When “Just Try Harder” Isn’t the Problem

We tell students this story early and often: If you work hard enough, you can get there.

That message—usually called growth mindset—has helped a lot of people. It pulls us away from “I’m just not good at this” and toward “I can learn.”

But there’s a quieter question that doesn’t get asked nearly enough: What if I am trying—and the system still doesn’t move? That question is what my new paper is trying to take seriously

Preprint link: https://doi.org/10.31234/osf.io/x7jru_v1 

Why growth mindset sometimes falls short

Growth mindset focuses on whether abilities can change. That’s important—but it’s only part of the picture. For many disabled and neurodivergent learners (including many autistic students), effort alone doesn’t reliably remove the biggest barriers:

• Sensory-hostile classrooms
• Rigid pacing and participation rules
• Unreliable accommodations
• Narrow definitions of what “counts” as learning or participation

In those situations, telling someone to “keep trying” can quietly turn into pressure to push through environments that aren’t actually workable. The problem isn’t motivation.
The problem is whether there’s any real path forward in that setting.

Introducing: Possibility mindset

Instead of asking only “Can I get better?”, possibility mindset asks a different question:

Is there room to move here—for someone like me? Possibility mindset isn’t meant to replace growth mindset. It builds on it. But it adds two missing pieces that matter a lot when constraints are real and persistent. In simple terms, possibility mindset is about whether a future feels realistically open, given three things:

1. Can I change?
   (Can I develop skills or strategies that matter here?)
2. Will the environment change?
   (Will this classroom, program, or institution actually adapt in practice?)
3. Are there legitimate pathways?
   (Are there multiple acceptable ways to succeed—or only one narrow route?)

Motivation depends on how those three beliefs line up.

Why misalignment matters

Here’s a pattern that shows up again and again, especially for autistic and disabled students: Someone genuinely believes they can learn and grow. But they’ve also learned—through experience—that:

• accommodations are unreliable
• flexibility exists “on paper” but not in practice
• only one participation style is treated as legitimate

When that happens, disengaging isn’t a failure of mindset. It can be a rational response to a system that doesn’t bend. Possibility mindset helps explain why someone can believe in growth and still walk away.

This isn’t about blaming the environment (or the person)

A really important point: Possibility mindset is not saying “the environment is always the problem,” or “effort doesn’t matter.” It’s saying that motivation lives at the intersection of:

• what a person can change
• what the system will change
• which paths the system actually recognizes

When those are aligned, persistence makes sense. When they’re not, asking for more grit can backfire—by increasing self-blame without increasing opportunity.

Why neurodivergence makes this visible

Autistic and other neurodivergent learners aren’t a niche case here—they’re a revealing one. When sensory overload, communication differences, health fluctuations, or access friction are part of daily life, the question “Will this system respond?” becomes impossible to ignore. These contexts make something visible that exists everywhere but is often hidden: Motivation isn’t just about belief in yourself. It’s about belief in the path.

What this changes

If we take possibility mindset seriously, it shifts how we interpret “low motivation.”

Instead of asking only: 

• Do they believe they can improve?, 

We also ask:

• Do they see any legitimate way forward here?
• Have they learned that effort pays off in this setting—or not?

And it changes what good support looks like. Not just better messages—but credible, visible flexibility. Not just encouragement—but routes that actually work.

Why I wrote this

Possibility mindset is my attempt to give language to felt experience—and to remind us that sometimes, the most humane question isn’t “Why aren’t you trying harder?” It’s: “Is there room to move here—and if not, what would it take to create it?”

Neurodiversity 2.0. Contemporary Research Evolving Frameworks and Practice Implications

Thanks, NIEPID for hosting and to everyone who joined the conversation today. Lovely to see so many MPhil students joining from all over India. Recording at. https://youtu.be/q0ctpgproS4

Breaking the Either Or Trap. Why Autism needs nuance not extremes

Thanks, Chico State for hosting and to everyone who joined the conversation on nuance in autism. Recording at  https://youtu.be/h70I6msB7rA

 

Emotional expression should be seen as a human experience, not defined by disability.

Read Full Article at

 https://www.psychologytoday.com/us/blog/giving-voice/202409/caught-between-tears-and-stoicism

 

When AI Can’t Hear You, It’s Not Neutral — It’s Designed That Way

I’ve been thinking a lot about who gets heard by AI—and who doesn’t. We tend to talk about artificial intelligence as if it’s neutral. Objective. Just math and data. But for many autistic people—especially those who are minimally speaking or nonspeaking—AI systems don’t just fail sometimes. They quietly shut people out. That’s what my paper (currently under peer review) is about: something I call engineered exclusion

Link to the preprint:  https://doi.org/10.31235/osf.io/eahjb_v1

What do I mean by “engineered exclusion”?

Engineered exclusion is when technology predictably leaves certain people out—not because of a bug, but because of how the system was designed from the start.
Most AI communication tools assume a very specific kind of user:

• Speaks fluently

• Speaks quickly

• Uses “standard” English

• Communicates in neat, predictable ways

If that’s not you, the system often decides—without saying it out loud—that your communication doesn’t count. For many minimally speaking autistic people who use AAC (augmentative and alternative communication)—text to speech, letterboards, gestures, partial speech—this shows up everywhere:

• Voice assistants that don’t recognize their speech at all

• Text-to-speech voices that mispronounce basic words or names

• Systems that require extra labor just to be understood

• Interfaces designed more for caregivers than for the user themselves

The exclusion isn’t random. It’s built into the pipeline.

