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Beyond Interaction: Human-Machine Teaming (UX and AI Series)
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Featuring Carol Smith, Carnegie Mellon University
We stand to gain significant benefits when humans are able to truly collaborate with machines. This progress is not without corresponding risks. We need to design artificial intelligence (AI) systems that are human-centered--designed to work with, and for, people. This requires thinking about engineering in ways that create effective implementations and minimize unintended consequences.
Drawing upon her work at Carnegie Mellon University's SEI, Carol will discuss three areas of focus to advance human-centered AI:
- Designers and systems must understand the context of use and sense changes over time.
- Development of tools, processes, and practices to scope and facilitate human-machine teaming.
- Methods, mechanisms, and mindsets to engage in critical oversight.
We stand to gain significant benefits when humans are able to truly collaborate with machines. This progress is not without corresponding risks. We need to design artificial intelligence (AI) systems that are human-centered--designed to work with, and for, people. This requires thinking about engineering in ways that create effective implementations and minimize unintended consequences.
Drawing upon her work at Carnegie Mellon University's SEI, Carol will discuss three areas of focus to advance human-centered AI:
- Designers and systems must understand the context of use and sense changes over time.
- Development of tools, processes, and practices to scope and facilitate human-machine teaming.
- Methods, mechanisms, and mindsets to engage in critical oversight.