In order for your AI model to benefit whomever it’s intended to serve, you’ll need an interface for users to interact with it. This may just be a new feature integrated into an existing digital product or it may mean building a brand new product around the model. Either way, it will be critical to build a user testing plan to prototype and get feedback on how the solution is working. In what ways do social responsibility principles — like human centeredness, transparency, data privacy, etc — need to show up in the product?
We won’t cover basic product development best practices here so much as focus on those practices relevant to AI solutions.
PJMF has not developed content for this module yet, but let us know you’re interested, and we’ll keep you in the loop if/when it’s released.
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What people, processes, and technology can help ensure our data is effectively managed throughout its lifecycle?
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How do we go about developing an effective AI model, and once it’s refined how do we deploy it to the world safely?
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What is our organizational-wide strategy for how AI should be leveraged to further our mission and how will we get there?
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The Patrick J. McGovern Foundation (PJMF) is a philanthropic organization dedicated to advancing artificial intelligence and data science solutions to create a thriving, equitable, and sustainable future for all. PJMF works in partnership with public, private, and social institutions to drive progress on our most pressing challenges, including digital health, climate change, broad digital access, and data maturity in the social sector.
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