Teaching with AI

1. AI is transforming work, learning, and human thinking

If the internet changed our relationship with knowledge, AI is going to change our relationship with thinking.

AI revolution underway. Artificial Intelligence is rapidly transforming every aspect of work, education, and human cognition. Unlike previous technological revolutions that primarily impacted manual labor, AI is poised to disrupt knowledge-based professions like law, medicine, and education. This shift is not just about automation, but about fundamentally altering how we process information, solve problems, and create.

Widespread impact. AI's influence extends beyond specific job functions:

• It's changing how we research, write, and communicate
• Altering decision-making processes in various fields
• Raising questions about creativity, originality, and human expertise
• Forcing a reevaluation of educational practices and learning outcomes

2. AI produces average work, raising the bar for human excellence

AI is the new C work. Unique but mostly average.

Redefining standards. AI's ability to produce consistently average-quality work is forcing a recalibration of performance standards across industries and education. This shift has significant implications:

• What was once considered acceptable human performance may now be subpar
• Employers and educators must raise expectations for human contributions
• The value of uniquely human skills like critical thinking, creativity, and emotional intelligence is increasing

Implications for education and work:

• Students need to aim higher than AI-level performance to remain competitive
• Assignments and assessments must be redesigned to evaluate higher-order thinking skills
• Workplaces will expect employees to add value beyond what AI can produce

3. AI literacy is essential for future success in all fields

AI literacy is an important new skill.

Universal need for AI competency. As AI becomes ubiquitous, the ability to effectively use and understand AI tools is becoming a core competency across all disciplines. This literacy encompasses:

• Understanding AI's capabilities and limitations
• Knowing how to craft effective prompts and interpret AI outputs
• Recognizing potential biases and ethical considerations in AI use
• Ability to critically evaluate AI-generated content

Integration into education. To prepare students for this AI-driven future:

• AI literacy should be integrated across the curriculum, not just in computer science courses
• Students need hands-on experience with AI tools in various contexts
• Ethical considerations and responsible AI use must be part of the discussion

4. New strategies needed to maintain academic integrity in the AI era

Detection will continue to have its uses, but it can't be our primary response.

Beyond detection. Traditional approaches to academic integrity, focused on detecting cheating, are becoming less effective in the age of AI. New strategies are needed:

• Emphasize the value of original thinking and human creativity
• Design assignments that leverage AI while still requiring unique human input
• Focus on process and thinking skills rather than just final products
• Develop clear policies on appropriate AI use in academic work

Rethinking assessment. Educators must adapt their evaluation methods:

• Move away from easily AI-replicable tasks
• Incorporate more real-time, in-person assessments
• Use portfolio-based evaluations that showcase student growth and process
• Implement peer review and collaborative projects that highlight human interaction

5. AI can enhance creativity and problem-solving abilities

AI is going to make us all more creative.

AI as a creative partner. Rather than stifling human creativity, AI has the potential to enhance it:

• AI can generate a vast quantity of ideas, overcoming human mental blocks
• It can make unexpected connections, sparking new insights
• AI's lack of social inhibitions can lead to more unconventional ideas

Leveraging AI for innovation:

• Use AI to brainstorm and explore a wide range of possibilities
• Combine AI-generated ideas with human judgment and refinement
• Employ AI to visualize concepts or prototype designs quickly
• Utilize AI to overcome creative blocks or explore new directions

6. Effective AI use requires clear prompts and iterative refinement

Good enough is constantly changing.

The art of prompting. Maximizing AI's potential requires skill in formulating effective prompts:

• Be specific about the desired output, format, and context
• Provide relevant background information and constraints
• Use clear, unambiguous language

Iterative process. Getting the best results from AI often involves:

• Starting with a broad prompt and refining based on initial outputs
• Asking follow-up questions to clarify or expand on AI responses
• Combining multiple AI outputs to create a more comprehensive result
• Human curation and editing of AI-generated content

7. AI-assisted education demands reimagined assignments and assessments

All assignments are now AI assignments.

Rethinking educational tasks. Traditional assignments and assessments need to be redesigned to:

• Incorporate AI as a tool rather than trying to prevent its use
• Focus on higher-order thinking skills that AI can't easily replicate
• Emphasize application, analysis, and synthesis of information
• Encourage students to critically evaluate and improve upon AI-generated content

New assignment types:

• Collaborative projects combining AI and human inputs
• Real-time, in-class activities that showcase individual thinking
• Assignments that require students to explain their AI use and decision-making process
• Projects that apply course concepts to novel, real-world situations

8. Motivation and process-focused learning are crucial in the AI age

I care, I can, I matter.

Intrinsic motivation. With AI able to complete many basic tasks, fostering student engagement becomes even more critical:

• Emphasize the relevance and personal value of learning
• Provide opportunities for autonomy and choice in assignments
• Create a sense of belonging and community in the learning environment

Focus on process. Shifting attention from outcomes to the learning process:

• Make thinking visible by requiring students to document their problem-solving steps
• Use reflective practices to encourage metacognition
• Implement formative assessments that provide feedback on learning strategies
• Design assignments that value iteration and improvement over perfection

9. AI feedback and role-playing offer new educational opportunities

AI can also be a debate partner.

AI as a learning assistant. Leveraging AI for personalized learning experiences:

• Use AI to provide immediate, customized feedback on student work
• Create AI-powered tutoring systems that adapt to individual learning needs
• Employ AI for language practice or simulated conversations

Role-playing and simulation. AI enables new forms of experiential learning:

• Historical figure interviews or debates
• Simulated professional scenarios (e.g., client interactions, ethical dilemmas)
• Practice in different communication styles or cultural contexts
• Exploration of complex systems through AI-powered simulations

10. Writing instruction must adapt to incorporate AI tools responsibly

Writing is what AI does best, and you can't out-prompt AI.

Redefining writing pedagogy. As AI becomes proficient at generating text, writing instruction needs to evolve:

• Focus on higher-level skills like critical analysis, argumentation, and synthesis
• Teach students to effectively use AI as a writing aid (e.g., for brainstorming, editing)
• Emphasize the importance of voice, style, and originality in writing
• Incorporate more collaborative and multimodal writing projects

Ethical considerations. Addressing the ethical implications of AI in writing:

• Develop clear guidelines for appropriate AI use in academic writing
• Teach students to critically evaluate and fact-check AI-generated content
• Emphasize the importance of proper attribution and transparency in AI use
• Discuss the broader societal implications of AI-generated text (e.g., misinformation, authenticity)

Last updated: August 8, 2024