5 AI Projects to Combat Global Inequality

  1. The Allegheny Family Screening Tool: Developed by the county, this predictive algorithm’s workings are public. Its criteria are described in academic publications (a benchmark private companies routinely do not meet, even under duress to explain their results) and interrogate-able by local officials, adoption lawyers, child advocates, parents and even former foster children at public meetings held in downtown Pittsburgh. Sixteen months after the Allegheny Family Screening Tool was first used, preliminary data has already shown that it is effective, including more children in need of services than before.
  2. African Orphan Crops Consortium: The consortium’s goal is to sequence, assemble, and annotate the genomes of 101 traditional African food crops, sometime referred to as “orphan crops” because they have long-been ignored in favor of western crops like corn, wheat, and rice. Crops like the African Yam Bean, the Desert Date and Ber are uniquely adapted to local climates and can increase nutrition. Solving world hunger and climate change issues will require the power of big data, and undoubtedly AI for speeding the development of genome improvements as Monsanto, Syngenta, and Carnegie Mellon University are all developing AI AgTech applications.
  3. Microsoft’s FATE: Fairness, Accountability, Transparency and Ethics in AI. The program was set up to ferret out biases that creep into AI data and can skew results. Lead by principle investigator, Kate Crawford and an (all female!) team of AI research super stars are currently working on collaborative research projects that address the need for transparency, accountability, and fairness in AI and machine learning.
  4. IBM’s Science for Social Good: IBM announced 12 projects planned for 2017. Each Science for Social Good project aligns with one or more of the 17 Sustainable Development Goals, the United Nations’ blueprint to address some of the globe’s biggest inequalities and threats by the year 2030. Poverty, hunger and illiteracy are all targets of these initiatives.
  5. Data 4 Black Lives: Often times policy makers have no data to back racial justice initiatives, because the data simply do not exist. No one has collected or analyzed it. Data 4 Black Lives aims to connect data scientists and activists in order to apply data science tools like artificial intelligence and machine learning, to bring meaning and solutions to impact black people’s lives.

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Founder www.artcompass.io | Scientist. Teacher. Author.

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Dr. Carol Lynn Curchoe

Dr. Carol Lynn Curchoe

Founder www.artcompass.io | Scientist. Teacher. Author.

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