# Matthew Karabinos

Matthew Karabinos works on AI literacy and the use of AI in education. Their posts discuss support for K–12 schools and educators, and feature conversations on education podcasts including The Curve Ahead and AI Real Talk. They identify their work with Appalachia Intermediate Unit 08.

- Profile: https://b2binfluencer.marketing/creators/matthew-karabinos/
- LinkedIn: https://www.linkedin.com/in/matthew-karabinos-mat
- LinkedIn followers: 5,938
- Topics: artificial-intelligence, ai-governance, ai-in-education
- Based on 13 dated posts, latest 2026-10-08

## Summary

Useful for K-12 AI literacy guidance, policy support, and educator conversations about balanced AI adoption.

- Best for: K-12 schools, districts, or edtech brands running AI literacy and teacher professional development campaigns.
- Not for: Enterprise or defense-adjacent AI vendor launches needing technical benchmarks, procurement evaluation, or measurable pipeline.
- Check first: Confirm commercial terms, recent reach, engagement, click figures, and audience roles for K-12 AI literacy work.

### Takeaways

- They tested six chatbots on teacher AI concepts and discussed what was missing.
- They examined K-8 computer science appearing in coding clubs and robotics without foundations.
- The Curve Ahead episode discusses LAUSD screen time limits and AI inevitability.

## Main ideas

- **AI belongs in schools through balance, not fear or full adoption**: Karabinos argues that the contentious question is not whether AI will arrive in schools, but how schools choose to use it. Drawing on earlier education-technology waves and social media, they show how adoption without purpose creates predictable problems. Intentional-design thinking supports deliberate limits and clear use cases. The position is a decision framework—screen time, purpose, implementation lessons—rather than a pro- or anti-AI stance.
- **AI governance is an access-and-oversight question, not just a safety slogan**: Karabinos argues that as AI systems become foundational infrastructure, powerful institutions will test companies' public safety commitments by requesting exceptions. Governments want reliability, auditability, and security assurances, while AI companies want to protect model integrity, safety constraints, and governance promises; those incentives do not always align. They frame the issue as a question of who gets access, under what conditions, and with what oversight.
- **Curiosity and admitting uncertainty are teaching strengths in an AI-shaped classroom**: Karabinos argues that teachers should not feel they must be the expert in the room, because AI changes what students can look up and what teachers are expected to know on demand. Modeling questions, uncertainty, and learning in public builds student agency better than performing authority. Saying “I don't know” is a powerful teaching move, not a failure.
- **AI literacy starts with foundations and concepts, not apps**: Karabinos argues that schools are often not ready for AI literacy because computer science exists in name only, scattered across coding clubs and robotics units without a real foundation. Tools change faster than the concepts teachers need to explain, so foundational knowledge about how large language models and AI systems work should come before product training. This is a curriculum-coherence argument, not a claim about any single tool.
- **Build understanding through public conversations with educators**: Karabinos uses podcast interviews to surface practitioner perspectives rather than broadcast answers from a single expert position. AI in education is unsettled enough that listening to teachers, administrators, and specialists across K–12, higher education, and corporate learning can produce better questions. The format also lets them test and revise their own stance in public.

## Work to read

- [Mark DiMauro on AI in the classroom](https://www.linkedin.com/posts/matthew-karabinos-mat_aiineducation-edtech-generativeai-activity-7492646036520435713-CmHh)
- [The Curve Ahead: LAUSD screen time and AI inevitability](https://www.linkedin.com/posts/matthew-karabinos-mat_aiineducation-ailiteracy-curveahead-activity-7481012257771159552-1aF0)
- [Testing six chatbots on teacher AI concepts](https://www.linkedin.com/posts/matthew-karabinos-mat_ailiteracy-aiknowledge-foundationalknowledge-activity-7485692776869822464-RCmW)
- [Stewart Brown on K-8 AI literacy and computer science gaps](https://www.linkedin.com/posts/matthew-karabinos-mat_aiineducation-edtech-computerscience-activity-7498073401668870144-WdSa)
- [AI Real Talk: becoming a cautious advocate](https://www.linkedin.com/posts/matthew-karabinos-mat_ai-real-talk-the-curiosity-connection-activity-7479608892063232000-LtI1)
- [Anthropic, the Pentagon, and the AI governance line](https://www.linkedin.com/posts/matthew-karabinos-mat_aigovernance-ai-activity-7429502422571720704-M8sL)

## Brand relationships

- **Appalachia Intermediate Unit 08** (disclosed_partnership)
- **The Curve Ahead** (disclosed_partnership)
- **AI Real Talk: The Curiosity Connection** (disclosed_partnership)

## Partnerships

Matthew Karabinos's posts span February to August 2026 and feature podcast episodes, educator interviews, and conference-style commentary—not paid formats, rates, media kits, or sponsor disclosures. They promote episodes of The Curve Ahead and AI Real Talk, credit guests and colleagues, and offer AI guidance, policy support, and professional development to schools and districts in the IU8 region and central Pennsylvania through Appalachia Intermediate Unit 08. That is a service and professional-development offer connected to the employer role, not a creator sponsorship package described in the posts. A brand planning a K-12 AI literacy workshop series should ask Karabinos directly whether they offer sponsorships and, if so, what formats, pricing, deliverables, and inquiry routes are available.

## Alternatives

- Dr. Jorge Valenzuela: Choose Valenzuela when the district's problem is assessment design rather than helping teachers understand how AI works. The posts argue that AI has made instructional design more important, and that project-based learning and strong assessment structures make student thinking visible: students justify decisions, explain reasoning, apply knowledge to authentic contexts, and reflect on process. This lets educators evaluate how AI was used rather than simply whether it was. The offer includes a single-point rubric a district can hand to teachers, and the questions address school and district leaders assessing the balance between AI literacy and instructional integrity. For a cohort whose deliverable is a rubric or a redesigned assessment, this is the closer fit.
- Mary Harper: Choose Harper when the buyer's audience is educator-preparation programs, higher-education faculty, accreditation teams, or early-childhood workforce leaders rather than K-12 classroom teachers. The posts centre on a design framework from the Learning Policy Institute that asks whether preparation systems are designed around what is known about learning and development. Its five principles cover coherence, clinical grounding, developmental science, equity, and modeling. The second post announces a Texas Workforce Commission grant to the Children's Learning Institute funding CDA credentials, registered apprenticeships, associate degrees, and bachelor's degrees. It targets Texas early childhood and EC-6, special education, and bilingual preparation. For a workshop series whose buyers are program deans or workforce-pipeline administrators, this writing is aimed directly at that room.
- Dr Michael Harvey: Choose Harvey when the workshop's centre of gravity is agency and control rather than tool mechanics. The posts take a position on who decides how AI enters learning: the change from Gems to Skills raises the question of whether teachers and students keep meaningful agency. They argue that teachers need to decide why, when, and how AI supports learning, while students need to decide when to seek help, question an answer, or reject it. The point is made concretely, with examples such as a teacher deliberately withholding a scaffold or requiring a prediction before an explanation. The Google Innovator posts show project work developed across three days with coaches and peer educators. For a district drafting rules about where judgement stays with people, these posts supply a sharper argument than a foundations session.

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AI-assisted summary of public posts. Audience demographics are not available. Engagement appears only where we checked recent posts. Method: https://b2binfluencer.marketing/methodology/