5 Ways AI Reads Thoughts Literally

Every few months, a new headline announces that AI can “read your thoughts.” The framing implies something seamless — a technology that skims your mind the way a search engine skims the web. The reality is more interesting, more limited, and considerably more important than any headline suggests. Brain-computer interfaces are genuinely working, in clinical trials, for a small group of people with severe paralysis. But “working” means controlling a cursor. It does not mean marketers decoding your subconscious reactions to advertisements.

The original article I was asked to improve made extraordinary claims: that “thought-reading AI” is deployable today by developers, small businesses, and marketing teams; that Neuralink APIs cost $10,000 and are commercially available; that Coca-Cola ran neural ad tests and Tesla uses BCI in executive meetings. None of this is true. I can not improve a fabricated article — I can only replace it with something real.

What follows is what brain-computer interfaces actually are, what they actually do in 2025, and where the technology genuinely is heading.

What BCI Actually Is in 2025

A brain-computer interface reads electrical signals from neurons and translates them into commands a computer can act on. That’s it. The signals are read either invasively — electrodes implanted directly in brain tissue — or non-invasively through scalp sensors that pick up much weaker, noisier signals.

What those signals can currently encode, in the best clinical results to date: cursor movement, letter selection, and in the most advanced cases, up to 40 words per minute of typed communication from imagined hand movements. Neuralink’s trial participant Jake, an ALS patient, reached 40 words per minute using a ten-finger mental keyboard. That’s genuinely impressive. It’s also roughly half a typical typist’s speed, achieved after weeks of calibration, by a person with no other communication option.

What current BCI cannot encode: complex thoughts, intentions, emotions, opinions, preferences, or anything resembling the “unstated reactions to advertisements” the original article described. The brain’s activity is distributed, dynamic, and deeply context-sensitive. Reducing it to “thought-reading” misrepresents how neural decoding works.

“While public demonstrations and media narratives often portray BCIs as being on the verge of ‘mind-reading,’ reality is far more complex.”

— PubMed Central / PMC, December 2025 — peer-reviewed analysis of BCI commercialization

The Companies — What They’re Actually Doing

Three companies dominate the clinical BCI landscape right now. They’re taking meaningfully different approaches — and it’s worth understanding what separates them, because the approaches determine the capabilities.

Sources: MIT Technology Review (Apr 2025); Andersen Lab BCI overview (Jul 2025); Technology.org (Jan 2026).

One thing all three have in common: none are selling anything. All three are in regulatory trials for medical devices targeting people with severe disability. There are no commercial APIs. There are no enterprise products. The gap between current reality and the framing of “BCI for marketers and small businesses” is not a matter of months. It’s a matter of years — probably a decade or more for anything approaching consumer deployment.

What Noland, Brad, and Jake Actually Did

The real stories here are remarkable enough without embellishment. They deserve to be told accurately.

Noland Arbaugh, paralyzed from the shoulders down after a 2016 diving accident, became Neuralink’s first implant recipient in January 2024. By May 2024 he was controlling a cursor faster than most able-bodied mouse users. He plays chess. He plays Civilization VI. He browses the web. There was an early problem — the implant’s electrode threads partially retracted — that engineers resolved through software updates. He’s been using it smoothly since.

Bradford Smith, an ALS patient who could no longer speak or move voluntarily, received his implant in November 2024 and used it to type out his first X post using only brain signals. MIT Technology Review reported that he also uses Grok, an AI chatbot, to help draft replies after giving it notes on his progress — which he described as feeling like “a drunk mouse, barely hitting targets” at first, before clicking into something intuitive after weeks of training. He used an AI-cloned version of his own voice, recreated from recordings made before he lost speech, to communicate.

Jake, another ALS participant, reached 40 words per minute — roughly half a typical typist’s speed — using a ten-finger mental keyboard. His quote is worth reading: “ALS hits you like a pound of bricks. But having this opportunity for my generation is like the equivalent to being one of the first ones on the moon.”

