Today, the Chan Zuckerberg Initiative (CZI) announced the expansion of its work in artificial intelligence to help ensure that educational tools that leverage ai are based on research and best practices for teaching and learning. <a target="_blank" href="https://chanzuckerberg.com/education/ai/”>CZI launched two new ai developers<a target="_blank" href="https://chanzuckerberg.com/blog/education-technology-2025-czi-journey/”>eloper tools for education designed to allow developers to integrate high-quality educational content seamlessly into their platforms. Knowledge graph helps developers improve ai system inputs by aligning them with scientific learning research, state academic standards, and curricula, while Evaluators Help developers evaluate ai system outputs to ensure they meet the accuracy, rigor, and quality essential for teaching and learning.
In addition to these new private beta tools, CZI also announced the appointment of a new advisory board that includes experts in schools, data privacy, artificial intelligence, educational technology, and learning sciences.
“With the rapid growth of artificial intelligence, improving the quality of results from large language models is increasingly important, especially when student learning and outcomes are involved,” he said. <a target="_blank" href="https://chanzuckerberg.com/blog/education-technology-2025-czi-journey/”>Sandra Liu Huang, head of education at CZI. “CZI is partnering with education, research and technology experts to help ensure ai tools are high quality and support educators' efforts to unlock the full potential of every student.”
These new tools are part of CZI's efforts to help schools address everyday challenges by co-creating tools with educators and providing technology developers with resources to create high-quality ai solutions for education and backed by research.
Basic ai Resources for Educational Developers
Through Knowledge Graph and Evaluators, CZI is using its learning sciences expertise and technical strengths to enable edtech developers to incorporate high-quality, rigorous educational content into their platforms and improve the overall infrastructure of educational products powered by ai.
To help developers improve the quality of their contributions, Knowledge Graph will launch with two key interconnected data sets: a high-quality, openly licensed mathematics core curriculum in partnership with Illustrative Math, and academic standards from the 50 states in partnership with 1EdTech.
For evaluators, CZI also worked with academic experts to help educational technology developers help teachers close the gap in students' reading skills. They leveraged a literature rubric from Student Achievement Partners to assess the complexity of ai-generated text results. They also worked with English language arts experts from The Achievement Network and Gradient Learning to evaluate the data set.
The private beta phase includes initial collaboration with Playlab and Diffit, who are testing tools to enhance their ai-based educational offerings.
Education Advisory Board
CZI also announces its Education Advisory Council, bringing together a diverse group of experts to help guide efforts to advance the use of ai to transform learning and improve educational outcomes.
The members of the Advisory Council are:
Daniel Carroll
Former Chief Product Officer and Co-Founder of Clever
Richard Culata
General Director of ISTE+ASCD
Alina von Davier
Head of Assessment at Duolingo, CEO and Founder of EdAstra tech and VC Partner at LearnLaunch Accelerator
Luis Gomez
Professor of Education at UCLA and member of the National Academy of Education
Babak Mostaghimi
Founding Partner of LearnerStudio
Amelia Vance
Amelia Vance, founder and president of the Public Interest Privacy Center (PIPC)
“We know more than ever about how children really learn. And that is the objective: to build a bridge between the science of learning and its incorporation into this new technology.”
“One of the challenges right now is that ai results may appear correct, but may contain inaccuracies. “So we believe that one of the first steps to making general ai more pedagogically aligned (more useful in the classroom) is to actually measure the quality it is returning.”
“Put simply, we're really focused on both improving ai system inputs and evaluating those system outputs by being really intentional in our work with edtech developers.”
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