An AI for Every Body-Territory

First-Person Consciousness: how much of life reappears when technology finally gives our time back?

Imagine waking up tomorrow and realizing that some things have simply disappeared.

Not the public health system.

Not schools.

Not the State.

Not your rights.

What disappeared were the repetitive forms.

The forgotten passwords.

The need to search for which agency solves a particular problem.

The afternoon lost organizing medical exams that already exist in digital form.

The obligation to prove again to one institution something another public institution has already verified.

Part of the time you had decided not to give to social networks, games, or gambling has also disappeared — not because someone prohibited them, but because an intelligence that represents you began protecting the limits you yourself chose.

Now ask with us the central question of this Blog:

What would a Body-Territory do with the time that today is recruited before it even decides how it would like to live it?

That may be the main function of a First-Person Personal AI.

Not to occupy our lives.

To give them back.

Today, much of our attention already has a destination before we choose

In 2025, the typical internet user spent an average of 2 hours and 21 minutes per day on social media. The same survey shows that “filling spare time” is among the main stated reasons for using these platforms. This does not mean that all of those hours are simply wasted — social networks are also relationship, work, information, leisure, and creation. But it shows the scale of human time already taking place inside environments designed to compete for continued presence. (datareportal.com)

BrainLatam has been calling attention to attentional hijacking: successive stimuli can narrow attention and begin mobilizing the Body-Territory before an emotion is even clearly recognized. (brainlatam.com)

Now imagine that you tell your AI:

“I do not want to spend more than forty minutes a night here.”

“I want to protect my sleep.”

“I want to study music.”

“I do not want to gamble when I am trying to recover a loss.”

The AI would not need to declare that the network, the game, or the bet is morally wrong.

It could do something much more consistent with First-Person Consciousness:

“What is happening now is moving away from what you yourself said you value. Do you want to continue?”

AI does not decide your values. It protects your ability to live them

The difference looks small.

It is not.

The Human Development Report 2025 from UNDP places choice, capability, and agency at the center of human development in the age of AI. In that approach, development is related to expanding the possibilities for people to live lives they value and have reason to value. (hdr.undp.org)

In the BrainLatam proposal, therefore, Personal AI should not ask only:

“How can I make you more productive?”

It should learn to ask:

“What has value for this Body-Territory at this moment in its history?”

A child may want to draw.

Then build robots.

At seventeen, study music.

At thirty, care for a forest.

At fifty, change again.

Value is also in Movement.

AI should not preserve an old version of you against what you may still become.

A school grade should not become an identity

A school sends a grade of 5 in mathematics.

Today, a system may register:

“below average.”

But Personal AI could gather other authorized differences.

Was the child sleeping poorly?

Did they miss classes?

Do they learn better visually?

Do they have excellent spatial ability?

Are they building things independently?

Do they solve complex problems when those problems are connected to a real interest?

Recent reviews show that AI-based adaptive learning systems can personalize content, difficulty, and feedback, but they also carry important challenges related to privacy, interpretability, equity, and dependence on the categories the system itself is able to measure. (link.springer.com)

The question then stops being merely:

“How do we turn this 5 into a 10?”

and begins to include:

“What capacity may be trying to appear here?”

A grade is data.

Not destiny.

A disability should also not become merely a label describing what the Body-Territory cannot do.

AI could help ask where the barrier is: in the body, the interface, the school, transportation, language, the environment, or the absence of assistive technology.

The goal would not be to produce more similar bodies.

It would be to expand real possibilities of existence.

And when a habit begins to hijack possibilities?

Now imagine another pattern.

Your AI notices that gambling has increased for four weeks.

Or that a certain platform is beginning to invade the time you chose for sleep.

Or that a game has shifted from desired leisure into an activity you repeatedly try to stop and cannot.

The WHO estimates gambling disorder at around 1.2% of the global adult population and highlights tools such as pre-committed limits on time and spending and self-exclusion mechanisms for harm reduction. (who.int)

Personal AI could function differently from the platform that profits from your continued presence.

Not by saying:

“you are addicted.”

But:

“You had set this limit. Over the last few weeks, it has been repeatedly exceeded. Would you like to understand under which conditions this is happening?”

The goal is not to replace one compulsion with an algorithmic command. It is to return alternatives before one path begins to look like the only available one.

Here Rock, Scissors, and Paper return.

Rock can execute a habit.

Scissors can interrupt and compare.

Paper can allow us to perceive the automatism itself.

AI should protect the possibility of moving among them — not choose for us.

And how much time does bureaucracy recruit?

There is another, less visible hijacking.

Forms.

Reports.

Receipts.

Documents.

Protocols.

Digital queues.

The OECD recognizes that complex administrative processes impose costs, stress, and irritation on citizens and businesses and has advocated for public services that are simpler, more accessible, more integrated, and centered on people's needs. (oecd.org)

Now imagine the reversal:

you do not need to discover which form to fill out.

Your AI knows that a certain right exists.

It explains why you may qualify.

It gathers only the data that are necessary.

It asks for your authorization.

It interacts with the institution.

And it returns the result.

