Augmented Intelligence Advisory

Kids are outsourcing their minds We’re building the layer that makes them think anyway

Before the research catches up.

Before the regulation lands.

Before a generation loses the habit of thinking for itself.

Students’ access to unlimited AI isn’t a tools problem.
It’s a thinking problem.

California has mandated AI literacy in every K–12 classroom.
30+ states are moving on similar bills.
AI literacy should teach students to think alongside AI, not outsource their thinking to it.

67% of students are already using AI daily with zero guardrails. BestColleges, 2024

The evidence is already in. The intervention is what’s missing.

We read it. We operationalize it.

MIT Media Lab  ·  2025
Weakest neural connectivity.
Students who wrote essays with ChatGPT showed the lowest memory recall of their own work across four months.
Kosmyna et al., “Your Brain on ChatGPT.”
Read the study →
PNAS  ·  2025
17% lower exam scores.
Nearly 1,000 high schoolers used GPT-4 during math practice. When access was removed for the exam, they underperformed peers who never had it.
Bastani et al., “Generative AI without guardrails can harm learning.”
Read the study →
Societies  ·  2025
Lower critical thinking.
Across 666 participants, heavier AI users scored significantly lower on critical thinking, and younger users showed the highest dependence.
Gerlich, “AI Tools in Society.”
Read the study →

In the classroom. In the policy conversation.

Co-build the tools and curriculum that teach AI literacy.

We design alongside the teachers and students who will use this work. Not for them, with them. The tools, prompts, and curriculum we build are tested and refined in the classrooms they are meant to serve.

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Make sure AI policy reflects what works in real classrooms.

We give public testimony, publish in education and policy outlets, and work alongside researchers and policymakers to make sure decisions about student AI use are grounded in evidence from real schools.

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What cognition-first AI actually looks like.

When a student opens any AI tool, the Platform pauses before the answer loads and prompts them to form a position first. Then AI answers. The exchange is scored and logged.

Student View · Sample
chat.openai.com  ·  us history · period 3
Maya’s prompt · draft
“What were the main causes of the Civil War?”
· PROMPT COMPLEXITY SCORE ·
Your prompt is a 2.1 out of 4. Here’s what it’s telling us.
Goal Clarity 3 / 4
Context Scaffolding 1 / 4
Reasoning Demand 2 / 4
Epistemic Posture 2 / 4
You’re asking for a list, not an argument. Before the model answers: which single cause do you think was most decisive, and what evidence would change your mind?
Strengthen my prompt →
Teacher View · Sample
think.aia.education  ·  class dashboard
US History · Grade 9 · Period 3
Prompt Complexity Curve · Fall semester
Weeks 1–14
of 18
Class avg. prompt score
2.8 / 4
up from 1.6 in week 1
Moved from recall to reasoning
68%
of prompts now ask for analysis, not just answers
Prompt Complexity Curve · weekly class average
Longer framing, more specific asks, and more follow-up questions before accepting an answer. Students are iterating on their prompts 2.4× more than in week 1.
7 students broke above a 3.0 this week. Their post–reflection answers diverged meaningfully from what AI returned. Suggested follow–up: share exemplars in Thursday’s mini–lesson.

Teachers build it. Students think with it.

A hands-on teacher fellowship. A student curriculum that builds AI literacy from the inside out. A research pilot that turns every classroom session into evidence.

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To ensure every student learns how to use AI as a thinking partner, not a thinking replacement.

Over 15 years, I’ve sat in nearly every seat in the system
Student Organizer: focused on the intersection of police reform and education inequity Teacher Leadership & Design Coach: invested in educators committed to addressing systemic inequity Senior Education Advisor to a senior elected official: led the office’s engagement on school integration in one of the country’s most segregated districts Google Product Consultant: focused on regulatory developments around AI in schools, and students’ socio-emotional bonds with chatbots

One learning: the system only moves when every seat works toward the same thing. I know how to convene these players, and I know how to move the system.

Protecting students’ ability to think is too dangerous to get wrong. We need every player at the table: it’s time we get to work.

I grew up in Brooklyn, between Flatbush and Marine Park, with my mom working in Midwood and my schools spread across all three neighborhoods. A city that can feel like everything is possible and nothing is simple, often in the same hour.

My parents had learned to navigate the behemoth of NYC public schools. In true Pakistani immigrant tiger parent fashion, they pulled me out of one middle school after two months because they didn’t like how math was being taught, and moved me into a “math lab” at Andries Hudde Junior High School in Midwood.

It was there, in sixth grade, that I learned my brain was both a tool I could trust and a muscle I could strengthen. We worked through thick textbooks on our own, taking unit tests at our own pace and needing at least an 80 to advance. If we got stuck, we had to interrogate the exact point we got lost before asking for help. Our two teachers served as guardrails, keeping us on track but never doing the thinking for us. That pedagogy has a name: mastery learning. It built the foundation for how I think today, a foundation now at risk with widespread student use of AI.

