In an interview, Stanford University Artificial Intelligence (AI) Lab director Fei-Fei Li advocates for more human-centered AI and the benefits it can yield.
She notes although most current AI breakthroughs in pattern recognition are significant, they lack the contextual awareness and learning flexibility of people.
Making technology safer, productive, and better for humans "requires a layer of human-level communication and collaboration," Li says.
She believes returning contextual understanding, knowledge abstraction, and reasoning to AI research is essential for making machines more helpful and useful.
Li cites her Visual Genome image database at Stanford as "exactly the kind of project that's pushing the boundaries of language understanding and visual understanding [by AI]."
Li also sees a strong economic need for more diversity in the AI workforce, which should power greater innovation and creativity while also helping to instill human morals and ethical values within AI.
From Technology Review
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