Algorithm for Change: The $1.5M AI/ML & xR Access to Education Competition

Helping low income, underrepresented minority and first generation students get to and through college with emerging technologies

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The NYU Social Entrepreneurship Program is proud to announce a new AI/ML & xR Access to Education Challenge with support from the Bill & Melinda Gates Foundation, which will offer one of the world's largest prizes for the AI/ML & xR community focused on solving challenges in postsecondary education.

About Algorithm for Change

Algorithm for Change (AFC) is a $1.5 million dollar competition designed to encourage innovative thinking and application of artificial intelligence (AI), machine learning (ML) and augmented reality (xR)1 to address enduring challenges in U.S. post-secondary education for students at risk of not enrolling and/ or graduating, with a particular focus on low income, underrepresented minority and first generation (LIMFG) students. The competition seeks innovative solutions that can serve as models of best practice and taken to scale based on demonstrated success. For-profit, not-for-profit, governmental and educational organizations are eligible to apply. Underrepresented founders are strongly encouraged to apply.

Algorithm for Change is comprised of two separate competitions: the AI/ML track, administered by the NYU Social Entrepreneurship Program, and the xR track, administered by Techstars.

To learn more about the xR competition, visit
Note: xR Challenge applications will open on March 19, 2018.

AI/ML Track Prizes

Submissions will be judged by a panel of prominent entrepreneurs and educators. One (or more) winners will be selected from each of the categories below:

  • Tier 1 - Ideation: $100,000 cash prize plus coaching and mentoring
  • Tier 2 - Validation: $300,000 cash prize plus coaching and mentoring
  • Tier 3 - Commercialization: $700,000 cash prize plus coaching and mentoring


LIMFG enrollment and graduation rates lag behind that of their wealthier, white and Asian American peers. The difference is staggering. Whereas 42 percent of whites and 63 percent of Asian Americans between 18 and 24 enrolled at degree-granting, postsecondary institutions in 2015, only 37 percent of Latinxs and 35 percent of blacks matriculated.2 Forty five percent of whites and 61 percent of Asian Americans between 25 and 64 had earned a degree or certificate in 2014, while just 21 percent of Latinxs and 29 percent of blacks had.3

At the community college level, LIMFG students graduate and transfer to four-year institutions at significantly lower rates as well. Almost one in five white students and one in four Asian American students completed this transfer pathway after six years, while just one in 10 Hispanic students and about one in 12 black students did.4 Achievement and attainment gaps are substantial. When coupled with the rising cost of tuition and an anticipated “skills gap” of nearly 11 million jobs by 2025, the urgency of tackling the problem becomes even more acute lest the gaps widen further.5


Emerging technologies like AI and ML have immense promise, but their true value and impact are scarcely understood in general, much less within the context of education. This competition seeks to shine an intense spotlight on these technologies and their potential to harness vast and growing datasets to better identify micro and macro pathways for success, better support students at risk through targeted interventions, and better prepare those students academically for promising lives and careers.

For many reasons, education is often one of the last fields to adopt and fully embrace new technologies--stakeholders are many and varied; decision makers are difficult to reach; and practitioners feel perpetual change fatigue. The competition aspires to attract and incent a diverse pool of entrepreneurs to invest in education and in diversity. In so doing, the competition hopes to spur ongoing awareness, discussion and debate about the inherent potential and limits of AI and ML when applied to post-secondary education in order to drive thoughtful and sustained investments, which lead to quicker and sustained closure of achievement and attainment gaps in the U.S.


Awards are intended to facilitate the further development and dissemination of AI and ML technologies and practices that, for one or more groups of LIMFG students, narrow achievement gaps, increase graduation rates, increase student academic achievement, and smooth or create new student pathways to success in post-secondary education, as demonstrated with meaningful data in terms of either:

  1. LIMFG persistence and graduation: student progress from term to term, particularly from year one to year two and transfer from two-year to four-year institution, as well as completion/ attainment of associate’s or bachelor’s degree within six years
  2. LIMFG application and enrollment: secondary students who submit applications and ultimately enroll at degree-granting institutions

Do you have an idea, a prototype or a company that helps LIMFG students get to and through college? Then this competition is for you.


  1. The AI and ML track of the competition will be administered by the NYU Social Entrepreneurship Program, and the xR track will be administered by Techstars.
  2. The Condition of Education 2017. Report. National Center for Education Statistics, U.S. Department of Education. 2017.
  3. A Stronger Nation. Report. Lumina Foundation. 2016.
  4. Shapiro, D., Dundar, A., Huie, F., Wakhungu, P., Yuan, X., Nathan, A & Hwang, Y., Completing College: A National View of Student Attainment Rates by Race and Ethnicity – Fall 2010 Cohort. Report. National Student Clearinghouse Research Center. 2017.
  5. Carnavale, A., Smith, N., & Strohl, J. Recovery: Job Growth and Education Requirements Through 2020. Report. Center on Education and the Workforce, Georgetown University. 2013.

Questions about the competition? Interested in being a reader, judge, or sponsor? Email us at

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