Preparing Students to Learn, Question, and Thrive in the Age of Generative AI
As part of the SMED GenAI Blog series, I am sharing this interview with our graduate and undergraduate students, colleagues, and members of our broader educational community.
My purpose is not simply to repost an interesting interview. I want to use it as an opportunity to encourage students to listen carefully, think independently, and ask their own questions about the rapidly changing world of Generative AI.
We are living through a period in which AI systems are becoming part of research, learning, writing, creativity, entrepreneurship, and professional practice. For students, this creates new possibilities, but it also requires new forms of literacy, responsibility, and judgment.
I find myself in agreement with many of the arguments presented in this interview. In my own work, I increasingly collaborate with multiple AI systems and agents that support research, writing, planning, content development, and scholarly production. These systems extend my capacity, but they do not replace my responsibility as a human researcher, educator, and decision-maker.
This is why I continue to emphasize AI literacy, epistemic humility, human-in-the-loop governance, and the need for personal or institutional AI constitutions. As students and educators, we must learn not only how to use AI, but also how to question it, guide it, verify it, and remain accountable for the knowledge we create.
As you watch the interview, I invite you to reflect on the following questions:
- What opportunities does Generative AI create for your learning, research, career, or personal development?
- What new skills will students need in order to work responsibly with AI systems?
- How can AI agents support human creativity without replacing human responsibility?
- What does epistemic humility mean when AI systems can generate confident answers instantly?
- Should students begin developing a personal AI constitution to guide how they interact with intelligent systems?
My hope is that this interview will help us move beyond fear, hype, or passive use of AI. We must become active, thoughtful, ethical participants in shaping how AI will influence education, research, work, and society.
Why This Interview Matters
What struck me most about this discussion is that it reflects a reality many of us are beginning to experience:
- AI is becoming a collaborator rather than simply a search tool.
- Success depends less on technical expertise and more on the ability to ask meaningful questions.
- Human judgment remains essential.
- The quality of outputs often depends on the quality of human guidance.
For undergraduate and graduate students, this represents both an opportunity and a challenge.
On one hand, AI can accelerate learning, research, writing, coding, brainstorming, data analysis, and problem solving.
On the other hand, overreliance on AI can create the illusion of understanding without genuine learning.
This is why AI literacy is becoming a foundational skill for the 21st century.
1. My Perspective as an Educator and Researcher
As an educator and researcher, I increasingly find myself working alongside multiple AI systems and agents that support research, writing, content development, and scholarly dissemination. These tools have become valuable partners in my daily work. However, their effectiveness depends not only on the sophistication of the technology, but also on the quality of human guidance, critical thinking, and decision-making. This experience reinforces my belief that AI literacy is no longer optional—it is becoming an essential academic and professional competency.
2. Questions to Consider While Watching
As you watch this interview, I encourage you to think critically about the ideas being presented:
- How might AI agents support your learning, research, or future career?
- What skills will become more important as AI systems become more capable?
- How do we balance efficiency with genuine understanding?
- What responsibilities accompany the use of AI in academic and professional settings?
- How can we remain critical thinkers in an age of increasingly intelligent machines?
3. Connecting to Our SMED Discussions
This interview also connects to several themes we have been exploring in our ongoing discussions about AI literacy, epistemic humility, human-in-the-loop governance, and the idea of an AI Constitution. As AI becomes more deeply integrated into education and society, we must learn not only how to use these systems effectively, but also how to question them, govern them, and use them responsibly. The future will be shaped not simply by AI capabilities, but by the wisdom with which humans choose to apply them.
Related Publications and Blogs
Published Works
Diack, M. (2026). Scaffolding Presence in AI-Enhanced Online Learning: Avatar-Mediated Guidance and AI Tutoring as Complementary Supports. Zenodo.https://zenodo.org/records/20347760
Diack, M. (2026). Le modèle d’orchestration avec l’humain dans la boucle : un cadre collaboratif pour la recherche assistée par l’Intelligence Artificielle (IA) et la production des connaissances. Zenodo.https://doi.org/10.5281/zenodo.20219014
Manuscript Under Revision
Diack, M. From Multimedia to AI: JEDI as a Human-Centered Framework for Learning and Development Effectiveness in AI-Enhanced Education.Currently under revision for TechTrends.
