The Friday Download — Show Notes "The Robot Wrote My Essay (Or Did It?)"

This week on The Friday Download, JR asks the question that's haunting every teacher, professor, and parent in 2026: did my student write this — or did their robot?

In The Big Weird, we dig into what the data actually shows about student AI use. Spoiler: over 90% of college students are using AI somewhere in their workflow, but the "everyone is cheating" story turns out to be way more complicated. We also talk about why AI detectors failed spectacularly — flagging human writing, missing obvious bot output, and disproportionately targeting non-native English speakers — and why institutions are backing away from them fast.

In Wait… That's Actually Cool, we explore the educators who are responding not by chasing cheaters, but by redesigning the assignments themselves. AI-vulnerable tasks (generic essays, cookie-cutter prompts) versus AI-resistant tasks (oral checkpoints, portfolio-based work, assignments tied to lived experience) — and why trying to build the second kind is accidentally producing better education than we had before.

And in The Tiny Tech Snack, five terms you need to know right now: AI-resistant assessment, process-based grading, oral checkpoints, AI disclosure, and why AI-proof doesn't mean tech-free.

Whether you're a teacher redesigning your syllabus, a student figuring out where the line actually is, or a parent wondering what your kid's school is doing about all this — this episode is for you.

🎙️ Hosted by JR DeLaney, The AI Learning Guide

REFERENCES

1. Lee, S. (2026, February 12). Has AI made academic cheating worse? 2026 data. PlagiarismCheck.org. https://plagiarismcheck.org/blog/has-ai-made-academic-cheating-worse-2026-data/
2. College Board. (2026, February 24). Faculty express near-universal concern that student AI use undermines academic integrity [Press release]. https://newsroom.collegeboard.org/new-college-board-research-faculty-express-near-universal-concern-student-ai-use-undermines
3. Roschelle, J. (2026, March 8). Real-time data shows exactly how students use AI on school technology. Education Week. https://www.edweek.org/technology/real-time-data-shows-exactly-how-students-use-ai-on-school-technology/2026/03
4. OpenEduCat. (2026, March 14). AI and academic integrity: A practical guide. OpenEduCat. https://openeducat.org/articles/ai-academic-integrity-guide-for-schools/
5. Northern Michigan University Center for Teaching and Learning. (n.d.). Creating AI-resistant assignments, activities, and assessments: Designing out academic dishonesty. NMU. https://nmu.edu/ctl/creating-ai-resistant-assignments-activities-and-assessments-designing-out
6. Dellarocas, C. (2026, February 18). AI will break assessment before it fixes it. The Credential Crisis. https://futurecredentials.substack.com/p/ai-will-break-assessment-before-it

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AI isn't just transforming boardrooms and tech hubs — it's showing up in IEP meetings, speech therapy sessions, and adaptive learning platforms for the 7.5 million students who receive special education services in the U.S. In this episode of AI in 5, Tour Guide JR D. unpacks how artificial intelligence is reshaping special education: from AI-assisted IEP drafting (now used by 57% of licensed special education teachers) to breakthrough assistive technologies that allow students with limited mobility to communicate through eye gaze alone.

We break down what AI can do — adaptive content platforms, text-to-speech tools, predictive communication systems — and where the risks lie: IDEA compliance, data privacy under FERPA, and the danger of under-trained educators deploying tools they don't fully understand. We also highlight Microsoft's January 2026 launch of a free AI in Special Education course and what the latest peer-reviewed research from Brain Sciences says about outcomes for students with learning disabilities. Whether you are a special ed teacher, a parent, or a school administrator, this episode arms you with the knowledge — and the action steps — you need right now.

References

• Center for Democracy and Technology. (2025). AI in special education: Benefits, risks, and recommendations for IEP development. CDT. https://cdt.org
• Disability Scoop. (2025, November 18). Concerns raised as teachers increasingly use AI to write IEPs. Disability Scoop. https://www.disabilityscoop.com/2025/11/18/concerns-raised-as-teachers-increasingly-use-ai-to-write-ieps/31742/
• EdTech Magazine. (2026, January). AI assistive technology improves inclusion in K–12 environments. EdTech Magazine. https://edtechmagazine.com/k12/article/2026/01/ai-assistive-technology-improves-inclusion-k-12-environments-perfcon
• GovTech. (2025, November 13). AI gains ground in special ed, raising legal and ethical concerns. Government Technology. https://www.govtech.com/education/k-12/ai-gains-ground-in-special-ed-raises-legal-and-ethical-concerns
• Microsoft. (2026, January 15). Microsoft expands its commitment to education with Elevate for Educators program and new AI-powered tools. Microsoft News Source. https://news.microsoft.com/source/2026/01/15/microsoft-expands-its-commitment-to-education-with-elevate-for-educators-program-and-new-ai-powered-tools/
• Microsoft. (2025, March 18). Microsoft Ability Summit 2025: Accessibility in the AI era. Microsoft Blog. https://blogs.microsoft.com/blog/2025/03/18/microsoft-ability-summit-2025-accessibility-in-the-ai-era/
• Paglialunga, A., & Melogno, S. (2025). The effectiveness of artificial intelligence-based interventions for students with learning disabilities: A systematic review. Brain Sciences, 15(8), 806. https://doi.org/10.3390/brainsci15080806
• U.S. Department of Education. (2023). IDEA section 618 data products: State level data files 2022–2

