Problem definition is one of the most important parts of the whole AI journey. We know it may seem like an obvious step in the process, but we often see organizations glaze over it or skip it entirely, with real consequences down the road! Not taking the time to properly understand the problem can lead to tech solutions that don't meet your users’ needs, that take longer to develop, that cost more money, or that fail to gain traction once they're out in the world.
Give this step in the journey the full time and dedication that it deserves, and your team will be off on much better footing towards a truly impactful solution. Maybe that will be an AI-based solution? But maybe it won’t!
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Learn through our self-paced group online course
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See how Climate Policy Radar took a problem-first approach to leveraging AI for climate action.
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Let us know if you’re interested in a live session
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How do we navigate the decision to build something custom vs. leverage an off-the-shelf solution?
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How do we think about the data we have or still need, the quality of that data, and the infrastructure required to support a safe and successful implementation?
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From budgeting to building the right team to assessing potential risks, how do we go about planning an AI project?
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With an impactful solution in mind and an AI project plan in hand, how do we craft a strong grant proposal to secure the necessary funding?
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The Patrick J. McGovern Foundation (PJMF) is a global, 21st century philanthropy committed to bridging the frontiers of artificial intelligence, data science, and social impact.
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