Advocacy

Two Different AI-Literacy Stories Are Colliding This Fall — Boston’s Proficiency Push and Massachusetts’ Proposed Recommendations, and What It Means If You’re Not in Public School

This fall, two Massachusetts stories are getting mashed into one headline: AI is now required. They are not the same thing. One is a Boston Public Schools proficiency initiative, planned…

This fall, two Massachusetts stories are getting mashed into one headline: AI is now required. They are not the same thing. One is a Boston Public Schools proficiency initiative, planned for participating high schools as students return on September 8. The other is a set of statewide recommendations from Governor Maura Healey’s K-12 Graduation Council that would, if adopted, put an AI and digital literacy module into a MyCAP milestone — on a long runway, not this school year, and not as law today.

Even the Boston coverage had to walk the first claim back. WBUR corrected an earlier version after a city spokesperson clarified that the program’s goal is to ensure students are proficient at AI, “but it is not yet a requirement.” NBC Boston added an editor’s note that a previous version incorrectly called the programming a diploma rule. Boston.com’s March 27 headline still said the city would “require AI training.” That headline language is the error this piece exists to unwind.

If you teach in a co-op, run a microschool, homeschool, or work in a private school, you are not bound by either story. You should still watch both. The public-school definition of “AI literacy” will leak into tools, co-ops, and parent anxiety. Better to know what was actually announced than to parent against a headline.

What Boston’s September launch actually is — and isn’t

On March 26, 2026, Mayor Michelle Wu, BPS Superintendent Mary Skipper, and Paul English announced a public-private partnership: a $1 million contribution from English to Boston Public Schools, with UMass Boston’s Paul English Applied Artificial Intelligence Institute as the curriculum, educator-training, and student-engagement partner. The city’s press — last updated March 27 — frames the work as giving students and staff “opportunities to become proficient in AI.” That is a proficiency push, not a diploma gate: no published competency rubric, and no test that unlocks a diploma.

The launch is in participating high schools — secondary, not K–12, and not the whole district on day one. Partners have described a start on the order of about 20 high schools; English has talked about training one teacher from each of the city’s roughly 25 high schools as AI ambassadors. The public materials do not publish a named school list, and contemporaneous reporting noted it was still unclear which grades inside those high schools would get the curriculum first. The project FAQ: teacher training begins summer 2026; students in participating schools begin the foundational curriculum in 2026–27, with expansion to follow.

As of August 28, 2026, that remains the plan. BPS’s first student day for grades 1–12 is September 8. No delay has been announced, and the curriculum has not launched in classrooms yet.

The partnership, as the city and project site describe it, also includes professional development, industry-informed curriculum, college-level AI coursework for some students, career-pathway access, and a Boston Public AI Advisory Board co-chaired by English and Ellen Rubin of Glasswing Ventures. Wu said the curriculum is “really grounded in ethics” and meant to “enhance the learning that’s happening, not replace or substitute for it.” That is design intent, not an outcome we can verify from the kitchen table.

The actual “must” in Boston is a use policy, not a diploma

On June 10, 2026, the Boston School Committee approved BPS’s first Artificial Intelligence Policy (TECH-06). That is governance for how staff and students may use AI inside the district, not a diploma rule. AI must not replace human judgment or be the sole basis for grading, placement, discipline, or evaluation. Only district-approved tools. No personally identifiable information in unapproved tools. Vendor contracts must keep district data from training public AI models. Staff and students are to be trained in AI literacy — the ability to understand, evaluate, and use AI responsibly, “regardless of whether you use AI tools or not.” Students “must not use AI tools to replace their own critical thinking, learning, skill building, and effort.”

That last line is closer to a mission filter than any fluency headline: approved-tools list, no PII in the random chatbot, a human still responsible for the grade.

What the Healey recommendations actually are

On June 17, 2026, Governor Healey released the final recommendations of the K-12 Graduation Council, submitted by Education Secretary Stephen Zrike and Commissioner Pedro Martinez. The proposed public-school framework: MassCore coursework, end-of-course assessments, a My Career and Academic Plan (MyCAP), and a culminating capstone or portfolio.

AI is not a standalone required course in that package. If the framework is adopted, all students would complete an AI and digital literacy learning module through a proposed required MyCAP milestone — foundational knowledge about emerging technologies, responsible use of AI tools, and AI’s impact on education, work, and everyday life. Districts would have flexibility: their own coursework or a state-developed module. Nothing in that language requires putting generative AI in a student’s hands. The AI piece was elevated into the final report after stakeholder input, and the report itself says the recommendation may need updating over time.

