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What does digital inclusion look like in the age of AI? Over 6,000 of the world’s 7,000-plus living languages remain digitally disadvantaged.
What does digital inclusion look like in the age of AI? Over 6,000 of the world’s 7,000-plus living languages remain digitally disadvantaged.
AI+Science: Accelerating Discovery is an interdisciplinary conference bringing together researchers across physics, mathematics, chemistry, biology, neuroscience, and more to examine how AI is reshaping scientific discovery. Experts will separate hype from reality, spotlighting where AI is already enabling genuine breakthroughs and where its limits and risks remain.
AI+Science: Accelerating Discovery is an interdisciplinary conference bringing together researchers across physics, mathematics, chemistry, biology, neuroscience, and more to examine how AI is reshaping scientific discovery. Experts will separate hype from reality, spotlighting where AI is already enabling genuine breakthroughs and where its limits and risks remain.
While Large Language Models (LLMs) show promise in many domains, relying on them for direct policy generation in games often results in illegal moves and poor strategic play.
While Large Language Models (LLMs) show promise in many domains, relying on them for direct policy generation in games often results in illegal moves and poor strategic play.
Leaders and members of established organizations – from governments to hospitals and nonprofits – are zealously exploring ways to harness these powerful tools to amplify their intended impact. Today, nearly every organization is actively experimenting with AI, whether through formal initiatives or informally, within their operations.
AI’s deployment in real-world organizational settings, however, may also spark transformations beyond those of individual organizations and the communities they serve. First, because the creation, development, and governance of these new tools in the real world present formidable challenges that transcend traditional boundaries across organizations, but also across industries, and even sectors (public, private and nonprofit). Such challenges foster, and indeed necessitate, new or different ways of partnering across organizations, industries and sectors. I call these AI-driven partnerships. Second, because AI-driven partnerships may hold the promise of creating value that no single industry or sector could achieve alone and unlock benefit for all society beyond the direct communities that the individual organizations may serve.
In this presentation I delve into my empirical research on two case studies of AI-driven cross-sector partnerships. These are real-world research studies that examine the deployment of AI ‘in the wild’, in humanitarian aid initiatives and health settings. In humanitarian aid initiatives, we examine over 18 months the design and deployment of human-AI teams that bring together humanitarian agencies, ‘tech for good’ firms, and local communities, with artificial intelligence tools (both generative and non), to address urgent needs in areas in conflict (Gaza and Ukraine). In health settings, we examine the deployment of an open-source AI application into hospitals. This initiative brings together a private technology firm, hospital staff (medical professionals, governance experts, and leadership), and patient and public representatives. This program of research provides empirical evidence of how AI-driven cross-sector partnerships reshape established partnership paradigms and collaboration models, generating new in-context governance mechanisms and emerging business models.
