This article from 2016 (https://k12.cioreview.com/cxoinsight/blurring-the-lines-between-educational-technology-and-assistive-technology-nid-23392-cid-143.html) came to light for me recently per a connection that had it cross their path. It led to a very interesting discussion about how relevant this still is in the age of Artificial Intelligence in Education. As AI-driven education tools and platforms enter the marketplace, it’s important to analyze them through the lens of supporting all learners. How is the AI designed to scaffold instruction and provide personalized supports, interventions, and challenges for students with diverse learning needs and abilities? Terms like “differentiation” and “Universal Design for Learning (UDL)” should guide these considerations.

Discussions with some of the people working for these companies also bring consideration to whether they are including these tools and what instructional basis they have used to design the function.

*Do concepts from the Science of Reading guide your AI algorithms?

*How do you ensure materials provide an optimal sequence for students to build decoding skills? Do you align to any specific scope and sequence guidelines?

*How do you to ensure your AI-generated content reinforces effective foundational reading skills??

*How do you balance having an AI “recommend” content while still allowing teacher control and customization?

Additionally, how can current #educationaltechnology and #assistivetechnology leverage AI to make their tools more efficient and more supportive and increase the breadth of the support they can provide? I envision a world of an AI tool that a student with learning differences can easily interact with to gain the support they need, including scanning documents to be read, summarizing the material, highlighting key points, and asking key questions to support comprehension….the possibilities are endless.

As I imagine these future possibilities, I reflect on why any supports under consideration should not be designed exclusively for students with learning disabilities. Rather, they should be built with universal design in mind to benefit all users. The future of AI in education still lies ahead like a wide-open runway. I hope the evolution of these tools is grounded in strong pedagogy, uplifts teacher and student agency, and is informed by educational research.