7 Things You Can Do With AI (But Really Shouldn't...)

Outline

0–5 minutes - Welcome & Session Framing
The session begins with brief introductions and an overview of the goals. The presenters introduce the theme “7 things you can do with AI (but really shouldn’t…)” and explain how the “Seven Deadly Sins” metaphor will guide the structure of the session. To engage participants immediately, a live poll (e.g., Mentimeter or Slido) is used to ask: “What’s one way you’ve seen AI used badly?” A couple of volunteers share their examples with the group.
5–10 minutes - Why This Matters: Ethics and Pedagogy
Participants are given a short, focused overview of why examining AI misuse is critical in education, covering issues of bias, critical thinking, ethics, and trust. The presenters connect these themes to the ISTE Educator Standards: Citizen, Collaborator, and Analyst. A quick think–pair–share invites participants to reflect on where they see the greatest risk in their own contexts, helping them anchor the session in their professional reality.

10–53 minutes - The Seven Deadly AI Sins - Misuse and Reframe
The main body of the session explores each of the seven “AI sins” in turn, spending approximately six minutes on each. For each sin, the presenters:

1) Introduce a real or simulated example of AI misuse.

2) Explain how it connects to the corresponding “sin” and discuss its educational implications.

3) Engage participants in a short analysis or reflection.

4) Reveal a positive, thoughtful alternative use.

The format for each sin is consistent: one to two minutes are spent presenting the scenario (e.g., “Sloth” illustrated through a student outsourcing an entire essay to AI). Two minutes follow for brief peer discussion or quick individual reflection on why the scenario is problematic in practice. The presenters then spend two minutes unpacking the sin’s ethical and pedagogical implications and offering a constructive reframe, linking it to practical classroom or professional strategies. Throughout, participants are encouraged to use their devices to test prompts or quickly explore examples, keeping the session active and participatory.

53–58 minutes - Individual Reflection: “Which is the Deadliest Sin?”
After all seven sins have been explored, the presenters briefly summarise them and their corresponding positive reframes. Participants are then invited to reflect individually on which misuse poses the greatest challenge in their own contexts. Using a live poll or a short written response, they answer the question: “Which of the seven AI sins is ‘deadliest’ in your setting, and why?” The live poll results are displayed, offering a quick snapshot of the group’s perspectives and prompting brief, whole-group insights.

58–60 minutes - Wrap-Up and Next Steps
The session closes with a concise recap of key themes: moving from misuse to mindful use of AI. Participants are provided with a link to session resources, including the seven-sins framework and further reading. The presenters thank participants and invite continued conversation beyond the session.

Engagement Tactics
Throughout the session, engagement occurs every few minutes through a blend of peer-to-peer discussion, quick reflections, and device-based interactions such as live polls and optional prompt testing. Scenario-based learning anchors the content in realistic contexts, and the final individual reflection ensures participants leave having applied the ideas to their own practice. The pacing balances presenter input with regular interaction, sustaining attention and encouraging critical engagement without requiring extended group activities.

Outcomes

After this session, participants will be able to identify and critically evaluate seven common misuses of AI in education, using the “Seven Deadly AI Sins” framework to analyse their ethical, pedagogical, and practical implications. They will examine and interpret AI-generated outputs to detect issues such as bias, lack of authenticity, over-reliance, or misuse in assessment, and will gain strategies for using these outputs as teachable moments or professional reflection tools. Participants will collaboratively re-frame problematic scenarios into constructive, inclusive applications of AI, drawing on multiple perspectives to design thoughtful approaches tailored to their own contexts. They will also be able to apply clear strategies and protocols for integrating AI in ways that preserve human judgement, promote digital citizenship, and support deeper learning. By the end of the session, attendees will have developed a richer understanding of both the pitfalls and the transformative potential of AI, and will leave with practical examples, discussion frameworks, and adaptable classroom ideas to support responsible and empowering AI use.

Supporting research

OECD / European Commission. (2025). Empowering Learners for the Age of AI: Draft AI Literacy Framework.
Outlines core domains and competencies in AI literacy for K–12, positioning AI literacy as essential in modern education systems.
URL: https://ailiteracyframework.org/wp-content/uploads/2025/05/AILitFramework_ReviewDraft.pdf

UNESCO. (2023). Guidance for Generative AI in Education and Research.
Provides policy guidance, ethical frameworks, and pedagogical principles for integrating generative AI responsibly.
URL: https://www.unesco.org/en/articles/guidance-generative-ai-education-and-research

UNESCO. (2024). AI Competency Framework for Teachers.
Defines the knowledge, skills, values, and progression levels educators need to integrate AI in ethical, human-centred ways.
URL: https://ju.se/download/18.53389cd2193ed80e16f93737/1737107948692/UNESCO%20AI%20competency%20for%20teachers.pdf

International Society for Technology in Education (ISTE). (2023). AI in Education: Practical Guidance for Educators and Leaders.
Provides strategic recommendations, classroom strategies, and policy considerations for integrating AI in alignment with ISTE Standards.
URL: https://iste.org/ai

Cassidy, R. et al. (2023). Use Scenarios & Practical Examples of AI Use in Education.
Presents classroom AI use cases that illustrate both potential and risks, useful for scenario design.
URL: https://arxiv.org/abs/2309.12320

Perkins, M. et al. (2023). The AI Assessment Scale Revisited (AIAS): A Framework for Ethical Integration of Generative AI in Educational Assessment.
Proposes a scale to guide valid, fair, and pedagogically sound use of AI in educational assessment.
URL: https://arxiv.org/abs/2412.09029

Mollick, E. & Mollick, L. (2023). Assigning AI: Seven Approaches for Students, with Prompts.
Discusses pedagogical roles for AI in learning (e.g., AI coach, Socratic guide) and highlights associated risks.
URL: https://arxiv.org/abs/2306.10052

Zawacki-Richter, O. et al. (2024). Developing an Artificial Intelligence Literacy Framework: Evaluation of a Draft.
Empirical study refining AI literacy frameworks, focusing on critical, civic, and technical dimensions.
URL: https://www.sciencedirect.com/science/article/pii/S2666920X24000158

UNESCO / Global Review. (2024). Integrating AI in Education: Navigating UNESCO Global Guidelines.
Reviews obstacles, opportunities, and ethical implications in aligning AI integration with UNESCO guidelines and the SDGs.
URL: https://chemrxiv.org/engage/api-gateway/chemrxiv/assets/orp/resource/item/67d5cbf681d2151a0281479b/original/integrating-ai-in-education-navigating-unesco-global-guidelines-emerging-trends-and-its-intersection-with-sustainable-development-goals.pdf