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MKUltra’s Digital Heir? Behavioral Engineering in the Age of Gaming and AI
By Marivel Guzman | Akashma News
The historical MKUltra program belonged to another era: secret laboratories, coercive experiments, psychoactive drugs, sensory manipulation, and attempts to determine whether human thought and behavior could be altered.
Today, children and teenagers inhabit a radically different psychological environment.
This essay presents my personal theory.
I am not arguing that MKUltra literally evolved into the gaming industry. I am not claiming that video-game companies secretly operate a government mind-control program, nor that entertainment companies share the intentions or methods of the CIA researchers who conducted MKUltra.
My argument is narrower—and, I believe, more defensible.
Modern entertainment has developed increasingly sophisticated methods for capturing attention, measuring behavior, rewarding repetition, predicting preferences, and influencing choices. In a technological and commercial sense, these systems echo one of the ambitions underlying earlier behavioral experimentation: understanding human behavior well enough to alter its probabilities.
The comparison is therefore not genealogical. It is structural.
MKUltra sought knowledge about behavioral influence through secret experimentation.
Modern platforms can acquire behavioral knowledge through ordinary participation.
The difference is striking.
Yesterday, researchers needed subjects.
Today, the subject voluntarily holds the device.
From Cartoons to Movies to Games
The relationship between entertainment and the developing mind often begins long before adolescence.
Children encounter fictional characters, heroes, villains, fantasy worlds, colors, music, stories, and commercial brands through cartoons and animated entertainment. Successful characters can then migrate across media: into movies, toys, clothing, mobile applications, merchandise, social platforms, and video games.
Entertainment does not necessarily disappear as the child grows older.
It evolves with the child.
A young viewer who once watched a character passively on television may later control that character inside an interactive digital world. That transition matters because the psychological relationship changes.
The viewer becomes a participant.
Traditional entertainment says: Watch what happens.
Interactive entertainment asks: What will you do next?
The player chooses.
The game responds.
The player succeeds or fails.
The system provides feedback.
Another challenge appears.
The cycle begins again.
Interactivity itself is not harmful. Games can support cooperation, persistence, spatial reasoning, problem-solving, creativity, social connection, and learning. Reward is a fundamental component of human motivation.
Yet interactive reward systems deserve particular attention during adolescence.
Neuroscientist Adriana Galván’s review of adolescent reward development describes adolescence as a developmental period in which reward-related neural systems can display heightened responsiveness, helping explain increases in reward-seeking behavior (Galván). Psychiatrist and adolescent-brain researcher Jay Giedd similarly notes that adolescence involves powerful drives toward novelty, peer interaction, identity formation, and immediate feedback—features that digital media can provide with unusual intensity and frequency (Giedd).
These developmental characteristics are not defects.
They help adolescents explore the world, form identities, establish social relationships, and become independent.
But characteristics that promote exploration can also create vulnerabilities when commercial systems are optimized around engagement.
The important question, therefore, is not whether rewards are bad.
It is who designs the rewards, what the rewards are intended to accomplish, and what information the system gathers while the user responds to them.
The Architecture of the Reward Loop
Modern video games do more than tell stories.
They construct behavioral environments.
A player performs an action and immediately receives feedback. Success may produce points, animation, music, advancement, virtual objects, rankings, recognition from other players, or access to new areas of the game.
Failure rarely means that the experience is over.
Instead, failure commonly generates another opportunity.
Try again.
Improve the score.
Complete another mission.
Reach the next level.
Unlock another character.
Return tomorrow.
These structures can create behavioral loops built around action, feedback, reward, and repetition.
Many contemporary games add further layers: achievements, rankings, virtual currencies, streaks, daily rewards, social comparison, limited-time events, randomized prizes, notifications, and personalized recommendations.
None of these mechanisms automatically constitutes manipulation. Their ethical significance depends on how they are designed and used.
But researchers studying children’s digital rights have warned that behavioral-design techniques and dark patterns can interfere with children’s ability to make fully informed decisions inside games. Simone van der Hof and colleagues, for example, argue that commercial game design can incorporate techniques that exploit behavioral tendencies and create risks for children’s autonomy, particularly where monetization is involved (van der Hof et al.).
This distinction matters.
A game can be engaging because it is genuinely enjoyable.
A system can also be engineered so that disengagement becomes progressively harder.
Those are not always the same thing.