I spent the first decade of my career in the weeds of NYC classrooms, advising elected officials on school integration and zoning issues, watching how students get sorted early, who gets the advocates, and who gets written off. Then I watched that same dynamic collide with technology.

Inside Google, I worked on AI policy, specifically the socio-emotional dependencies kids were forming with chatbots. I saw a surreal disconnect. Google had spent years pushing devices into American schools; the executives driving that push sent their own kids to low-tech schools that kept screens out of the classroom. As AI has arrived, I see the pattern repeating. Publicly, panacea. Privately, use carefully.

The people shipping these tools to other people’s children were shielding their own.

Well-resourced students are now treating AI the way their parents treat an early draft: something to push against, not something to accept. Not because their schools are teaching it. Because their parents model it. They push back on outputs, ask themselves what they think before accepting what ChatGPT/Claude/Gemini returns, and continue to refine the thinking until they arrive at their own point of view. That scaffolding is domestic, not institutional. For a student whose parents don’t have that fluency, the classroom is the only potential equalizer. But teachers are waiting on guidance. So students ask AI. AI answers. And the answer becomes the thought.

This isn’t a technology problem. It’s an equity problem wearing technology’s clothes.

The mission I’ve spent my career on, the battle to ensure every kid builds the capacity to think is now inside every backpack in America. And the kids with the fewest advocates are the most exposed. The teachers I’ve worked with aren’t the problem; they are the last line of defense. What they lack is a way to turn their pedagogical instincts into data that districts and policymakers can act on.

We are watching this movie in real-time with social media: harm first, research a decade later, regulation a generation too late.

But this trajectory is not inevitable. AI systems can be built to prompt students to form hypotheses, make their reasoning visible, and engage before handing them answers. That friction is not inefficiency. It is the defining product decision of this generation.

So that’s what I built. A layer that sits on top of every AI tool a student already uses, slows them down just enough to think, and gives teachers the visibility to guide them. When a student asks ChatGPT/Claude/Gemini to write their thesis, the layer will ask them first to think through what they think the argument should be. It tracks habits over time and tells teachers which students are learning to think alongside AI and which are outsourcing it. It doesn’t replace the teacher. It gives the teacher something to work with.

I built the first version myself, then found the people who shared the conviction. That’s what we’re building at Augmented Intelligence Advisory: the cognitive guardrails so the next generation can still think for themselves.

We will come to see this as the student equity issue of the 21st century.

Work with us to get it right.

Ayisha Irfan
Ayisha
Ayisha Irfan
Founder & CEO, Augmented Intelligence Advisory

Five stages, captured in real time.

THINK teaches students to recognize when AI is augmenting their thinking and when it is replacing it. Built on decision science learning standards, the Platform scores every prompt and surfaces how thinking matures over weeks and months.

T
Think
Structuring Decisions
H
Hypothesize
Probabilistic Thinking
I
Interrogate
Resisting Cognitive Bias
N
Navigate
Valuing Rationality
K
Know
Process Reflection

The framework in action, at the point of use.

When a student opens any AI tool, the Platform pauses before the answer loads and prompts them to form a position first. Then AI answers. The exchange is scored and logged.

Student View · Sample
chat.openai.com  ·  civics · period 5
Jordan’s prompt · revised
“Would expanding the Supreme Court to 13 justices materially shift the ideological balance of the Court over the next 20 years, assuming current nomination patterns hold?”
· PROMPT COMPLEXITY SCORE ·
Your prompt is a 3.5 out of 4. That’s a jump from your first draft.
Goal Clarity 4 / 4
Context Scaffolding 4 / 4
Reasoning Demand 3 / 4
Epistemic Posture 3 / 4
You gave the model a mechanism, a timeframe, and an assumption. Now before you read its answer: which direction do you expect the effect to go, and why? Commit to a prediction so you can compare it to what comes back.
Log my prediction →
Teacher View · Sample
think.aia.education  ·  class dashboard
US History · Grade 11 · Period 2
Prompt Complexity Curve · Spring semester
Week 15
of 18
Source verification rate
82%
of students now name a way to fact-check the AI’s answer
Prediction-vs-output gap
1.3×
students revise their position after comparing to AI
Prompt Complexity Curve · weekly class average
Students are now asking the AI to defend its claim with a specific source 3.1× more often than in week 1, and rejecting answers they can’t verify.
4 students wrote reflections this week that directly contradicted the AI’s output with cited evidence. Suggested follow–up: feature one as a Socratic seminar opener Friday.

Ready to make thinking visible in your district?

We work with district leaders, policymakers, and school systems to stand up the platform, train teachers, and turn the evidence into action.

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Every day, leaders are setting policies, teachers are designing assignments, and students are outsourcing their thinking. These three decisions don’t happen in isolation. We work with schools across the full ecosystem: diagnose, onboard, equip, co-design, implement.