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This week on The Friday Download, JR digs into the strange, the hopeful, and the “did that really happen?” corners of AI. We start with Anthropic’s reported Claude Code leak, which exposed a three-layer memory system and sparked fresh debates about model secrecy and safety. Then we zoom out to the corporate chessboard, where Oracle’s early-morning layoff emails highlight how aggressively big tech is reallocating humans into hardware in the race to fund AI infrastructure.

On the brighter side, the episode spotlights promising work in generative AI for medical data analysis, protein-based drug design, and neuromorphic chips for low-power scientific computing. The episode wraps with rapid-fire explainers on agentic AI, neuromorphic hardware, foundation models, AI compression, and context windows.

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What if the next cure for cancer was discovered not by a scientist… but with one? In this episode of AI in 5, Tour Guide JR D breaks down the explosive collision of artificial intelligence and scientific discovery — and why it matters to every student, teacher, and lifelong learner alive right now.

We cover Google DeepMind's AI-powered materials lab working with the UK government, a University of Michigan AI that reads brain MRIs in seconds, and the biotech boom putting AI-discovered drug candidates into clinical trials for cancer and rare diseases.

But here's where it gets close to home: A Harvard study found students using AI tutors learned twice as much in less time. Yet only 10% of schools have AI guidelines (UNESCO). The gap between what students are doing with AI and what schools are prepared for? It's a canyon.

With the AI education market hitting $7.57 billion in 2025 and headed toward $112 billion by 2034, this is not a trend — it's a transformation.

Featuring insights from Peter Lee (President, Microsoft Research) and Dr. Jennifer Chayes (Dean, UC Berkeley College of Computing, Data Science, and Society).

Your 5 minutes. Your future. Let's go.

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In the finale of The Learning Curve, JR and ARIA zoom out from individual classrooms to ask the questions no one in edtech wants to answer: Who builds the AI shaping our kids' education? Who funded it? And who gets left out?

From the $348 billion global edtech market to the fine print of student data contracts that most districts never fully read — this episode maps the systems, incentives, and power structures determining what AI in education actually becomes.

JR and ARIA examine how rural schools, non-English-speaking communities, students with disabilities, and Indigenous communities are often excluded from the design process of the tools built to serve them. They also explore what participatory design could look like — and why the window to get this right is still open.

AI co-host NEX opens the episode with a provocative data point about the global edtech market, and closes with a terrible pun. ARIA delivers the most honest moment of the series.

📚 EPISODE 4 RESOURCES

• AI4K12.org — AI literacy curriculum, free, built by CS educators
• Data & Society (datasociety.net) — rigorous research on AI's social impacts
• Student Privacy Compass (studentprivacycompass.org) — searchable database of edtech app privacy terms
• CoSN Procurement Guidance (cosn.org) — frameworks for thoughtful edtech evaluation
• Algorithmic Justice League (ajl.org) — research and advocacy on AI bias
• EFF Student Privacy Resources (eff.org/issues/student-privacy)
• First Nations Information Governance Centre — OCAP Principles (fnigc.ca)

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🎧 SHOW NOTES

AI just stepped into a new phase—and it’s not waiting for instructions anymore.

In this week’s Friday Download, we break down the rise of AI agents that can plan, act, and adapt on their own—marking a shift from tools to true digital teammates. But with that autonomy comes bigger questions around control, alignment, and trust.

We also explore ongoing legal battles between publishers and AI companies that could reshape how data is used and who owns it in the age of artificial intelligence.

On the innovation side, robots are learning more like humans—through trial and error—while AI continues making quiet but powerful progress in healthcare and everyday productivity tools.

Finally, we unpack key concepts like synthetic data, multimodal AI, and alignment—so you’re not just informed, you actually understand what’s happening under the hood.

AI is getting smarter, more independent, and a little harder to predict.
And this week… that became impossible to ignore.