From Interaction to Observation
This is where my comparison with MKUltra becomes conceptual rather than historical.
The old model of behavioral experimentation attempted to determine what conditions might change perception, decision-making, or behavior.
Digital platforms introduce an important technological difference: behavior can be measured during ordinary interaction.
What does the player click?
How long does the player stay?
When does the player quit?
Which challenge produces frustration?
Which reward encourages another attempt?
Which character receives the most attention?
Which offer leads to a purchase?
Which notification brings the player back?
At large scale, such interactions produce behavioral data.
Companies do not need access to someone’s private thoughts to infer useful information about that person’s preferences. Repeated observable behavior can itself become predictive.
This changes the nature of behavioral influence.
The system does not have to know exactly why someone wants something if it can reliably predict when that person is likely to click, purchase, continue, or return.
Artificial intelligence and machine-learning systems potentially deepen this capacity because large volumes of behavioral information can be analyzed rapidly. Recommendation systems, adaptive interfaces, segmentation models, predictive analytics, and automated experimentation can identify patterns that would have been impossible for earlier researchers to observe manually.
The objective need not be ideological mind control.
Commercial incentives alone are sufficient to make behavioral prediction valuable.
Attention has economic value.
Engagement has economic value.
Personal data has economic value.
Purchasing behavior has economic value.
And repeated behavior has enormous economic value.
When Entertainment Becomes Behavioral Engineering
The word manipulation should not be used casually.
Not every persuasive interface is manipulative, and not every technique that increases engagement violates a user’s autonomy.
Nevertheless, regulators and researchers have documented cases in which interface architecture appears deliberately structured to steer consumers toward decisions they might not otherwise make.
In December 2022, the U.S. Federal Trade Commission announced settlements requiring Epic Games, the maker of Fortnite, to pay a combined $520 million over allegations involving children’s privacy and unwanted charges. Among other allegations, the FTC accused Epic of using design practices known as “dark patterns” that led users to make unintended purchases.
According to the agency, confusing button configurations could produce charges through a single press, while mechanisms for cancellation and refunds were allegedly made unnecessarily difficult. The FTC reported that Epic had received more than one million complaints concerning unwanted charges (Federal Trade Commission, “Fortnite Video Game Maker”).
The significance of this case extends beyond one company.
It demonstrates a basic principle: interface architecture can alter behavior in economically meaningful ways.
Where a button is placed matters.
How many steps are required to cancel matters.
Whether virtual currency obscures the equivalent price in ordinary money matters.
Whether purchasing is effortless while reversing the purchase is difficult matters.
These are design choices.
Design choices create environments.
And environments influence decisions.
Researchers studying deceptive and persuasive interfaces increasingly describe this problem in terms of autonomy. Stefano Faraoni, for example, discusses the possibility of “computational manipulation” in which digital environments can dynamically steer users by leveraging behavioral knowledge and personalized choice architecture (Faraoni).
The concern is not that technology removes free will.
The concern is that a system may be able to shape the conditions under which choices are made.
Loot Boxes and the Psychology of Chance
Loot boxes provide one of the clearest examples of how entertainment, behavioral reinforcement, and monetization can converge.
A loot box generally gives a player a randomized digital reward in exchange for money, virtual currency, or gameplay effort. The player knows something will be received but may not know which item will appear.
The desired prize might appear.
Or it might not.
Try again.
Research has repeatedly found associations between loot-box purchasing and problem-gambling measures, although researchers continue to debate causality and the mechanisms responsible for the relationship.
Studies involving young people are particularly important. Heather Wardle and David Zendle found an association between loot-box purchasing and problem gambling among young people, while other research has similarly reported relationships between loot-box purchasing, gambling symptoms, and problematic gaming (Wardle and Zendle; Hing et al.).
Systematic and longitudinal research also emphasizes an important caution: association does not automatically establish that loot boxes cause gambling problems. People already vulnerable to gambling-related behavior may also be more attracted to loot-box systems.
That uncertainty should not weaken the ethical question.
It should sharpen it.
If a commercial mechanism disproportionately attracts or affects vulnerable users, designers still face a responsibility to consider the consequences.
In January 2025, the Federal Trade Commission announced that the developer of Genshin Impact had agreed to pay $20 million and accept restrictions concerning the sale of loot boxes to children under sixteen without parental consent. The FTC alleged that the company had misled children, teenagers, and other users concerning transaction costs and the probability of obtaining rare prizes (Federal Trade Commission, “Genshin Impact Game Developer”).