Related Blogs
Moustapha Diack Substackhttps://moustaphad.substack.com
AI for Learning Substackhttps://ai4learning.substack.com
Southern University UNESCO Digital Week Substackhttps://susunescodigitalweek.substack.com
Together, these publications and blogs document my ongoing work on AI literacy, human-in-the-loop research, epistemic humility, open education, JEDI-informed learning design, and responsible AI adoption in education.
Decoding AI for Rookie Teachers: Your Ultimate Guide to Navigating the Tech-Powered Classroom!
Let's be honest, the term "AI literacy" can feel like another piece of jargon tossed into the already overflowing educator's lexicon. But I implore you, dear rookie teachers, to resist the urge to dismiss it as mere buzz. This is not about knowing what ChatGPT is, but grasping the intricate clockwork beneath its surface. It’s about understanding the potential – and the pitfalls – of this technological force reshaping our classrooms.Think of AI literacy as your educator's superpower. It equips you to not only understand and evaluate AI but also to ethically integrate it into your lessons and daily routines. It’s the ability to discern between genuine pedagogical enhancement and technological snake oil.
AI's Inner Workings (Simplified!):
Let's demystify the black box, shall we?
- Machine Learning (ML): Picture a diligent student, absorbing information and refining their understanding through repeated exposure. That, in essence, is machine learning. AI algorithms learn from data, identifying patterns and making predictions. This can manifest in grading systems that adapt to student performance or in identifying subtle learning trends within your classroom.
- Natural Language Processing (NLP): This is the art of enabling computers to comprehend and respond to human language. Your virtual assistant, the chatbot offering support – all powered by NLP.
- Generative AI: The creative engine, capable of producing novel content – text, images, even code. The essay-writing bot? A product of generative AI. Its potential is immense, but so are the ethical considerations.
- Prompting: Consider this your secret weapon, the key to unlocking AI's potential. Mastering the art of crafting precise and effective prompts is crucial. It's about learning to communicate with AI in a way that elicits the desired response, ensuring it aligns with your pedagogical goals.
Why You Need This Skill Set:
In a world increasingly shaped by AI, ignorance is no longer an option.
- Know Your Tools: AI is pervasive, embedded in everything from learning applications to navigation systems. Recognizing its presence is the first step towards harnessing its power.
- Smart Integration: Imagine leveraging AI to streamline lesson planning, personalize instruction to meet the unique needs of each student, or even alleviate the burden of grading.
- Critical Eyeball Test: AI is fallible. It can "hallucinate," fabricating information with an air of certainty. It can also perpetuate biases present in its training data. Your critical eye is essential in detecting these flaws.
- Be the Ethical Guardian: As educators, we have a responsibility to guide our students towards responsible AI citizenship. This includes understanding data privacy, algorithmic biases, and the ethical implications of AI.
Faculty's Mission Control:
Your professors are keenly aware of the seismic shift occurring in education. They are actively preparing to transform you into AI-savvy educators, equipping you with the knowledge and skills necessary to navigate this new landscape.
II. A Whirlwind Tour Through AI's Classroom Journey (From PLATO to ChatGPT)
The narrative of AI in education is not a recent phenomenon; its roots extend further back than one might expect. Let us embark on a brief historical expedition, tracing its evolution from nascent beginnings to the present day.
- The OG Days (1960s-1980s): In the annals of educational technology, the 1960s marked the emergence of AI's early forays into the classroom. Pioneering computer programs like PLATO, designed to teach mathematics and science, laid the groundwork for what would later become "Intelligent Tutoring Systems," sophisticated algorithms attempting to emulate personalized, one-on-one instruction.
- The Quiet Years (1990s-2010s): While the public perception of AI in education may have waned, the technology continued its quiet evolution. Data-driven predictions and advanced machine learning techniques were refined, largely confined to the domain of computer science laboratories rather than permeating the average K-12 classroom.
- The ChatGPT "Boom!" (November 2022 & Beyond): The advent of generative AI, epitomized by the launch of ChatGPT in November 2022, served as a watershed moment. This disruptive technology propelled AI into the mainstream consciousness, igniting a global conversation that shifted the focus from whether AI would infiltrate schools to how it would be integrated responsibly and effectively.
- AI as Your Sidekick, Not Your Replacement: Throughout its history, a consistent theme has underscored the development of AI in education: the concept of AI as a partner, augmenting human teaching rather than supplanting it entirely. This symbiotic relationship, where AI handles certain tasks to free up educators for more personalized interaction, remains the guiding principle.
