AI Innovations Unleashed

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
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/
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
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
OpenEduCat. (2026, March 14). AI and academic integrity: A practical guide. OpenEduCat. https://openeducat.org/articles/ai-academic-integrity-guide-for-schools/
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
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
Send us Fan Mail
Support the show

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
Send us Fan Mail
Support the show

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.
Send us Fan Mail
Support the show

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.
Send us Fan Mail
Support the show

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) 
Send us Fan Mail
Support the show