Healey’s office said that if adopted, the framework would create the most comprehensive statewide high-school expectations in the nation. “If adopted” is doing the work. As of August 28, 2026, it has not been adopted, is not statute, and is not in effect. A Massachusetts diploma today is still the Competency Determination plus local rules; DESE’s graduation page still presents the June package as recommendations. GBH reported that legislation and then Board of Elementary and Secondary Education regulations would still be needed. When the state board took the package up in late June, members were in discussion — not a vote to put it in effect.

If it ever were adopted, the proposed timeline is not this fall: MassCore for incoming ninth graders in fall 2027; remaining components, including MyCAP milestones, with the next year’s ninth graders. The earliest class that could graduate under the full package would be 2032 — a proposed runway, not an enacted calendar. None of this automatically binds homeschoolers, co-ops, or private schools. Massachusetts homeschooling runs through local plan approval under G.L. c. 76, §1. The report is addressed to public school districts.

Why watch both anyway if you’re not in public school

You will still feel the weather. When a major-city district and a gubernatorial council both start defining “AI literacy,” vendors, platform defaults, and co-op parents tend to copy the public definition — sometimes the careful version, sometimes the headline. “Proficiency” can quietly become “the kids should be using the tools.” A MyCAP module described as foundational knowledge can quietly become a how-to-prompt unit. Parent anxiety fills the gap: Is my kid behind if their co-op isn’t doing this in September?

They are not behind a diploma rule that does not exist. They might be behind a cultural shift. That is a design question: can a student understand, evaluate, and refuse a shortcut — or only operate a tool?

The Auxesis read

Auxesis exists to augment intelligence, not sell a shortcut. Two questions on every claim: Does this augment thinking, or replace it? Does this deepen learning, or shortcut it?

Boston’s own policy says students must not use AI to replace their own thinking. Wu said the curriculum should enhance learning, not substitute for it. The Healey language is foundational knowledge and responsible use, with local flexibility. That is the opening. It is not a guarantee.

Literacy that deepens thinking teaches a kid to question the machine: What did it assume? What would I have to verify? Where did my judgment go? Literacy that is a compliance checkbox teaches a kid to operate the machine: log in, prompt, paste, move on. One of those is intelligence. The other is a new kind of busywork with a modern logo.

We cannot tell you which version participating BPS high schools will get in September. We can tell you the question to ask before you copy either one into a co-op Tuesday or a homeschool block.

If your kid’s school — or co-op — added an “AI literacy” unit this fall, would you want it to teach them how to use the tools, or how to catch when the tools are doing the thinking?

Continue this in the community → Auxesis Community

Sources

For two years, Auxesis has made an argument that felt, at times, like we were making it alone: that a student can look like they’ve mastered something — fast, fluent, high scores — while the actual thinking never happened. We call this the illusion of mastery. It’s the thing we exist to fight.

This month, two independent education writers walked into a well-funded, fast-growing math platform called Math Academy and came out describing the exact same problem, in almost the exact same words — without ever having heard of us.

What happened

Math Academy markets itself on speed. Math educator Michael Pershan spent a month inside the platform, working through a full course, to see what that speed actually produced. His account, Math Academy: A Mixed Review, is careful and fair, but one line does the most damage: “Math Academy offers direct instruction for procedures, discovery learning for concepts.” In practice, he found, the platform hands you the steps for solving a problem clearly and quickly — and leaves you to construct the why almost entirely on your own, with no one checking whether you actually did.

Pershan’s sharper point is about incentives, not just design. The platform awards experience points for completing exercises, he writes, not for reading the conceptual explanations sitting alongside them: “If the exercises don’t require the concepts, then the concepts only inhibit your progress and kids will drive past them at 75 mph.” A student can hit every target the app measures without ever slowing down for the part where understanding actually forms.

Dan Meyer picked up Pershan’s review and went after the marketing claim itself in a piece titled “It Is Fun to Pretend That Hard Things Are Easy!” He points out a pattern common to platforms that promise to have cracked the code on faster learning: they quietly redefine what “learning” means — not to educators, not to universities, not to the people who eventually have to use the math for something real, just to their own dashboard. Fast completion of exercises gets rebranded as mastery. The gap between the two is where the illusion lives.