III. What Everyone's Saying About AI in the Teacher's Lounge (Current Opinions & Hot Takes)
The corridors of academia are abuzz with discourse surrounding the integration of AI, a chorus of opinions both optimistic and apprehensive. Let's eavesdrop on the conversations unfolding in the teacher's lounge, dissecting the prevailing sentiments and concerns.
- Faculty's Mixed Feelings: A recent survey reveals a nuanced perspective among faculty members. While a significant majority (86%) express optimism regarding AI's potential and envision incorporating it into their teaching practices, a substantial portion (40%) acknowledge that they are only beginning their own journey of understanding and mastering AI. So, if you're feeling like a novice, know that you're in good company!
- The "Train the Trainers" Dilemma: A critical bottleneck hindering widespread adoption lies in the lack of adequate professional development. The data reveals that a concerning 68% of educators have not received formal training on AI. It stands to reason that educators cannot effectively teach what they themselves do not fully comprehend.
- The Big Worries on Campus:
- "Is this cheating?!" This is the elephant in the room. A staggering 83% of faculty members express concern about students' ability to critically evaluate AI-generated outputs, raising questions about academic integrity.
- Losing the Human Touch: The potential erosion of human connection is a palpable anxiety. Concerns revolve around diminished student-teacher interaction, job security, and students becoming overly reliant on AI tools.
- Privacy Panic: The protection of student data is paramount. Questions surrounding who has access to this information and the potential for algorithmic bias are legitimate and demand careful consideration.
- The "Policy Void": The absence of clear institutional guidelines on AI use leaves many teachers adrift, uncertain of how to navigate this uncharted territory.
- Best Practices for Getting AI-Smart:
- Hands-On Fun: Embrace experimentation. Engage with AI tools in low-stakes environments to gain firsthand experience and demystify the technology.
- Focus on the "Why": Delve beyond the technical specifications and explore how AI can genuinely enhance learning and teaching outcomes.
- Continuous Learning: The landscape of AI is constantly evolving, necessitating a commitment to lifelong learning and adaptation.
- Clear Rules of Engagement: Institutions must proactively establish clear and comprehensive AI policies to provide guidance and ensure responsible implementation.
- Human-Centered Design: Always remember that AI is a tool designed to augment, not replace, the invaluable human connection that lies at the heart of education.
IV. The Wild West of AI: Debates & Dilemmas for New Teachers (Controversies!)
The integration of AI into education is not without its controversies. Like the Wild West, it presents a landscape of uncharted territory, ethical quandaries, and ongoing debates that demand careful consideration from rookie teachers.
- Too Fast, Too Furious? A central debate revolves around the pace of AI adoption in schools. Are we rushing headlong into implementation before adequately preparing teachers to understand and utilize these tools effectively? Many argue that the answer is a resounding yes.
- Robots vs. Teachers: The Showdown? The perennial fear of technological displacement looms large. Will AI ultimately replace human teachers? While experts largely concur that AI should serve as an assistant rather than a substitute, the apprehension remains palpable.
- What Even Is "AI Literacy," Anyway? The very definition of "AI literacy" is subject to debate. Does it simply entail knowing how to operate AI tools, or does it require a deeper level of critical thinking and the ability to challenge the systems themselves? The answer, undoubtedly, lies in the latter, though the specifics are still being hammered out.
- The Assessment Nightmare: How do we assess student learning in an era where AI can generate essays and complete assignments? This necessitates a fundamental rethinking of traditional testing methods and a shift towards evaluating higher-order thinking skills.
- The Ethical Minefield (Watch Your Step!):
- Data Demons: The privacy and security of student data are paramount. We must address critical questions about who has access to this information and how it is being used.
- Bias Bots: AI algorithms can inherit and amplify biases present in their training data, leading to unfair or discriminatory outcomes. Novice teachers must be trained to recognize and mitigate these biases.
- The Equity Gap: Will AI tools exacerbate the existing divide between well-resourced and under-resourced schools? Ensuring equitable access to AI technology is essential.
- Misinformation Mayhem: AI can generate convincing but false information, making critical evaluation skills more important than ever.
- The "Automation Bias" Trap: Especially for new teachers, there's a risk of blindly trusting AI suggestions without applying critical judgment. Remember, AI is a tool, not an oracle.
