
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In AI we trust? How might we design intelligent systems that inspire trust?
How might we design intelligent systems that inspire trust?