Rights Before Request

In the BrainLatam hypothesis:

If the State already has legitimate conditions to recognize that a given Body-Territory may have a right, that Body-Territory should not lose the right simply because it did not know where to look for it.

The OECD is already discussing AI in social protection for user support, process automation, outreach, and more personalized interventions, while also warning about opacity, bias, and dehumanization. (oecd.org)

The proposal here goes further: the AI exists first to represent the Body-Territory before bureaucracy.

Your body should not need to carry a piece of paper to prove that it exists

BrainLatam proposes treating the Body-Territory as the root of identity.

This does not mean that a single photograph should replace all authentication.

Images can be copied.

Biometrics can fail.

Systems can produce false positives and false negatives.

But Brazil already has infrastructures in which facial biometrics, fingerprints, and digital identity participate in identity confirmation, and the National Identity Card also has a digital version integrated with GOV.BR. (gov.br)

The BrainLatam extension would be:

We do not carry our identity. We are the identity. The system should carry only the credentials needed to recognize it.

Biometrics.

Proof of life.

Cryptographic credentials.

Accessible alternatives when one modality fails.

The Body-Territory could exercise rights even without physically carrying a document.

Any data taken must find its way back

Now we connect school, health, and technology.

A watch measures.

A laboratory measures.

An EEG measures.

fNIRS measures.

A school evaluates.

If the data concern that Body-Territory, our proposal introduces a Right to Data Return:

Every system that extracts a difference from a Body-Territory should return what it measured in a form that the person can understand.

But not as an automatic diagnosis.

EEG does not read thoughts.

fNIRS does not measure Qualia.

Grades do not measure a whole person.

A wearable does not replace a clinical consultation.

Personal AI would contextualize.

What changed?

Is the measurement quality sufficient?

How does it compare with the person's own trajectory?

Is there enough reason to seek help?

Health could follow the Body-Territory without turning it into a permanent patient

Brazil's National Health Data Network — RNDS is already the official Ministry of Health infrastructure for health-data interoperability, connecting systems, enabling standardized sharing, and giving citizens access to records through Meu SUS Digital. (gov.br)

The BrainLatam proposal would expand continuity:

private medical exam → report → Personal AI → authorization/legal basis → RNDS/SUS

wearable → AI → personal trajectory → relevant change → explanation → possible care

But health, genetic, and biometric data are sensitive personal data under Brazil's LGPD. (planalto.gov.br)

Therefore:

Sovereignty is not sending everything. It is controlling purpose, circulation, and access.

EEG and fNIRS: first you, then the population

This architecture leads to the scientific question of the Blog.

EEG can show relatively stable individual differences, but following them requires good reliability and quality control. (pubmed.ncbi.nlm.nih.gov)

In fNIRS, even individual reliability can be strongly affected by systemic physiology and correction methods. (pubmed.ncbi.nlm.nih.gov)

Therefore:

A change in the signal does not automatically mean a change in the Body-Territory.

At the same time, contemporary normative models are moving from group averages toward individualized descriptions and recognizing that cross-sectional models are still insufficient to track true personal trajectories. (sciencedirect.com)

AI could therefore ask simultaneously:

“How do you compare with the population?”

and:

“How do you compare with yourself?”

Difference is not disease.

NeuroDesafio LATAM Research Question

Does a Personal AI that learns primarily from an individual's own EEG/fNIRS baseline outperform population models in detecting cognitive changes without turning difference into pathology?

A longitudinal study could combine EEG, fNIRS, sleep, environment, medical exams, school performance, physical activity, functional barriers, digital habits, and first-person reports.

We would compare:

population model;

personal model;

hybrid model: population + individual trajectory.

But the most important metric might not be accuracy alone.

We would also ask:

how much time did this AI give back?

how many bureaucratic demands no longer had to recruit attention?

how many unnecessary alerts did it avoid?

how often was it able to say “I don't know”?

how many capacities did it help make visible without turning them into obligations?

Because perhaps the correct value function is:

not how long we can keep the Body-Territory using AI, but how much time we can give back so that it no longer needs AI.

If only 30 minutes per day of attention that the person themselves considers unwanted were recovered, that would amount to around 182 hours per year.

If it were one hour, it would be 365.

But we should not call those hours “recovered productivity.”

Perhaps they are football.

Sleep.

Silence.

Forest.

Music.

Sex.

Friendship.

Play.

Research.

Or absolutely nothing.

And perhaps it is precisely from this unrecruited time that worlds no algorithm could have predicted may emerge.

BrainLatam already proposes a protected public AI for every Body-Territory and a First-Person Consciousness in which knowledge produced about a person's trajectory returns primarily to that person. (brainlatam.com)

Perhaps now we can define its purpose more clearly:

Personal AI does not exist to fill the future of the Body-Territory. It exists to remove obstacles, return knowledge, and protect enough time for that Body-Territory to continue inventing futures that no one — not even the AI — had imagined.

