The main goal of the study is to explore the ethical challenges and implications of using artificial intelligence (AI) in K-12 educational settings and to provide resources and strategies for educators to navigate these challenges while integrating AI into classrooms.

Methods: The study synthesizes existing literature on AI applications in education, identifies ethical challenges, and reviews instructional resources from the Massachusetts Institute of Technology's (MIT) Media Lab and Code.org to support teachers and students in understanding AI and its ethical implications.

Key Findings:

• AI applications in education, such as personalized learning platforms and automated assessment systems, offer significant benefits for students and teachers.
• Ethical challenges, including bias, privacy concerns, and surveillance, are prevalent in AI systems used in K-12 education.
• Educational resources from MIT Media Lab and Code.org provide valuable tools for teaching AI and ethics to K-12 students.

Implications: The findings emphasize the need for educators to be aware of and address the ethical challenges associated with AI in education. By doing so, they can better harness AI's potential to enhance learning experiences while safeguarding against its risks.

Limitations: The study primarily focuses on the U.S. educational context, which may not fully represent ethical concerns in other regions. Additionally, there is limited research on how K-12 teachers can effectively integrate AI ethics into their instructional practices.

Future Directions: Future research should explore the development of culturally relevant pedagogies that address AI ethics and the provision of professional development opportunities for K-12 teachers to enhance their understanding and teaching of AI and its ethical implications.

Title and Authors: "Artificial intelligence in education: Addressing ethical challenges in K-12 settings" by Selin Akgun and Christine Greenhow.

Published On: September 22, 2021

Published By: AI Ethics Journal