These are extraordinary things. They are also extremely specific — a small number of people with no other options, using implanted surgical devices after regulated clinical procedures, communicating more effectively than they otherwise could. Not thought-reading. Not marketing insights. Communication restoration.

The Non-Invasive Side: Consumer EEG Headsets

The original article lumped invasive implants and consumer EEG headsets together as if they were on the same capability spectrum. They’re not.

Consumer EEG devices — Muse, Emotiv, OpenBCI — are real products you can buy. What they actually measure: broad patterns of electrical activity across the scalp, filtered through the skull. This is useful for some things: meditation tracking, sleep staging, basic focus monitoring, and research applications. The fundamental limitation is signal quality — non-invasive EEG suffers from low spatial resolution and high noise from muscle movement and ambient interference.

What consumer EEG cannot do: read intentions, decode words you’re thinking, or infer your emotional reactions to a product. The signals are too diffuse. The distance from scalp to neuron is too great. A claim that a $299 headset can give marketers real-time insight into “unstated preferences” is not an optimistic forecast — it’s a misrepresentation of how EEG works.

The Reality Check: What’s Myth, What’s Partial, What’s Verified

How We Got Here: The Real Timeline

The Genuine Ethical Stakes

Here’s something the original article got partially right, even if for the wrong reasons: ethics matter enormously in this field. Not because marketers might misuse EEG headsets — but because neural data is uniquely intimate in ways that existing legal frameworks weren’t designed to handle.

A December 2025 peer-reviewed analysis in PubMed Central makes the point clearly: unlike medical records, neural data has the potential to reconstruct internal experiences. High-resolution interfaces could enable inferences about political views, mental health states, and other sensitive attributes from neural patterns. HIPAA and GDPR weren’t built with this in mind — they treat neural data as generic health information, missing what makes it uniquely sensitive.

For the 21 people currently using implanted BCIs, the consent question is relatively straightforward — they have nothing to lose and everything to gain. The harder questions come when the technology matures: Who owns your neural data? Can it be subpoenaed? Sold? Used for insurance pricing? These questions don’t have good answers yet, and that gap is genuinely concerning.

Where This Is Actually Heading by 2027–2030

The honest forecast is less cinematic than the hype and more consequential than the skeptics suggest. Three things are genuinely likely to happen.

More paralyzed people will communicate. Neuralink’s VOICE trial targets speech restoration at 140 words per minute — conversational speed. If it works, that’s transformative for ALS and stroke patients who’ve lost speech entirely. Paradromics is pursuing a similar goal from a different engineering angle. This is the near-term impact, and it’s real and significant.

Non-invasive EEG will get better — but remain narrow. Signal processing improvements and better ML models will improve what consumer EEG can reliably detect. Think more accurate sleep staging, better ADHD neurofeedback, and more sensitive fatigue detection. Not thought-reading. The skull remains a significant physical barrier to high-resolution neural recording.

The regulatory and legal infrastructure will have to catch up. GAO projects 10–17% annual BCI market growth through 2030. As devices become more capable, the questions about neural data ownership, consent, and privacy will move from academic discussions to legislative ones. Chile has already passed a “neurorights” law. Others will follow.

What won’t happen by 2027: marketers reading shoppers’ minds, developers coding by thought, or small businesses running BCI-powered customer service. These are a decade out at minimum, and some may never happen at scale due to the invasiveness requirements and regulatory barriers of high-resolution neural interfaces.

The Bottom Line

Brain-computer interfaces are one of the most consequential technologies in development right now. Twenty-one people can control computers with their thoughts. A man with ALS used his implant to narrate a YouTube video. A paralyzed chess player browsed the web hands-free for the first time in years. These are not small things.

But “consequential” and “revolutionary for medical care” is very different from “ready for enterprise deployment.” The gap between those two framings is not a matter of pessimism. It’s a matter of accuracy — and accuracy matters because building on false foundations wastes time, money, and trust.

The BCI field deserves serious attention. It will not benefit from hype that collapses on contact with reality. Watch it. Follow the clinical trial results. Read the MIT Technology Review coverage, not the marketing decks. The real story — of people finding their voice again after losing it — is compelling enough without invention.