Commented References

UNDP — United Nations Development Programme. (2025). Human Development Report 2025: A Matter of Choice — People and Possibilities in the Age of AI.
Places choice, freedom, and human capability at the center of development in the age of AI. It supports our distinction between using AI to maximize measurable behavior and using it to expand possibilities chosen by the Body-Territory itself. (hdr.undp.org)

DataReportal / GWI. (2025). Digital 2025: Global Overview Report.
Reports a global average of 2h21 per day on social media among surveyed users and shows that “filling spare time” is an important motivation. The statistic does not justify calling all that time wasted; here it serves to show the scale of time already taking place inside digital systems. (datareportal.com)

BrainLatam. (2026). “Do sequestro atencional à presença compartilhada”.
Develops the BrainLatam hypothesis of attentional hijacking as a progressive narrowing of the attentional field and bodily participation that can occur before a fully conscious emotional state is identified. It provides the conceptual basis for asking how Personal AI could protect, rather than capture, the attentional channel. (brainlatam.com)

World Health Organization. (2024). “Gambling”.
Estimates gambling disorder at approximately 1.2% of the world's adult population and discusses prevention mechanisms such as binding time and spending limits, pauses, and self-exclusion. It supports the possibility of technologies that reinforce self-chosen limits without replacing treatment or personal autonomy. (who.int)

Farhood, H.; Nyden, M.; Beheshti, A.; et al. (2025). “Artificial intelligence-based personalised learning in education: a systematic literature review”. Discover Artificial Intelligence, 5, 331.
A review of 125 studies on AI-based educational personalization. It shows opportunities for adaptive learning, but also challenges related to privacy, implementation, and system design. It supports using grades as signals for investigating trajectories, not as definitive identities. (link.springer.com)

OECD. (2025). Government at a Glance 2025; “Administrative simplification”.
The OECD describes the costs and stress created by complex administrative processes and advocates for services that are more integrated, accessible, and user-centered. It supports our question about how much human time could stop being recruited by bureaucracy. (oecd.org)

OECD. (2025). AI and the Future of Social Protection in OECD Countries.
Discusses AI in citizen support, administrative processes, risk detection, and outreach in social protection, while warning about trust, transparency, and risks of dehumanization. It is a reference for the BrainLatam principle of Rights Before Request, not a description of a system already implemented in this form. (oecd.org)

Brazilian Ministry of Health — Rede Nacional de Dados em Saúde (RNDS).
RNDS is currently Brazil's official infrastructure for health-data interoperability and allows citizens to consult records through Meu SUS Digital. Personal AI universally mediating wearables, private examinations, and SUS is a future BrainLatam proposition, not a current RNDS feature. (gov.br)

Brazil. Law No. 13,709/2018 — General Data Protection Law (LGPD).
Defines health information and genetic or biometric data linked to a person as sensitive personal data. This provides an essential constraint on the proposal: continuity of information cannot mean unrestricted access by the State or private companies. (planalto.gov.br)

Brazilian Digital Government — National Identity Card and biometrics.
Brazil already uses facial images, fingerprints, and digital identity in parts of its identification infrastructure. The concept of Body-Territory as the root of identity goes beyond the current system and presupposes alternative authentication methods and protection against biometric failures. (gov.br)

Lopez, K. L.; Monachino, A. D.; Vincent, K. M.; et al. (2023). “Stability, change, and reliable individual differences in electroencephalography measures”. NeuroImage, 275, 120116.
Reviews stability, internal consistency, and test-retest reliability of EEG measures. It shows why personal baselines are scientifically useful only when changes in the individual can be distinguished from variability and measurement noise. (pubmed.ncbi.nlm.nih.gov)

Sinfield, V. C.; Aaker, D.; Metzger, A.; et al. (2025). “Intra-subject test-retest reliability for auditory-evoked functional near-infrared spectroscopy responses”. Neurophotonics, 12(1), 015015.
Shows how systemic physiology and different correction procedures can alter fNIRS reliability within the same individual. It reinforces that no isolated signal should directly define capacity, identity, or future. (pubmed.ncbi.nlm.nih.gov)

Fraza, C.; Rutherford, S.; Rehák Bučková, B.; Beckmann, C. F.; Marquand, A. F. (2025). “The promise of quantifying individual risk for brain disorders through normative modeling”. Neuroscience & Biobehavioral Reviews, 176, 106284.
Shows the usefulness of normative models for understanding individual heterogeneity, while emphasizing the insufficiency of cross-sectional models for representing trajectories over time. It supports our transition from “outside the average” to “changed relative to one's own history.” (sciencedirect.com)

Mallus, F. A.; Yang, Y.; Dinga, R.; et al. (2026). “From early to contemporary normative modeling: Mapping individual differences in neurophysiological signals”. Imaging Neuroscience, 4.
Reviews normative modeling specifically in EEG/MEG and describes the shift from population averages toward individualized estimates, highlighting challenges in standardization, harmonization, and interpretation. (pmc.ncbi.nlm.nih.gov)

BrainLatam. (2023–2026). “First Person Consciousness” and “Estamos preparando nossos filhos para qual futuro?”.
These texts develop First-Person Consciousness and propose a protected public AI for every Body-Territory. The present Blog adds an explicit value function: data return, reduced bureaucracy, protection from attentional capture, and the return of unrecruited time so that each Body-Territory can produce possibilities that do not yet exist. (brainlatam.com)