5 AI Projects to Combat Global Inequality
This story was published in Venture Beat.
Artificial Intelligence (AI) promises to improve human welfare and make the world a more educated, meaningful, safer place filled with more possibilities and potential than ever before. However, a real and imminent fear is that biased AIs will deepen inequalities.
Smarter computers, at our behest, are helping us build a more satiated world. As Aldous Huxley would appreciate, satiation when indulged, becomes mere habit. We don’t question how decisions are made anymore, and no one really even knows how the most advanced AIs do what they do. AI makes many of the most important decisions that guide your life’s trajectory; investment, medical, and policy-making decisions all rely on potentially biased algorithms. There’s already a discussion that being able to interrogate an AI system about how it reached its conclusion is a fundamental legal right.
‘But I like the inconveniences.’
We don’t,’ said the Controller. ‘We prefer to do things comfortably.’
But I don’t want comfort. I want God, I want poetry, I want real danger, I want freedom, I want goodness. I want sin.’
― Aldous Huxley, Brave New World
And with good reason. The computers that run AI services have essentially programmed themselves, and they have done it in ways we don’t fully understand. Even the engineers who build AIs cannot fully explain their behavior. The potential for unintentional bias is enormous, but the potential that no one really cares that the biases exist is far worse. One company that helps businesses identify and correct biases in the algorithms they use, had no customers at the time of reporting.
A few key examples of AI bias have been extensively covered in the news; several gaffs with Google’s AI algorithm include labeling some black people as gorillas, image searches for “CEO” returned only pictures of white men and it displayed fewer ads for high-paying executive jobs to women. A LinkedIn advertising program showed a preference for male names in searches. A British pediatrician was denied access to the women’s locker room at her gym because the software it used to manage its membership system automatically coded her title — “doctor” — as male. Microsoft’s Tay Twitterbot had to be shut down when it learned to be racist after just 16 hours. Lastly, a program used by U.S. courts for risk assessment, Correctional Offender Management Profiling for Alternative Sanctions (Compas), was discovered to be more prone to mistakenly label black defendants as likely to reoffend — wrongly flagging them at almost twice the rate as white people (45% to 24%), according to ProPublica.
Here are 5 really cool projects that are applying big data, AI, and/or machine learning to fulfill these new technology’s promise of making the world a better place for everyone.
- 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.
- 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.
- 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.
- 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.
- 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.
There are so many cool AI projects (for example PAWS a Wildlife Conservation AI that use machine learning to predict where poachers may strike) that I have not included here, in the interest of brevity and limiting this article in scope. Tell me your favorite AI project in the comments!