Filtered by tag: student privacy × Clear
Learning Context and AI: A 1EdTech Labs Live Webinar
Matched: AI
1EdTech is hosting a free webinar on February 26 at 11:30 AM ET exploring how AI systems interpret learning context differently from humans. The session argues context should be treated as distinct from data in application design and technical handling, with implications for AI coherence, student privacy, and interoperability standards. It will also mark 1EdTech's shift toward more public engagement on its AI work, followed by a member participation call.
Short on resources, special educators are using AI – with little knowledge of the effects
Matched: AI
U.S. special education faces chronic underfunding and staff shortages, prompting growing use of AI tools to help manage caseloads, draft individualized education plans, support professional training, and assist with disability assessments. While AI shows promise in reducing administrative burden, experts warn of serious concerns including student data privacy risks, embedded bias in training data, and questions about whether AI-generated services meet legal standards required under federal disability law.
Student cheating dominates talk of generative AI in higher ed, but universities and tech companies face ethical issues too
Matched: AI, Artificial Intelligence
Debates about AI in higher education focus mainly on student cheating, but broader ethical issues deserve attention. These include tech companies training AI models on copyrighted material, student data privacy under vendor agreements, and unequal access to AI tools. Experts argue responsibility shouldn't fall solely on students — universities should vet AI tools, disclose vendor terms transparently, and update academic integrity policies, while tech companies must address their own ethical violations.