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Understanding AB 2876: AI Literacy in California Schools

June 8, 2026 by incredibrain Leave a Comment

If you work in a California school, district office, or college teaching-and-learning center, you’ve probably already heard the name: AB 2876. Signed into law by Governor Gavin Newsom and authored by Assemblymember Marc Berman (D–Menlo Park), this bill marks the first time California has formally written artificial intelligence literacy into the fabric of K–12 curriculum. For those of us working at the intersection of AI and education, it’s not just a policy update — it’s confirmation that the questions we’ve been asking in classrooms and faculty meetings for the last few years are now the questions the state is asking too.

What AB 2876 actually does

At its core, AB 2876 directs California’s Instructional Quality Commission to incorporate AI literacy into the mathematics, science, and history–social science curriculum frameworks and instructional materials the next time those frameworks are revised. It also adds media literacy to English language arts/English language development, science, mathematics, and history–social science instructional materials on the same revision cycle.

The law defines AI literacy in refreshingly practical terms — not as a checklist of tools to master, but as:

“The knowledge, skills, and attitudes associated with how artificial intelligence works, including its principles, concepts, and applications, as well as how to use artificial intelligence, including its limitations, implications, and ethical considerations.”

In other words, the law isn’t asking schools to teach students how to prompt a chatbot. It’s asking them to build the kind of judgment that lets a student understand what AI is doing, where it falls short, and what responsibilities come with using it — in the classroom and far beyond it.

Why this matters right now

AB 2876 doesn’t exist in a vacuum. It lands at a moment when:

Generative AI has already reshaped how students draft, research, and turn in work — often faster than school policies have been able to keep pace.
The California Department of Education’s statewide AI Working Group is actively shaping model guidance that districts will be expected to follow.
College and university teaching-and-learning centers are fielding the same questions from faculty that K–12 instructional leaders are fielding from teachers: What do we actually do about this?

For superintendents, curriculum directors, instructional coaches, and faculty developers, AB 2876 turns “should we have an AI policy?” into “we are now expected to.” That’s a real shift — and it’s one that rewards schools and systems that get ahead of it rather than scrambling to react once the frameworks are formally revised.

Where IncrediBrain comes in

This is exactly the work we do. IncrediBrain isn’t a consultancy parachuting in with generic slide decks about “the future of AI.” We are faculty practitioners who work inside California schools and universities. We see the students K–12 is preparing. We see where generative AI is genuinely helping learning — and where it’s quietly replacing the thinking it’s supposed to support.

AB 2876’s definition of AI literacy — knowledge, skills, and attitudes; principles and ethics; capability and limitation — maps almost exactly onto the framework we’ve built our work around:

Constructivist learning — helping students build understanding through interaction, revision, and meaning-making, not just output.
Executive function support — using AI thoughtfully to help students externalize thinking and manage cognitive load, rather than outsource it.
Process-based assessment — shifting the core question from “did the student produce the work?” to “how did the student think, choose, revise, and understand?”

That last shift — from product to process — is, in our view, the real heart of what AB 2876 is asking California schools to wrestle with. It’s not a compliance checkbox. It’s a genuine rethinking of how we know a student has learned something in a world where the artifact alone can no longer prove it.

Join the conversation: free AI Literacy webinar series for educators

If your school, district, or campus is trying to figure out what AB 2876 means in practice — not just on paper — we’d love to have you join our free three-session webinar series, AI Literacy for Educators, designed for both K–12 and higher education audiences.

July 8, 15, and 22, 2026 • 10:00 AM PT / 1:00 PM ET • Live online • Free

Session 1 — July 8: The Artifact Is Failing — AI, assessment, and the future of evidence
Session 2 — July 15: Executive Function in the Age of AI — the hidden curriculum education assumed students already had
Session 3 — July 22: Ethics Before Tools — institutional readiness, equity, and human judgment

These sessions are built around real conversations with educators in the room, frameworks you can put to use the following Monday morning, and ethical, human-centered perspectives on AI that you won’t find in a typical product demo.

👉 Register for the free webinar series

AB 2876 has set a new expectation for California schools. The good news: you don’t have to figure out how to meet it alone — and you don’t have to wait for the official frameworks to be revised to start building the practices, policies, and judgment your students need today.

Want to talk through what AB 2876 means for your specific school, district, or campus? Schedule a consultation with IncrediBrain.

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Rehumanizing AI: Inside American River College’s First AI Symposium

May 15, 2026 by Dyanne Marte Leave a Comment

On April 24, 2026, American River College hosted its first AI Symposium, a half-day event that brought together educators, students, and industry partners to talk honestly about what artificial intelligence means for teaching and learning.

