Session 2: Ethics/Bias/Privacy

Top takeaways from the breakout session discussions

Collaborative Learning: The conversation about AI in education is robust, and there is a recognition that educators, students, and parents are all learning together. This collaborative approach can foster a sense of community and support as everyone navigates the implementation and understanding of AI.

Responsible and Ethical Use: Ethical considerations are crucial when teaching about AI. It is important to model responsible behavior and emphasize that AI is a tool, not a substitute for students' own thinking and creativity. Plagiarism concerns should be addressed, and students should be encouraged to use AI appropriately while citing their sources.

Nuanced Understanding: Developing a nuanced understanding of AI's role in society is essential for the school community. Events like back-to-school nights and faculty meetings can be used to discuss AI's potential benefits and drawbacks. This dialogue helps teachers, administrators, students, and parents gain a deeper understanding of AI's implications.

Privacy and Security: Mitigating the risk of users entering sensitive information is crucial. Schools can establish teams dedicated to testing new AI tools, educating colleagues about privacy concerns, and ensuring compliance with privacy laws. Regular evaluation of the effectiveness of these tools in protecting sensitive information is also important.

Integration in Instruction: AI can be integrated into various subjects, such as science and language learning. Science teachers can use AI tools to enhance experiments and data analysis, allowing students to analyze complex data sets and make predictions. In language learning, AI can be leveraged as a resource, but students should still rely on their own language skills for engagement and learning.