Data Nutrition Project Inc
Tools & practices for responsible AI development, including "nutrition" labels for datasets. Launched out of @BKCHarvard @medialab Assembly Program in 2018 The Data Nutrition Project creates dataset quality standards and fosters conversations around the topics of responsible data creation and use. Our belief is that deeper transparency into dataset health can lead to better data decisions, which in turn lead to better Al. Founded in 2018 through the Assembly Program at the Berkman Klein Center at Harvard University, our research team takes inspiration from nutritional labels on food, aiming to build labels that highlight the key ingredients in a dataset. Examples include metadata and populations, unique or anomalous features regarding distributions, missing data, and comparisons to other 'ground truth' datasets.
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Jersey City
The Data Nutrition Project The Data Nutrition Project Our Mission We believe that technology should help us move forward without mirroring societal biases The Data Nutrition Project team Want to get involved. Contact Us. The Problem Incomplete misunderstood and historically problematic data can negatively influence AI algorithms. Algorithms matter and so does the data theyre trained on.
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