From 8:00 a.m. to 1:30 p.m., Raef Hall, the STEM Center, and the CTE Building were full of conversations about assignments, accessibility, policy, creativity, and the future of work. The goal was simple but ambitious: move beyond AI hype and focus on what actually helps students learn and succeed.

Incredibrain at the Center

The symposium was designed and led by Dr. Dyanne Marte, American River College’s AI Faculty Fellow and one of the founders of Incredibrain, together with Professor Michael Angelone, CCC Vision 2030 Changemaker, ARC faculty member, and Incredibrain co-founder.As co-founders, they shaped the day to be hands-on, cross-disciplinary, and grounded in real classroom practice. In the opening session, Dr. Marte welcomed attendees alongside ARC President Dr. Lisa Cardoza, naming what many educators are feeling: AI is already in students’ lives, and colleges need safe spaces to explore, experiment, and build thoughtful guardrails rather than ignore the technology or react out of fear.

The symposium brought Incredibrain’s mission to life: helping institutions move from confusion to confident, responsible AI use.

A Keynote About People, Not Just Tools

The morning keynote, “Beyond the Hype: Rehumanizing Education in the Age of Artificial Intelligence,” was delivered by Chesa Caparas, AI Faculty Fellow at De Anza College and professor of English and Ethnic Studies.

Instead of giving a tour of tools, she focused on people and on how colleges can keep human judgment at the center while AI systems evolve quickly. Her message set the tone for the rest of the day: AI should support learning, equity, and community, not replace them.

Sessions for Every Comfort Level

After the keynote, participants chose from three levels of sessions: L1 for those new to AI, L2 for classroom and workflow applications, and L3 for policy, governance, and institutional strategy.

In the first breakout block, sessions explored assessment redesign, AI-powered enrollment and engagement, Microsoft Copilot and Gemini as supports for student success, and Vibe Code Academy, a student-created platform that makes coding more approachable through short interactive lessons.

This structure gave everyone a way in, whether they were just curious or already experimenting with AI in their classrooms and offices.

Spotlight: Authorship from Superhuman

One of the most talked-about tools of the day was Authorship from Superhuman (formerly Grammarly for Education). Partnership Specialist Marc Santos led multiple sessions on “Authorship in the Writing Process,” showing how the tool reveals how a document is created over time, including what a student writes directly and where AI-assisted text appears.

What resonated with faculty was the shift in mindset: the goal was not simply to catch AI use. Instead, Authorship was positioned as a way to create more transparent, informed conversations about writing, revision, and academic integrity.

Michael Angelone’s Anchor Sessions

Professor Michael Angelone played a major leadership role throughout the symposium. He presented “When the Artifact Fails: Rebuilding Trust in Assessment in the Age of AI,” moderated “AI, Authorship, and the Future of Publication,” and moderated “From Guidelines to Guardrails: AI Policy and Legislation in California Community Colleges.”

Together, these sessions pushed attendees to consider what counts as evidence of learning, how concepts like authorship and plagiarism are shifting, and what guardrails colleges need as AI becomes part of daily academic life.

Centering Student Voice and Real-World Practice

The symposium made sure students were not just talked about, but heard. A student panel, “AI in the Classroom and Beyond,” gave students space to share how they actually use AI in coursework, where the tools help, and where they create confusion or stress.

Other sessions connected campus learning to the world beyond ARC. Presenters from Intel, Equinix, College Track, AweFull Learning, Gravyty, Nectir, and other partners showed how AI already shapes business operations, infrastructure, student support services, nonprofits, and media.

Community, Food, and a Sense of Place

Community was built into the design of the day. Breakfast and lunch in the Community Rooms atrium gave people time to debrief sessions, trade ideas, and build new cross-campus relationships.

The symposium also reflected American River College’s hands-on learning culture. Student-run spaces like the Bakery and the Oak Café highlight how ARC pairs classroom learning with real-world hospitality and culinary experience.

From Ideas to Guardrails

In the final breakout block, attention turned to policy and long-term direction. The “From Guidelines to Guardrails” panel connected proposed Los Rios AI guidelines and human-in-the-loop practices with statewide frameworks like Vision 2030 and emerging AI legislation shaping how community colleges use AI in teaching, governance, and student services.

Other sessions explored authentic assessment, Universal Design for Learning, accessibility, and course design that keeps human creativity and productive struggle at the center.

Why This Symposium Matters

What made American River College’s AI Symposium stand out was not just the number of sessions or the variety of speakers, but the way it brought difficult questions into one shared space. Faculty, students, technologists, lawyers, policy experts, and community partners sat at the same tables, wrestling with how AI is changing education and what colleges should do next.

For Incredibrain, this symposium was more than a single event. Under the leadership of co-founders Dr. Dyanne Marte and Professor Michael Angelone, it demonstrated what responsible AI adoption can look like when it starts from the classroom and moves outward: thoughtful, collaborative, equity-minded, and firmly focused on rehumanizing education in an AI-shaped world.