Why this matters beyond one platform

Neither Pershan nor Meyer set out to make our argument. They set out to review a product. That’s what makes it useful. When a business built around a critique makes that critique, it’s easy to dismiss as self-interested. When two working educators, with no connection to each other or to us, independently spend real time inside a platform and land on the same conclusion — using almost the same language — that’s a signal the pattern is real, not a marketing angle.

The pattern, stated plainly, and stated by them, not us: speed and fluency are being measured and rewarded. Understanding is not. A system that only measures what’s easy to measure will quietly train students, and the adults watching them, to mistake the measurement for the thing itself.

What we’d ask instead

Auxesis builds around a different question: not “did the student finish,” but “can the student explain it, apply it somewhere new, and still have it a month from now?” We call that the difference between Explain, Apply, and Sustain — the three conditions that have to hold before we call something mastered. A student can pass a platform’s exercise set, by Pershan’s own account, and still fail all three. That gap is not a rounding error. It’s the whole problem.

None of this means adaptive practice tools are worthless — deliberate, well-designed practice has a real place, and Pershan says as much in his review. The problem isn’t that Math Academy exists. It’s that “fast” and “learned” are being treated as the same word, at a moment when a lot of anxious parents are looking for a shortcut and being told, credibly, that one exists.

The reviewers didn’t need us to tell them that. They found it themselves, inside the product, and wrote it down. Our job now is simple: point at what they found, and say it plainly, before “cognitive offloading” gets flattened into a buzzword nobody bothers to define.

# The Internet Says Homeschool Parents Aren’t Qualified. Here’s Why They’re Wrong — And How AI Is the Proof.

*A version of this article first appeared on Reddit’s r/NoStupidQuestions, where it gathered over 17,000 upvotes and nearly 3,000 comments. The debate it sparked reveals something important about how we think about education — and who gets to do it.*

—

“The problem of the world is that intelligent people are full of doubts, while stupid ones are full of confidence.” — Charles Bukowski

If you’ve been homeschooling for more than a week, you’ve probably seen the thread.

It goes something like this: someone on Reddit asks why parents who “barely passed high school” think they can teach their kids. The post goes viral. Thousands of people pile on. The top comments call homeschool parents arrogant, underqualified, delusional. One response suggested that the real problem with homeschool kids is that “the intelligent people are full of doubts.”

In other words: the very trait that makes a good homeschool parent — humility, willingness to question your own certainty — gets spun as evidence of incompetence.

It’s a trap. And it’s one that homeschool parents have been losing at for decades.

But something has changed. Something that makes the old attack not just wrong, but provably wrong.

**AI doesn’t just help homeschool kids learn. It makes the “unqualified” parent more qualified than any classroom teacher — by the standards those critics actually believe in.**

—

## The Qualification Standard Was Always a Moving Goalpost

Before we get to AI, let’s be honest about what “qualified to teach” has always meant in the public conversation.

The critics say: you need a teaching degree. You need to know the subject matter deeply. You need pedagogical training. You need certification.

But here’s what actually happens in a public school classroom: a teacher with a literature degree teaches math because the school has a staffing gap. A first-year teacher with no classroom management experience gets thrown into a Title I school with 32 students and no aide. A science teacher reads from the textbook because the lab budget was cut three years ago and hasn’t been restored.

The qualification bar, it turns out, is applied selectively.

—

## What AI Actually Does to the Qualification Equation

When a homeschool parent uses AI as a learning partner, it does three things that directly address every legitimate criticism of unqualified teachers.

### 1. AI Knows What You Don’t Know (And Shows You Where to Start)

The old standard for a qualified teacher was: have the knowledge already. The new reality with AI is different: You don’t need to have the knowledge. You need to know how to find it, guide the search, and make sure your child understood what they found.

When your daughter asks about photosynthesis and you genuinely don’t remember the Kreb’s cycle, you have two choices:

**Old model**: Pretend you know, make something up, hope she doesn’t notice. Or say “I don’t know” and feel the creeping dread that you’re failing her.

**AI model**: Say “That’s a great question — let’s ask our AI Guide.” You open it together. You read the answer together. You ask follow-up questions together. Your daughter sees you model how to learn something you don’t know. She internalizes the process — curiosity, search, verification, synthesis — not just the fact that chloroplasts make energy from sunlight.

The teacher who “knows it all” models expertise. The parent who learns alongside their child models how to learn. Research has consistently shown that metacognitive modeling is one of the most durable forms of instruction. AI makes that modeling possible for every parent, regardless of what they remember from high school biology.