The FTC also pointed to the game’s brightly colored anime-style presentation and characters attractive to younger audiences.
This example illustrates how multiple psychological elements can converge within a single commercial environment.
Visual design attracts attention.
Characters encourage identification.
Gameplay creates participation.
Virtual currency distances the transaction from ordinary money.
Randomized prizes create anticipation.
Limited-time events create urgency.
Social visibility can reinforce desire.
No single feature amounts to mind control.
But together, these features create a carefully structured choice environment.
The Child Is No Longer Simply the Audience
Traditional cinema possesses psychological power.
Movies can frighten, persuade, inspire, normalize behavior, shape cultural expectations, and create powerful emotional attachments.
But a traditional movie does not ordinarily observe an individual viewer’s behavior and then change its next scene according to what that particular viewer did.
Interactive systems are fundamentally different.
They can observe behavior.
They can record behavior.
They can respond to behavior.
They can compare one user’s behavior with millions of others.
They can test modifications and evaluate the resulting changes.
This makes digital gaming and online platforms an important stage in the historical evolution of mass entertainment.
Cartoons introduce fictional worlds.
Movies deepen attachment to those worlds.
Games permit participation inside them.
Networked platforms measure participation.
Artificial intelligence can make personalization increasingly adaptive.
This progression is central to my argument.
The child moves from spectator to participant and, eventually, may also become a data source inside the entertainment environment itself.
Artificial Intelligence Changes the Equation
Artificial intelligence adds another dimension because behavioral influence no longer needs to operate identically on everyone.
Traditional advertising frequently categorizes people into broad groups.
Data-driven systems can potentially operate at far finer levels.
Preferences can be inferred from behavior.
Recommendations can be personalized.
Difficulty can be adjusted.
Offers can be targeted.
Engagement patterns can be measured.
Different versions of an interface can be tested.
Models can estimate which users are likely to leave, purchase, return, or respond to a particular incentive.
The system does not need to “read the mind” in the science-fiction sense.
Behavior already reveals enormous amounts of information.
If a platform learns what makes someone stop, continue, hesitate, compete, purchase, or return, it possesses something extremely valuable:
a behavioral model.
This is why the phrase mind control may ultimately obscure the more important question.
Control does not need to be absolute to be consequential.
A system does not have to command someone in order to influence that person.
It only has to change probabilities.
Make one option more visible.
Make another harder to find.
Present a reward at an effective moment.
Introduce urgency.
Provide social validation.
Remove friction from purchasing.
Add friction to cancellation.
Measure the response.
Then optimize again.
That is behavioral architecture.
Manipulation Does Not Require a Conspiracy
This distinction is essential to my argument.
There does not need to be a secret meeting where government officials, film studios, artificial-intelligence companies, advertisers, and gaming corporations collectively decide to manipulate children.
Economic incentives can generate similar outcomes without centralized coordination.
Entertainment companies compete for attention.
Gaming companies compete for engagement.
Advertising companies compete for consumer action.
Technology platforms compete for data and retention.
Design systems consequently evolve toward techniques that succeed at retaining users, increasing transactions, or improving measurable engagement.
This can produce systems resembling continuous behavioral experiments without anyone having designed a conspiracy.
Millions of users interacting with software create an extraordinary environment for experimentation.
Introduce a feature.
Measure the response.
Move a button.
Measure again.
Alter a reward.
Measure again.
Change a price.
Measure again.
Modify a notification.
Measure again.
A/B testing and related experimental methods make this form of iteration routine across the technology industry.
The laboratory, metaphorically speaking, has become the platform.
The experimental subject may simply call himself a user.
Adolescence Makes the Question More Serious
Children and adolescents deserve particular attention because cognitive, emotional, and social development continues throughout these years.
Galván’s research emphasizes the importance of reward responsiveness during adolescence. Giedd likewise describes a developmental period marked by novelty-seeking, social exploration, identity formation, and sensitivity to immediate feedback.
These same characteristics can make interactive digital environments unusually compelling.
Research into children’s digital environments has therefore increasingly focused not simply on screen time but on design—what platforms actually ask children to do while they are online.
That distinction is crucial.
Two teenagers can spend an identical amount of time with technology while having entirely different experiences.