The School-Based AI Audit

Most school leaders are making AI policy decisions without data on what’s actually happening in their classrooms. We start by giving them that data.

We start with anonymous student and teacher surveys mapping current AI use and concerns about cognitive impact, alongside interviews with school leadership. We learn more about how students and teachers are actually using AI, and where the cognitive risk is concentrated. From there, we work with leadership to align on what the school needs and how the fellowship and curriculum can meet it.

The THINK Fellowship for Educators

A partnership where teachers become designers of AI literacy, testing what works in their classrooms and building evidence of real behavior change.

Hands-On Intensive Launch

Teachers build their own AI fluency grounded in cognitive science, then move into a co-design sprint: drafting classroom interventions, testing them with real students, and iterating based on what actually moves behavior change.

Ongoing Community of Practice

Office hours, peer-to-peer problem solving, surveys that measure what’s actually changing in classrooms, and a culminating gathering where teachers present classroom data, co-design the next version, and earn their Certified THINK Facilitator credential.

The THINK Curriculum for Students

Students design their own AI practice and measure whether it’s making them think more.

Students start with the research showing AI is making them think less, then learn the THINK Framework: think, hypothesize, interrogate, navigate, know. They practice with real AI, test their knowledge, remove the scaffolds, and build the practice of using AI as a thinking tool, not a replacement tool. Our program runs alongside their AI use, surfacing the evidence: are they asking better questions, fact-checking more, thinking more?

By the end

You have evidence of what changed across leaders, teachers, and students: and a school positioned to keep building.

Interested in partnering?

We work with districts, school networks, and education organizations to bring these programs to classrooms.

Get in Touch →

AIA partners with K–12 schools to protect students’ ability to think alongside AI. Our work happens at three layers: a school-based audit, a teacher fellowship, and a student curriculum.

We also show up in the public conversation through testimony, op-eds, and partnerships with researchers and policymakers working on student AI use.

Ayisha Irfan
Ayisha Irfan
Founder & CEO

Ayisha Irfan is the founder of Augmented Intelligence Advisory. She brings 15+ years of experience across every layer of the education ecosystem, and in tech.

Most recently, she spent the last several years inside Google advising product and engineering teams on Search’s data governance and generative AI features. This is where her education policy brain collided with the realities of how AI was being shipped to students, and this work led directly to the formation of AIA.

Prior to Google, at Airbnb, Ayisha led North America local policy and partnerships. Her work included Airbnb’s public commitment to provide accommodations for 20,000 Afghan newcomers and the national public-private partnerships that housed first responders and survivors of domestic violence and human trafficking during COVID-19. This work shaped her understanding of how tech can be used as a tool for public good.

Prior to that, Ayisha spent a decade in NYC government and policy spaces, focused on: leading grassroots organizing with students, leading leadership development work with current and former teachers, and advising elected officials on educational equity issues.

She holds a master’s in Policy and Applied Statistics from NYU and a bachelor’s in Biology from Brooklyn College.

Sahil Shah
Sahil Shah
Technologist in Residence

Sahil Shah is a software engineer, and the Technologist in Residence at Augmented Intelligence Advisory. His work spans more than a decade of building and scaling systems across industries, including fraud detection, payments, search, and business analytics. He focuses on solving ambiguous problems, working across stakeholders, and delivering solutions that balance short-term iteration with long-term sustainability.

Sahil has held engineering roles at Meta Platforms, Workday, and Airbnb. At Airbnb.org, he was a technical lead on the org’s commitment to provide emergency housing to 100,000+ people displaced by disasters and conflict. This work reinforced his interest in applying technology to real-world needs.

He currently works as a software engineer at The New York Times, focusing on AI, data engineering, and digital archiving.

Sahil holds a degree in Computer Engineering from University of California San Diego.

Yissely Ortiz
Yissely Ortiz
Chief Programs Officer

Yissely Ortiz is Chief Programs Officer at Augmented Intelligence Advisory, where she leads program strategy, and designs educator and student-facing learning experiences at the intersection of AI, critical thinking, and educational equity.

She brings more than 15 years of cross-sector experience in leadership development, inclusive program design, and systems change. Yissely’s career spans private sector, nonprofit, and community-based work. Her work across the public and private sectors has enabled her to move fluidly between strategy and implementation, ensuring that programs are designed with the same care they are delivered.

At AIA, Yissely leads instructional design and facilitation across pilot sites, partnering with teachers, students, and community organizations to ensure that AI literacy work is grounded in everyday classrooms and real needs. She is driven by a conviction that the communities too often left out of new technology should be the first to shape how it is used.

Let’s talk about what comes next.

AI companies building for classrooms. Ed-tech platforms designing their next product. State agencies implementing new mandates. Foundations backing what comes after the hype. Districts and educators ready to stop watching and start building.

If that’s you, let’s talk.

Get in Touch →

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