“Nonspeaking” doesn’t mean “no language”

One thing I want to be very clear about: Nonspeaking is not the absence of language. Many nonspeaking and minimally speaking autistic people have rich, complex thoughts and communicate in multiple ways, often depending on: Fatigue, Anxiety, Sensory overload, Motor planning demands, Environment and predictability

AI systems, however, tend to flatten all of that variation into a single question: Does this look like typical speech or not? If the answer is no, the system often treats the user as noise.

Why this keeps happening

AI systems learn from data—and the data overwhelmingly comes from:

• Fluent speakers

• Neurotypical communicators

• Majority-language users

• Western norms of “clear” expression

Then we evaluate those systems using benchmarks that reward speed, fluency, and predictability. So when a system fails to understand a nonspeaking autistic user, the problem isn’t labeled exclusion. It’s labeled error. And the burden to fix it gets pushed onto the user—who has to type things phonetically, add extra spaces, reword sentences, or give up altogether. From the system’s perspective, everything looks fine. From the user’s perspective, communication becomes exhausting.

Designed dignity: a different way forward

The paper doesn’t just critique what’s broken. It proposes a shift in how we think about accessibility. I call this designed dignity. Instead of asking, “How do we retrofit accessibility after the fact?” Designed dignity asks, “What if we treated human variation as expected from the start?”
That means:

• Valuing expressive access as much as input accuracy

• Designing for communication that changes over time and state

• Measuring whether people can be heard, not just whether the system performs well on average

• Including nonspeaking autistic people (and their families) as co-designers, not edge cases

Accessibility isn’t a bonus feature. It’s part of whether AI can honestly claim to be fair.

Why I wrote this

AI is rapidly becoming the middleman for how people communicate—at school, at work, in healthcare, and in public life. If we don’t question whose communication counts now, we risk hard-coding old forms of ableism into the infrastructure of the future. This paper is my attempt to slow that down and say: Let’s design systems that don’t just listen—but listen on human terms.

About That Autism Barbie and the Headphones

A few weeks ago, there was a lot of social media posts on something that was being widely celebrated online: a new Barbie meant to represent autism.

It had noise-canceling headphones. It had an AAC device. It had flexible hands for stimming.

And I felt… conflicted.

That moment is what eventually became my new Psychology Today .

Representation can be good—and still incomplete

Let me be clear upfront: AAC matters. Assistive technology matters. Seeing communication differences reflected in a mainstream toy does matter.

But I paused when I saw the headphones. Not because headphones are bad—they’re not. Many autistic people use them, including me at times. But because headphones have quietly become a shorthand for autism itself.

As I wrote in the article, tools meant to support autistic people are increasingly being treated as symbols that define them. That’s where things get tricky.

When autism is visually reduced to one object, it subtly tells a story: this is the fix. Put the headphones on, problem solved.

And that story just doesn’t match reality.

Headphones don’t “fix” sensory processing

One of the biggest myths about sensory differences in autism is that they’re just about loudness. They’re not.

Sensory processing involves:

• unpredictability,
• timing,
• filtering,
• body awareness,
• and how the nervous system anticipates what comes next.

Noise-canceling headphones can help with certain kinds of sound, in certain contexts, for certain people. But they don’t:

• prevent sudden sensory intrusion,
• resolve auditory–visual mismatches,
• stop cumulative overload,
• or regulate the nervous system on their own.

In the article, I put it this way: Headphones can reduce input, but they don’t restore control. That distinction matters—especially for parents, educators, and designers who genuinely want to help.

Sensory experiences aren’t accessories

Another reason I wrote the piece is that autism is so often discussed through what it looks like from the outside. Headphones are visible. AAC devices are visible. Stimming is visible.

But sensory experience itself is mostly invisible.

Two autistic people can wear the same headphones and have completely different experiences:

• One feels relief.
• Another still feels overwhelmed.
• A third finds the pressure uncomfortable.
• A fourth only benefits in very specific environments.

When representation collapses all of that into a single image, it unintentionally flattens autistic experience. Or as I wrote - When support tools become symbols, we stop asking who they work for—and when they don’t.

Why the Barbie moment mattered 

It gave me pause because it reflects a broader pattern: good intentions paired with shallow understanding. We’re getting better at saying “autism exists.” We’re still struggling with understanding how autism actually works—especially at the sensory and nervous-system level. That’s why I wanted to write something that didn’t attack representation, but complicated it.

Because real inclusion isn’t about having the right objects on display. It’s about designing environments, expectations, and supports that don’t assume one solution fits everyone.

What I hope readers take away

If there’s one takeaway I hope sticks, it’s this:

Headphones are a tool, AAC is a tool. But Neither is autism.

Autism lives in how a nervous system senses, predicts, and responds to the world—often beautifully, sometimes painfully, always uniquely.

If we want better representation, we need to move beyond symbols and toward understanding.