Benetech Inclusive AI Initiatives Break down Barriers to STEM

Schmidt Futures and General Motors Support AI-Powered Initiatives for Accessible Math and Science Materials

Benetech, the leading software for social good nonprofit, announced two significant AI initiatives to reduce barriers to STEM (science, technology, engineering, and math) education and employment for people with disabilities and learning and thinking differences. The programs, supported by General Motors (GM) and Schmidt Futures, a philanthropic initiative of Eric and Wendy Schmidt, are focused on leveraging AI to make complex visuals, graphs, and equations in science and math educational materials accessible to people with dyslexia, vision loss, and other reading barriers. This technology will be used to enhance the accessibility of STEM education materials for students with reading barriers and empower other education stakeholders, including teachers, publishers, researchers, and students themselves, to improve the accessibility of their own materials.

“Betting early on people and organizations addressing big challenges is one of our core guiding principles,” said Kumar Garg, Vice President of Partnerships, at Schmidt Futures. “Math literacy is essential for a 21st century STEM education, the foundation to compete for jobs of the future. Benetech’s vision to make tools that can provide new pathways to make STEM education accessible will transform the livelihoods of millions of students.”

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Benetech brings two decades of expertise leveraging new technology to make reading and learning accessible for people with reading barriers, at scale, through its Bookshare initiative. However, transforming STEM education materials into accessible formats poses a significant challenge. Textbooks have complex formats, full of charts, graphs, and equations that must be manually transformed into accessible formats. The average Math textbook has over 5,000 equations, and it can take three to four months for a human to transform a print math book into accessible formats that can be properly read by a screen reader. This is a significant obstacle for students with reading barriers.

“Can you imagine trying to learn algebra with no equations or graphs?” said Ayan Kishore, CEO, Benetech. “Harnessing the power of AI, we are working to level the playing field for students with reading barriers, so that they have the same opportunity as their peers to learn and succeed independently in STEM.”

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AI for Accessible Math and Textbooks

With continued support from GM, Benetech is harnessing the power of neural networks, machine learning, and other AI techniques to automate the transformation of math educational materials into accessible formats readable by a screen reader. The latest funding from GM will enable Benetech to further build out and test the application in partnership with end-users, including educators, universities, publishers, and other stakeholders in the inclusive education ecosystem.

“Empowering the innovative and diverse talent of the future begins by making strong investments now to help STEM education become more equitable and attainable for students from all backgrounds,” said Kelsey Gaines, General Motors Senior Manager of STEM Education. “We’re excited to collaborate with Benetech to make STEM education materials more accessible and inclusive so that students with disabilities and learning differences can pursue STEM without barriers and see their own success in the classroom and beyond.”

Making Graphs Accessible

The copious information held in graphs and charts, are similarly very labor intensive to transform manually into accessible formats. However, the information contained in them is indispensable to a quality STEM education. With support from Schmidt Futures, Benetech is leading a project to improve the accessibility of graphs and charts in K-12 education. The project will include developing a large open-source dataset of annotated charts and graphs, and a data science competition around designing AI models to automate classification and remediation of graphs and charts.

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