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The AI Index, currently in its ninth year, tracks, collates, distills, and visualizes data relating to artificial intelligence.
The AI Index, currently in its ninth year, tracks, collates, distills, and visualizes data relating to artificial intelligence.
The possibility that AI will automate most cognitive labor is worth taking seriously. How should we adapt to this transformation? I start from the perspective, articulated in the essay “AI as normal technology”, that the true bottlenecks lie downstream of capabilities and that AI’s impacts will unfold gradually over decades. If this is true, there are major gaps in our current evidence infrastructure, because it over-emphasizes the capability layer.
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The possibility that AI will automate most cognitive labor is worth taking seriously. How should we adapt to this transformation? I start from the perspective, articulated in the essay “AI as normal technology”, that the true bottlenecks lie downstream of capabilities and that AI’s impacts will unfold gradually over decades. If this is true, there are major gaps in our current evidence infrastructure, because it over-emphasizes the capability layer.
In mid-July, a working group focused on AI for the environment convened to outline future directions that would leverage AI to address pressing environmental challenges, ranging from biodiversity and conservation biology to water availability and sustainable communities. The group focused on the concept of building a thrivable planet for all species – not just one that is merely habitable. With the backdrop of the Stanford Educational Farm, we leveraged a human-centered design process to focus on how we might harness AI to uniquely address a range of stakeholder needs. Our objective was to develop an array of prototype projects that lead to insights about future directions for AI in the environmental and sustainability realms. Project prototypes included halting slavery in the seafood industry, intelligent tools for ensuring water and food security, and intelligent approaches for managing species migration. Based on these projects, we identified the following overarching themes that would be exciting to pursue through collaborative research: (1) Predicting, detecting and mitigating or incentivizing environmental transitions, (2) quantifying well-being and compatibility with one’s environment, (3) environmental justice and human rights, (4) opening of new data streams and achieving interoperability of existing data streams.
