Our 2022-2023 Impact Report is here! Read on to meet AI4ALL Changemakers and champions.

Results

Our Work is Having an Impact in AI

AI4ALL Is Nurturing New AI Leaders

AI4ALL Programs are Designed to Create Changemakers

AI4ALL’s programs are deeply rooted in research and continually tested and refined. Our curriculum is developed in-house by content experts and educators, reviewed by leading AI researchers and industry experts, and tested at top AI institutions around the world. AI4ALL alumni have access to a lifelong network of support and are already making significant impacts in the field through research and outreach.

Who We Serve

AI4ALL strives to center people who have been historically excluded from AI and we are improving each year. This data pertains to our 2021 Changemakers in AI community.

  • 77.6% Woman
  • 21.2% Man
  • <1% Non-binary
  • <1% Another gender
  • 21.1% East Asian
  • 16.1% South Asian
  • 11.9% Asian
  • 5.3% Southeast Asian
  • <1% Central Asian
  • 15.2% Black/African American
  • 12.8% White Non-Hispanic
  • 12.3% Hispanic/Latinx
  • 2.9% Middle Eastern/North African
  • 1% Native Hawaiian/Pacific Islander
  • <1% Native American/Indigenous

Program Goals and Impact

  • Developing Technical Skills

    88% of alumni are pursuing or plan to pursue a degree or coursework in CS/AI at the college level

  • Nurturing Interest in AI

    86% of alumni are interested in
    a career in AI

  • Attaining Internships

    50% of alumni attained an internship in 2021

  • Now is a Critical Time for AI

    There is a diversity crisis in AI and computer science: a homogenous group of technologists is building AI solutions for our diverse population. The global economic impact of AI is expected to reach $15.7 trillion by 2030, and we’re already seeing AI incorporated into areas like medical diagnosis, self-driving cars, and customer support. At the same time, under 14% of AI researchers globally are women, and the numbers are even more dismal for people of color in advanced STEM roles: and Black and Hispanic men and women make up under 11% of people employed in science and engineering jobs in the US. This lack of diversity results in biased AI products that, at best, don’t serve everyone and, at worst, actively harm underrepresented groups. There is evidence that existing societal biases, including sexism, racism, and other forms of discrimination, are being built into AI products. It is crucial to take action now to ensure that everyone has the opportunity to guide the creation of AI as a tool for good.

Barriers to getting into AI

  • Access: Lack of Awareness and Exposure

    • Only 45% of high schools in the United States teach Computer Science 1
    • Only 1 in 4 students (26%) who attend high-poverty schools have access to any CS course in their school 2
    • Without curriculum that is engaging, culturally relevant, or aligned with the interests of historically excluded groups, CS will continue to be perceived as solitary, lacking interaction, and lacking connection to societal challenges 2

  • Interest: Lack of Technical Training, Confidence, and Feelings of Belonging

    • Barriers that prevent historically excluded talent from entering this field including a lack of exposure to technical concepts early; few relatable role models and mentors; and lack of peer-to-peer support 3, 4, 5, 6
    • Students question their belonging in new academic settings, especially when there is stigma or stereotype threat 7
    • AI4ALL program elements align with the 10 effective features of successful K-12 STEM intervention programs for historically excluded groups 7, 8
    • Research shows self-efficacy has the largest impact on STEM entrance, intent to major in a STEM field, and persistence within that major 9

  • Persistence: Lack of Professional Networks, Role Models, and Community

    • Students from historically excluded groups lack access to programs and social networks that prepare and connect them with internship and workforce opportunities 8, 10, 11
    • Research shows the lack of people from historically excluded groups in computing contributes to the limited peer networks, mentors, and role models for students from diverse backgrounds 8, 10, 11
    • Access to direct college admissions support, in addition to peer networks, has been shown to promote retention and persistence of students historically excluded from STEM pathways 12

AI4ALL Alumni are Changemakers

  • Using AI to Improve Surgery

    Amy discovered AI as a student at Stanford AI4ALL in 2015. She spent the next few years deeply researching computer vision, a type of AI, with mentors at Stanford. In 2017, her research that used computer vision to provide feedback to surgeons and improve outcomes for patients won the Best Paper Award among papers about machine learning and health at NeurIPS 2017. Read More.

  • Using AI to Build Community

    A few years ago, Kevin immigrated to the US from Vietnam with a vision of better access to tech classes. When he found that his new high school didn’t offer many, he joined Carnegie Mellon University AI4ALL 2018. After finishing the program, he was inspired to share his new AI knowledge with his high school classmates, so he started his own AI club with the support of an AI4ALL alumni grant. Kevin has already taught 112 of his classmates about AI through his club. Read more.

  • Using AI to Improve the Criminal Justice System

    At Stanford AI4ALL 2016, Bekah was excited to be exposed to a community of people applying AI to social issues. After completing the program, she was able to use her new AI skills in combination with her interest in examining inequities in the criminal justice system at a research internship at MIT on the uses of AI in the criminal justice system. Read more.

  • Using AI to Increase Access to Emergency Care

    Inspired by losing a family member due to excessive wait times for ambulance care, Stanford AI4ALL 2017 alum Viansa joined with 2 fellow alumni to do something about it. The three alumni used natural language processing to create a system to help emergency responders rank the urgency of 911 calls. Their system ensures that people with the most urgent needs are tended to first. Read more.

How We Measure Success

AI4ALL rigorously measures student outcomes using pre- and post-program surveys as well as medium to long-term outcome tracking for our students. We measure success by tracking AI4ALL student progress towards these outcomes.

  • Immediate Impact

    • Increased sense of belonging in the field
    • Development of technical skills
    • Increased confidence

  • Turning-Point Impact

    • Enrollment in post-secondary computer science/AI programs
    • Internships in CS/AI

  • Long-Term Impact

    • Entry into AI and related fields
    • Retention and advancement in AI and related fields

Read the Research