### 2. AI Personalizes the Pace That a Classroom Teacher Can’t

A classroom teacher with 28 students cannot slow down when one child is confused. They cannot accelerate when another is bored. They teach to the middle — which means the advanced student gets bored and the struggling student gets left behind.

A homeschool parent with AI can do something different. If your 4th grader doesn’t understand fractions after the third explanation, AI can re-explain it from a completely different angle — using money, using geometry, using a cooking analogy. It can generate 20 more practice problems at exactly the right difficulty level. It can adapt in real-time based on where your child gets stuck.

This is called adaptive learning. It’s what the best private tutors do. And AI makes it accessible to every homeschool family with a laptop — regardless of what the parent’s math grade was in high school.

The qualified classroom teacher has a degree but no time. The “unqualified” homeschool parent has AI and all day.

### 3. AI Identifies Gaps You Don’t Know to Look For

Expertise doesn’t just mean knowing the answer. It means knowing what you don’t know.

A parent who took chemistry in 1998 doesn’t know that the way they were taught the atom has been updated. They don’t know that the “Aufbau principle” has been superseded in some curricula by a more accurate model. They’re teaching confidently, but with wrong information.

AI doesn’t have this problem. AI trained on current curricula can identify where a child’s understanding has a gap, which prerequisite concepts they need, and which misconceptions are taking hold. A parent who uses AI as a learning guide is more likely to catch these gaps than a parent who thinks they remember the subject perfectly.

—

## The Reframe That Changes Everything

Critics of homeschool parents keep using the same word: qualified.

But what does that word actually mean?

If it means “knows every fact in every subject your child will study,” then yes, most homeschool parents are not qualified. Neither are most classroom teachers, if we’re being honest.

If it means “can facilitate learning in a way that builds genuine understanding and the ability to think critically,” then the answer is very different. And it’s changing fast.

**Your job is not to be the encyclopedia. It’s to be the learning coach.**

The best homeschool parents have always understood this. They were mocked for it. Called arrogant. Called underqualified. But here’s what the critics missed: the knowing everything model of education was always wrong.

What your child actually needs — in an age where AI can answer any factual question in seconds — is not an encyclopedia. They need to know how to ask the right questions. How to evaluate an answer. How to think through a problem they haven’t seen before. How to recognize when they don’t understand something, and how to work through that confusion.

Those are the skills that don’t expire. Those are the skills AI amplifies rather than replaces.

—

## What This Looks Like in Practice

A friend of mine — her highest credential is a GED — was asked by her 6th grader why the sky is blue. She had no idea. Instead, she opened an AI tool with her daughter and typed:

*”My child is learning about light and color. They asked why the sky is blue. Don’t give us the answer yet. Ask us one question at a time to help us figure it out.”*

What followed was a 20-minute conversation between her daughter and the AI. They talked about what “color” actually means. About why sunsets are red. About what happens to light when it hits air molecules. Her daughter asked follow-up questions the AI had prompted her to think of.

At the end, her daughter said: “Wait, so the sky is blue because of something called Rayleigh scattering? That’s so weird. I’m going to look that up later to see if it’s real.”

She was skeptical. She was curious. She was driving her own learning.

**That’s the goal.** And this mother — dismissed by internet strangers as “unqualified” — made it happen. Not by knowing the answer. By knowing how to facilitate the question.

—

## The Permission Slip You’re Allowed to Sign

If you’ve been homeschooling for any length of time, you’ve probably felt it. That moment when your child asks a question and your stomach drops because you genuinely don’t know the answer.

You are not failing. You are not unqualified.

You are doing exactly what education researchers have been saying for decades is the most valuable thing a teacher can do: model how a literate, curious person learns something new.

The internet wants to tell you that you need a teaching degree to teach your kids. The internet is wrong — or at least, it’s using the wrong definition of “teach.”

**You are not the content source. You are the learning architect.**

And with AI as a partner in that work, the gap between what you know and what your child can learn has never been smaller.

—

*This is what Auxesis builds toward: not replacing the parent with AI, but equipping the parent with AI so that the most important educational relationship — between a curious child and a learning coach who loves them — gets stronger, not weaker.*

*If you’re a homeschool parent who’s felt the weight of “am I qualified enough,” consider this your permission slip.*

*You are. And AI just made it easier to prove it.*