General Best Practices 

It’s essential to cultivate a healthy skepticism among students—and in our own practice—regarding the reliability of responses generated by AI. This includes consistently verifying AI outputs against credible sources. Moreover, fostering balanced and diverse perspectives on AI ethics is beneficial. For instance, while AI-generated hallucinations can sometimes lead to misinformation, they also offer opportunities for creative exploration and innovation. By understanding both the potential risks and benefits, students can better leverage AI’s creative capabilities in constructive and ethical ways.

When teaching AI ethics, the vast number of potential ethical issues can feel overwhelming. While it’s important to establish a baseline understanding using resources like OERs, a deeper engagement can be achieved by focusing on one or two ethical concerns that are particularly relevant to the course or the students’ disciplines. For instance, environmental science courses could emphasize the environmental costs of AI, while communications courses might focus on issues like deepfakes and misinformation. Alternatively, allowing students to choose an ethical issue that resonates personally with them can enhance their engagement and motivation to explore the topic further. This tailored approach ensures the learning experience is both meaningful and impactful.

Creating safe discussion spaces is fundamental to teaching AI ethics effectively in the classroom. Instructors need to cultivate an environment where students feel genuinely comfortable sharing their diverse perspectives on complex ethical issues, even when those views might challenge conventional wisdom.When students feel secure enough to contribute their personal experiences and observations, it enriches the learning experience for everyone and helps bridge the gap between theoretical concepts and real-world implications.

Staying current with AI developments represents a crucial responsibility for educators in this rapidly evolving field. This commitment to continuous learning involves carefully monitoring emerging ethical concerns as they arise in the AI landscape and promptly updating course materials to reflect new AI developments. By incorporating recnet case studies and examples, instructors can keep the material relevant and engaging. Furthermore, adapting teaching methods based on student feedback ensures the course remains responsive to learners’ needs and effectively addresses their most pressing questions about AI ethics.

Specific Strategies for Teaching Bias 

As educators, we must carefully consider how biases in generative AI might be perpetuated or overlooked when incorporating these tools into teaching materials or assessments. This is another reason why we need to be careful about using AI detectors for plagiarism, as research showed that AI detectors have been found to be more likely to label text written by non-native English speakers as AI-written.

We also need to engage students in learning about the inherent biases in generative AI, turning this into an opportunity for collective exploration. We should encourage students to identify and discuss the biases they observe in AI-generated outputs, reflecting on the potential causes and implications of these biases.

• • Helping students understand the biases in generative AI – This article by  Edutopia shared a framework from Demarginalizing Design that can be remembered by the mnemonic device, “Am I Right?” to help students examine their own biases and AI biases.
    • Avoiding objective facts.
    • Misinterpreting information in a way that only supports existing beliefs.
    • Ignoring information that challenges existing beliefs.
    • Remembering details that only uphold existing beliefs.
  • Helping students understand the biases in generative AI – This resource developed by Center for Teaching Excellence at the University of Kansas shared a number of interesting classroom activities at the end of the article for educators can explore.

Specific Strategies for Teaching Environmental Concerns 

Educators have a responsibility to inform students about the environmental impact of AI tools. We have an opportunity to make a difference by contributing to carbon offsetting programs and to educating our students on the environmental cost of these tools.

By training students in efficient prompt engineering and helping them understand when to use AI vs. traditional tools, educators can help to reduce the energy consumption associated with these AI tools.

• AI’s Impact on the Environment – This classroom guide developed by AI for Education provided a number of discussion and reflection questions for engaging your students in  exploring the potential impact of Generative AI (GenAI) on the planet.