AI Ethics in Education Lit
Key Questions
What ethical issues are addressed in AI education literature?
Systematic reviews cover bias, privacy, equity, and inclusivity in K-12 and higher ed via AI automation. They highlight dual-edged impacts and call for human-centered policies. Pre-service teacher views underscore the need for urgent frameworks.
How does AI support neurodiverse and inclusive learning?
AI tools like conversational agents, predictive text, and personalized platforms aid neurodiverse students and diverse learners. Resources list five essential tools for inclusion and six free tools for interest-based learning. They promote equity in assistive technology.
What do studies say about AI's role in educational equity?
Literature reinforces AI's potential for inclusivity but flags risks like bias and privacy breaches. Calls emphasize human-centered policies to balance benefits and harms. Automation's dual impacts require ethical frameworks for K-12 and higher ed.
How are pre-service teachers viewing AI ethics?
Pre-service teachers express concerns over bias, equity, and privacy in AI educational applications. Studies capture their perspectives amid rising automation. This informs urgent calls for comprehensive ethical training and policies.
What AI tools promote inclusivity in schools?
Tools from 'The Universal Sandpit' include six free AI and web-based options for diverse learners, supporting neurodiverse needs. They enable personalized, interest-based learning and assistive tech. These address ethics like equity and inclusivity in education.
Systematic reviews/studies on K-12/higher ed ethics (bias, privacy, equity, inclusivity via automation); pre-service teacher views; calls for human-centered policies. Reinforces dual-edged impacts, urgent frameworks.