(SAMPLE) Introduction to AI in Education Components
The Ethical Implications of AI in Your Classroom
AI can have a significant impact on student learning and teacher practices, so it is important to consider the ethical implications of its use. Teachers should consider the potential for bias, fairness, and privacy concerns when using AI in the classroom.
Risk of Bias: AI might unintentionally reinforce societal biases, such as those related to race or gender. It's crucial for educators to be aware of this when using AI tools.
Fairness Issues: AI tools, like automated grading systems, might not always consider the full context of a student's work, leading to potentially unfair outcomes.
Privacy Matters: AI tools need data to work, and that data often comes from the students themselves. It's important to ensure that student privacy and data security are respected when using these tools.
Openness and Accountability: It's important for teachers to be open about how they're using AI in the classroom. Students should understand how these tools are helping them learn and potentially assess their work.
Student Involvement: When it comes to using AI in the classroom, students should have a say. We suggest asking for their feedback on how these tools are used and how they can be improved to better support their learning.
Addressing Ethical Concerns
As AI becomes increasingly present in our lives, it is important to consider the potential for bias and unfairness in AI use, and work to mitigate these concerns. Here are some tips for addressing and working to mitigate these concerns:
Choose AI tools and applications carefully: Ensure that AI tools and applications are designed and used in a way that is fair and unbiased. For example, if an AI tool has "expert" chatbots, but all the avatars are of one gender or ethnicity, this would be a signal that the tool is biased.
Train students on identifying and mitigating bias: This may involve providing resources and training on how to recognize bias in AI-generated content. Students can provide feedback to you and also the makers of the tool itself.
Monitor AI use in the classroom: Make sure that AI in the classroom is being used in a fair and unbiased way. We suggest testing any tool that you are planning to use in the classroom to verify the quality and accuracy of the responses.
Solicit feedback from students and parents: Communicate with students and parents about their experiences with AI use in the classroom. Use this feedback to make any necessary adjustments to guarantee that AI is being used in a fair and unbiased way.
AI GUIDELINES FOR STUDENTS
We believe that every summative assignment should include AI guidelines as part of the instructions, guidelines, and rubrics that students are already given.
To make it easy and rememberable, we condensed these guidelines into three actionable options: red light, yellow light, green light.
RED LIGHT: AI USAGE IS NOT PERMITTED IN THIS ACTIVITY
This option is straightforward and leaves no room for interpretation. It is particularly useful for assessments or activities where the primary goal is to evaluate individual student understanding and skills. By explicitly stating that AI collaboration is not allowed, educators can maintain the integrity of the assessment process.
YELLOW LIGHT: PERMISSION FROM TEACHER REQUIRED BEFORE USING AI
This option offers a balanced approach, allowing for the possibility of AI usage while maintaining a level of oversight. The “yellow light” option is particularly useful for long-term projects that require extensive research, group activities where individual contributions are part of a collective grade, or case studies that could benefit from multiple perspectives.
GREEN LIGHT: STUDENTS ARE ENCOURAGED TO USE AI SOFTWARE
This option is the most open, encouraging students to explore the capabilities of AI in their learning journey. Assignments that are ideal for the “green light” option include creative writing tasks where AI can serve as a brainstorming tool, research projects that involve gathering and analyzing large sets of data, or activities that encourage innovation, such as coding projects or design tasks.