What Students Actually Think about AI in College and what it Means for your Institution

May 14, 2026 by incredibrain Leave a Comment

A new Inside Higher Ed Student Voice survey of more than 1,000 students across 166 two- and four-year institutions cuts through a lot of the noise about generative AI in higher education. The headline finding? AI is changing college, but it isn’t killing it. For institutions trying to chart a thoughtful path forward, the data offers a clearer picture of what students are actually doing with AI — and what they want from their schools.

Here are the takeaways every academic leader, faculty developer, and instructional designer should be sitting with.

1. Students are using AI — but mostly to support learning, not outsource it

Eighty-five percent of students reported using generative AI for coursework in the past year. But the dominant use cases look a lot more like productive study habits than wholesale cheating: brainstorming ideas (55 percent), asking AI questions like a tutor (50 percent), and studying for exams (46 percent). Only 19 percent reported using AI to write full essays.

The implication for institutions: treating AI use as a binary “cheating vs. not cheating” issue misses the texture of how students are actually integrating these tools. The harder, more useful work is helping students discern between uses that build skill and uses that erode it.

2. Grade pressure — not confusion about policy — is the main driver of misuse

When students were asked why their peers misuse AI, the top answer was pressure to get good grades (37 percent), followed by time pressure (27 percent) and indifference to academic integrity policies (26 percent). Only 6 percent blamed unclear policies.

This reframes the conversation. The problem isn’t primarily that students don’t know the rules — it’s that the incentive structure around grades is fueling shortcut-taking. Institutions that focus only on tightening policy without addressing assessment design and grade-driven anxiety are treating a symptom, not the cause.

3. Students want action — but not surveillance

Ninety-seven percent of students believe institutions should respond to AI-era integrity challenges. But the popular interventions aren’t the ones often debated in faculty senates. AI-detection software (21 percent) and tech restrictions in classrooms (18 percent) ranked low. What students actually want:

Education on ethical AI use (53 percent)
Clearer, standardized policies on when and how AI can be used
Flexibility to use AI with transparency

The lesson for institutions: a punitive posture is misaligned with what your students are asking for. Educational, transparency-based frameworks have a far stronger mandate.

4. Students are skeptical of faculty AI use, too

Only 29 percent of students felt positively about faculty using AI to create assignments or do other teaching work, while 39 percent felt negatively. The concerns students raise about faculty use — quality, overreliance, opacity — mirror the concerns faculty raise about student use. Any institutional AI strategy that asks more of students than it asks of instructors will struggle to land.

5. The critical thinking question is real — and nuanced

Among students who use AI for coursework, 55 percent said it has had mixed effects on their learning and critical thinking. Twenty-seven percent said the effect is positive; 7 percent said it’s negative. Notably, students who use AI to write essays were nearly twice as likely as those who use it to study to report negative effects on their thinking.

This is the data point worth holding onto. AI’s impact on cognition isn’t uniform — it depends heavily on how it’s used. That’s a design problem institutions can address.

6. Students want AI literacy as career preparation

Looking beyond the classroom, students said they want institutions to offer (but not require) training in professional and ethical AI use, alongside clearer guidance and open forums to discuss risks and benefits. Only 16 percent thought AI preparation should be left to individual professors, and just 5 percent thought colleges should do nothing. The expectation of an institutional response is overwhelming.

7. AI hasn’t devalued college — and for some, it’s raised the value

Thirty-five percent of students said AI hasn’t changed how they value their degree, and 23 percent said college is more valuable now. Only 18 percent said they question its value more than before. The “AI will kill college” narrative isn’t reflected in how students themselves think about their education.

What this means for institutional strategy

The survey points toward a clear playbook for institutions ready to lead rather than react:

Move from policing to pedagogy. Invest in AI literacy curricula and assignment-by-assignment guidance rather than detection tools that students distrust and that often produce false positives.

Redesign assessment. If grade pressure is driving misuse, then scaffolded assignments, alternative assessments, and a refocus on learning over point-getting do more for integrity than any policy ever will.

Build institution-wide frameworks. Students want consistency, not contradictory class-by-class rules. Frameworks like the University of Kentucky’s Student AI Use Scale or Mark Watkins’ VALUES framework offer starting points worth studying.

Prepare students for the workforce. Adult learners especially want training on how AI shows up in professional settings. This is a place where higher ed can lead.

There is, as one survey reviewer put it, “no instruction manual” for this moment. But the students themselves are telling us — clearly — what they need. The institutions willing to listen will be the ones that turn this transition into an opportunity instead of a crisis.

Based on “How AI Is Changing — Not ‘Killing’ — College,” by Colleen Flaherty, Inside Higher Ed, August 29, 2025. Read the original article.