Source-iabac
Artificial intelligence holds significant promise for revolutionizing education, according to Dan Rosensweig, Executive Chairman at Chegg, a leading student learning platform. In an interview ahead of his appearance at the TNW Conference on June 20, Rosensweig shared insights into how AI, particularly language models, can enhance the educational experience for both students and teachers.
When ChatGPT was launched in 2022, it triggered widespread panic in schools and academia. The AI model, capable of answering questions and writing texts, was quickly criticized as a tool that could enable cheating and undermine learning. However, by 2024, the initial panic has subsided, and the education sector is beginning to recognize the potential of large language models (LLMs) to support educational efforts.
Despite the potential benefits, Rosensweig emphasizes that general-purpose LLMs are not specifically designed with students’ learning processes in mind. These models can process vast amounts of data and summarize information effectively, but they are also prone to providing inaccurate answers and even hallucinating. As Rosensweig points out, “Generalist LLMs have no obligation to be accurate, or to be personalized, and they don’t know any individual student’s situation when it comes to what they know or what they don’t know.”
The Case for Education-Specific Small Language Models
To truly align AI’s potential with educational outcomes, Rosensweig argues for the development of education-specific small language models (SLMs). Unlike their larger counterparts, SLMs may have a more limited capacity to process information and generate text, but they are more efficient in meeting the specific needs of students and educators.
Rosensweig identifies two key elements necessary for building effective education-specific SLMs. The first is the incorporation of pedagogy by design. This involves developing models that understand how students learn best, what their individual needs are, and how to assess learning outcomes to support continuous progress. The second element is a proprietary, accurate dataset large enough to train AI across different subject areas. Chegg, for instance, has developed 26 SLMs using over 100 million pieces of learning content created over the past decade.
These education-specific SLMs have the potential to provide personalized learning support, which can significantly benefit the learning process. As Rosensweig notes, “It starts with the learning process itself and then offers a blend between critical thinking and actual employable skills.”
Machine Learning, AI, and the Future of Education | Marc Natanagara | TNW ConferencexBrookdaleCommunityCollege
Looking Ahead: AI In Education and the Future of Learning
As the education sector continues to evolve, the integration of AI and specifically tailored language models will likely play an increasingly important role. Rosensweig’s insights highlight the need for a thoughtful approach to AI in education, one that prioritizes accuracy, personalization, and pedagogy.
Dan Rosensweig is one of the many tech luminaries speaking at this year’s TNW Conference, taking place on June 20-21 in Amsterdam. The TNW conference promises to be a platform for exploring the latest innovations in technology and their implications for various sectors, including education. For those interested in attending, there is a special offer available: use the code TNWXMEDIA at checkout to receive 30% off business passes, investor passes, or startup packages (Bootstrap & Scaleup). Additionally, there is a 50% discount for the Women in Tech ticket.
In conclusion, the potential of AI to transform education is immense, but it requires a focused approach that leverages education-specific models and accurate data. As the sector moves forward, embracing these innovations will be key to enhancing the learning experience and equipping students with critical thinking and employable skills. Dan Rosensweig’s vision for AI in education underscores the importance of this ongoing transformation and the need to align technological advancements with educational goals.