- The Carbon Footprint: Training and running AI models requires significant energy consumption, raising concerns about the environmental impact.
V. Crystal Ball Gazing: The Future is Now (or Very Soon!) for AI-Savvy Educators
The future of education is inextricably linked to AI. For educators, embracing AI literacy is not merely an option but a necessity. Let's peer into the crystal ball and envision the transformative possibilities that lie ahead for AI-savvy educators.
- AI Literacy: Your New Superpower: AI literacy is no longer the domain of tech specialists; it is a core competency for all educators, empowering them to prepare the next generation for an AI-driven world.
- Your Personal AI Teaching Assistant:
- Admin Tasks Vanishing: Imagine a future where AI handles up to 70% of administrative tasks, including grading, scheduling, and attendance. This frees up valuable time for teachers to focus on what truly matters: personalized instruction and student engagement.
- Lesson Planning on Autopilot: AI can assist in generating lesson plans, activities, and discussion prompts tailored to specific learning objectives and student needs.
- Personalized Learning for Everyone (Yes, Even You!):
- Student Super-Personalization: AI can adapt content, pace, and feedback for each student, catering to individual learning styles and addressing diverse needs with unprecedented precision.
- Teacher PD, Just for You: AI will curate personalized professional development recommendations based on your career goals and teaching style, eliminating the need for one-size-fits-all training programs.
- Official AI Roadmaps & Frameworks: Expect governments and educational organizations to develop comprehensive guidelines and introductory courses to facilitate ethical and effective AI integration.
- The "AI-Fluent" Workforce: Employers are increasingly seeking individuals with AI literacy, with 66% of leaders stating that they will prioritize candidates with these skills. Acquiring AI proficiency is not just advantageous; it is becoming essential for career advancement.
- Continuous Evolution: AI is a dynamic field, constantly evolving and innovating. Therefore, your learning journey will be ongoing, requiring continuous adaptation and exploration of new tools and techniques.
Building AI Policies in Higher Education: A Crowdsourced Approach to Best Practices
Artificial Intelligence (AI) is reshaping higher education, impacting teaching, learning, research, and administration. Institutions must develop clear, ethical, and adaptive AI policies to navigate this transformation responsibly.The Southern University System (SUS)—as a leading HBCU system—must take a proactive stance in defining AI governance. While Southern University and A&M College (SUBR) is a key institution in this conversation, the broader SUS community, including faculty, administrators, and policymakers, must work together to ensure AI policies align with equity, ethics, and educational excellence.To support this effort, I am sharing an open crowdsourced repository of AI institutional policies, which can serve as a starting point for AI governance discussions across SUS.
Institutions need AI policies to:
✅ Ensure academic integrity (e.g., use of AI in coursework and research).
✅ Protect data privacy (e.g., ethical AI use in student records).
✅ Provide faculty guidance on integrating AI in teaching.
✅ Establish research ethics for AI-driven studies.
✅ Define administrative AI applications (e.g., admissions, advising).Without clear policies, institutions risk inconsistent AI usage, ethical concerns, and potential academic misconduct. A well-structured AI policy protects both faculty and students while fostering innovation.
A Crowdsourced Resource for Institutional AI Policies:
To assist SUS faculty, administrators, and policymakers, I am sharing resouces compiled from leading universities and AI policy experts.
✔ Examples of AI policies from leading universities.
✔ Guidelines on academic integrity and AI usage.
✔ Ethical considerations for AI in education.
✔ Templates to help institutions craft their own policies.
- Tracy Mendolia, has this amazing Padlet that is crowdsourced University Policies on Generative AI. It’s pretty amazing. But it’s also a little overwhelming and hard to navigate. I think padlets are great for collecting things as part of an activity, but personally, find them hard to sort through and figure out what is helpful and isn’t.
- Higher Education Strategy Associates has their AI Observatory which includes this page on Policies & Guidelines. This page does allow for some sorting based on country, and some other key terms (academic integrity, governance, guidelines, inclusion, operations, pedagogy, prohibition, policy, research, and statement). Granted, it isn’t clear what some of those terms means. Still, it’s a useful resource.
- Eaton started to build his own crowdsourced Institutional AI Policies & Governance Structures repository. Other institutions and universities can contribute to the work by submitting their institutional policies to continue to grow or share it with others.
Diack oversees a doctoral research group on AI4STEM. Diack is a leader in Ai4D and the pedagogical integration of AI in the classroom.