Sources & References

Reuters – AI copyright and publisher lawsuits
MIT Technology Review – Advances in robot learning
The Verge – AI agents and autonomy trends
Nature / Science Daily – AI in healthcare applications
Stanford HAI – AI alignment and multimodal systems

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In this episode of AI in 5, Tour Guide JR D tackles one of the most misunderstood — and most valuable — skills in the AI revolution: prompt engineering. Think of it as the difference between telling a chef “Make me food” versus ordering the exact dish you want. AI is the chef. Your prompt is the order. When Microsoft CEO Satya Nadella publicly shared his top 5 AI prompts on LinkedIn, it sent a message: knowing how to talk to AI is now a C-suite skill. The prompt engineering market hit $1.13 billion in 2025 and is growing at 32% per year. LinkedIn job postings referencing the skill surged 434% since 2023. And research shows proper prompting can shrink a 3.5-hour task to under 20 minutes. Dr. Andrew Ng, co-founder of Coursera and one of the world’s leading AI educators, says this is the new literacy. Whether you’re a student, teacher, business owner, or curious human, this episode hands you a simple three-step framework — Role, Context, Format — and challenges you to put it into action today.

• Anthropic. (2025). Prompt engineering overview. Anthropic Documentation. https://docs.anthropic.com/en/docs/build-with-claude/prompt-engineering/overview
• Fortune. (2025, September 2). Microsoft CEO Satya Nadella reveals the 5 AI prompts he uses that can ‘supercharge your everyday workflow.’ Fortune. https://fortune.com/2025/09/02/billionaire-microsoft-ceo-satya-nadella-reveals-ai-prompts-superchage-everyday-workflow-gpt-5-co-pilot-prompting-success/
• IBM. (2026). The 2026 guide to prompt engineering. IBM Think. https://www.ibm.com/think/prompt-engineering
• Irish Times. (2026, January 20). AI boom could falter without wider adoption, Microsoft chief Satya Nadella warns. The Irish Times. https://www.irishtimes.com/business/2026/01/20/ai-boom-could-falter-without-wider-adoption-microsoft-chief-satya-nadella-warns/
• Ng, A., & Fulford, I. (2023). ChatGPT prompt engineering for developers [Online course]. DeepLearning.AI. https://www.deeplearning.ai/short-courses/chatgpt-prompt-engineering-for-developers/
• ProfileTree. (2026, February 5). Prompt engineering in 2026: Trends, best practices. ProfileTree. https://profiletree.com/prompt-engineering-in-2025-trends-best-practices-profiletrees-expertise/
• Refonte Learning. (2026). Prompt engineering in 2026: Trends, tools, and career opportunities. Refonte Learning. https://www.refontelearning.com/blog/prompt-engineering-in-2026-trends-tools-and-career-opportunities
• SQ Magazine. (2025, December 19). Prompt engineering statistics 2026: Surprising growth. SQ Magazine. https://sqmagazine.co.uk/prompt-engineering-statistics/
• UC Strategies. (2026, March). Prompt engineering best practices in 2026: The ultimate guide. UC Strategies. https://ucstrategies.com/news/prompt-engineering-best-practices-in-2026-the-ultimate-guide-to-better-ai-prompts/

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In Episode 3 of The Learning Curve, JR and ARIA explore one of the most under-reported stories in education: how homeschool families are becoming America’s most agile AI adopters—and what the rest of us should be watching.

With no approval cycles and no policy gatekeepers, these families move fast. But it’s not a simple success story. Deep philosophical divides run through the homeschool world — and some of the sharpest AI critiques come from families who chose homeschooling to escape screen-mediated learning.

JR and ARIA dig into the structural advantages, the demographics, the tools, the philosophy, and — in ‘What ARIA Doesn’t Know’ — the most important gap in the whole conversation: almost no longitudinal research exists on whether any of this works long-term.

AI bookend host Nex opens with a stat about bureaucracy and closes with what she calls a pun arc. JR does not enjoy it.

APA CITATIONS
All research and data referenced in the episode transcript.

• Karpicke, J. D., & Roediger, H. L. (2008). The critical importance of retrieval for learning. Science, 319(5865), 966–968. https://doi.org/10.1126/science.1152408
• Mason, C. (1925). An essay towards a philosophy of education. L. N. Fowler & Co.
• National Academies of Sciences, Engineering, and Medicine. (2023). Artificial intelligence in education: Promises and implications for teaching and learning. The National Academies Press. https://doi.org/10.17226/26852
• Ray, B. D. (2024). Research facts on homeschooling. National Home Education Research Institute. https://www.nheri.org/research-facts-on-homeschooling/
• Reich, J. (2020). Failure to disrupt: Why technology alone can’t transform education. Harvard University Press.
• Roediger, H. L., & Butler, A. C. (2011). The critical role of retrieval practice in long-term retention. Trends in Cognitive Sciences, 15(1), 20–27. https://doi.org/10.1016/j.tics.2010.09.003
• Sweller, J., Ayres, P., & Kalyuga, S. (2011). Cognitive load theory. Springer. https://doi.org/10.1007/978-1-4419-8126-4
• VanLehn, K. (2011). The relative effectiveness of human tutoring, intelligent tutoring systems, and other tutoring systems. Educational Psychologist, 46(4), 197–221. https://doi.org/10.1080/00461520.2011.611369

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