A new paper just published in AI & Society puts the AIR framework research transparency model under a microscope—and the results are a mixed bag. The framework is a genuine leap forward for honest AI disclosure in research. But it also has five significant gaps, and one of them could quietly punish disabled and neurodivergent researchers for using the very tools that make their work possible.

A device that streams your child’s behavior to adults but can’t lower the noise, dim the lights, or ease social demands is not a safety tool—it’s a surveillance tool. Monitoring tech child safety is only real when it can change the environment, not just record the struggle.

If a therapy leaves your child more anxious, exhausted, or ashamed, the fact that it has randomized trials behind it does not obligate you to keep signing the consent forms. “Evidence‑based” is not a magic word that trumps your child’s lived experience.

For decades, most “autism research” has quietly treated autistic people as problems to be managed, not as people whose lives should get better. The primary outcome has been behavior control for neurotypical comfort, not autonomy or quality of life for autistic communities themselves.

Stimulant meds can be life‑changing, but “take your pills” has quietly become the only ADHD medication accommodation many schools and employers are willing to offer. This piece explores how powerful tools are being used to patch broken systems instead of redesigning them.

Most “autism tech” isn’t actually built to make autistic lives safer or less painful. It’s built to watch—tracking gaze, movement, and “engagement” so adults can see dashboards and funders can see metrics, while the autistic person absorbs the risk and rarely gets more control.

Many autistic adults now describe their early “intensive therapy” as ABA trauma: years of compliance training and stimming suppression that left them with PTSD‑like symptoms and a deep mistrust of their own bodies. This piece explores how that happens, and what care would look like if we put autistic people’s safety—not adult comfort—at the center.

I patented an ethical AI wearable to help neurodivergent people manage sensory overload. Turning my S²MHD and DAD Framework research into hardware forced a non‑academic question: when AI is strapped to a human nervous system, who is the data really for, who controls it, and whose comfort does the device ultimately serve?

A large-scale randomized trial in high school math found that unrestricted GPT‑4 help during practice boosted grades in the moment but left students 17% worse off on a later, no‑AI exam. For neurodivergent learners, that’s not just a statistic — it’s a safety warning about how schools are rolling out AI.

Schools, therapy centers, and community organizations are adopting AI tools for autism support without asking the most important question: who built these tools, and who did they ask? On April 17, I'm presenting the answer — and it's not comfortable.

There's a hidden cost to AI reliance that nobody is measuring yet. Dr David Ruttenberg introduces Cognitive Debt — the accumulated neurological toll on attention, learning, and mental health from chronic AI over-reliance — and asks whether we're building it into the default without ever deciding we should.

As AI systems increasingly impact healthcare, hiring, and public safety, hidden risks and biases continue to arise. This article reveals why autistic and neurodivergent professionals bring unmatched skills in pattern recognition, data validation, and ethical oversight that are essential for responsible AI.