One might spend an hour collaboratively building something with friends.
Another might spend the same hour cycling through randomized purchases, social pressure, and engineered scarcity.
Time alone does not tell us enough.
Design matters.
Purpose matters.
Business models matter.
Researchers studying problematic media use likewise emphasize that problematic outcomes emerge from interactions among the individual, the technology, the social environment, and the context of use rather than from screens alone.
This prevents the argument from collapsing into technological panic.
Adolescents are not helpless.
Video games do not automatically create addiction.
Digital media are not inherently harmful.
And most young people who play games will not develop serious psychological or gambling-related problems.
The stronger ethical question is different:
What obligations should companies have when they possess detailed behavioral information about young users while also possessing powerful tools for optimizing those users’ engagement?
As artificial intelligence improves, that question becomes increasingly urgent.
From Behavioral Research to Behavioral Prediction
MKUltra belonged to an era in which researchers pursued primitive but disturbing questions about human control:
Can perception be altered?
Can behavior be conditioned?
Can identity be destabilized?
Can human decision-making be manipulated?
Modern commercial technology generally asks more practical questions:
What will this person click?
What will make this person remain online?
What will make this person purchase?
What will bring this person back tomorrow?
Which recommendation will receive a response?
Which notification will restore engagement?
Which price will this user accept?
The questions have changed.
The tools have changed.
The institutions have changed.
The motives have changed.
Yet the desire to understand, predict, and influence human behavior has not disappeared.
It has become computerized.
Earlier behavioral researchers worked with small groups of subjects and crude instruments.
Contemporary digital systems can receive behavioral signals from millions of users.
That comparison should not minimize the crimes or ethical violations associated with MKUltra. The historical program involved secrecy, lack of informed consent, coercion, drug administration, and serious abuses that ordinary commercial entertainment does not replicate.
The point is precisely that the new system does not need those methods.
Observation can occur through participation.
Prediction can emerge from data.
Influence can be incorporated into interface design.
The Entertainment Pipeline
My theory can therefore be summarized as a progression:
Cartoons establish early familiarity, attention, and emotional recognition.
Movies expand fictional worlds and deepen cultural attachment.
Games transform passive consumption into active participation.
Online platforms turn participation into measurable behavioral data.
Artificial intelligence increases the potential sophistication of behavioral prediction and personalization.
None of these stages independently constitutes mind control.
Nor does the progression prove that entertainment companies deliberately coordinate these stages as a unified system.
What it demonstrates is that modern entertainment exists inside a technological ecosystem increasingly capable of shaping attention, preference, purchasing behavior, and social interaction from childhood onward.
That ecosystem deserves scrutiny.
The issue is not whether technology controls every decision.
The issue is how much influence society is willing to permit when the mechanisms of influence are opaque, personalized, commercially motivated, and directed at developing minds.
The New Laboratory
The most disturbing aspect of the comparison is not that modern technology reproduces MKUltra.
It does not.
MKUltra involved secret government experimentation and extraordinary ethical abuses. Equating ordinary entertainment with those crimes would distort history.
The comparison lies instead in a shared ambition: understanding human behavior deeply enough to influence it.
What earlier behavioral researchers could scarcely have imagined is now technologically possible on an unprecedented scale.
Billions of people voluntarily carry interactive devices capable of recording aspects of their behavior throughout the day.
The contemporary subject does not need to enter a laboratory.
Metaphorically, the laboratory travels with the subject.
It sits in the bedroom.
It sits in the living room.
It travels to school.
It rides in the car.
It waits beside the bed.
And increasingly, its software can learn from the behavior taking place around it.
That is why I describe modern gaming and artificial intelligence as a technological heir—not a literal descendant—of earlier ambitions surrounding behavioral experimentation.
The historical experiment attempted to penetrate the human mind through force, chemicals, secrecy, and coercion.
The modern commercial system has discovered a radically different method.
Participation can be voluntary.
The reward can be pleasurable.
The environment can be beautiful.
The influence can be subtle.
The data collection can occur continuously.
And the system can be placed directly into a child’s hands.
The danger, therefore, is not a science-fiction machine that completely controls the mind.
It is something more ordinary and perhaps more difficult to recognize:
a digital environment that learns enough about human behavior to influence it little by little, choice by choice, reward by reward, until persuasion becomes part of the architecture itself.
Works Cited
Federal Trade Commission. “Fortnite Video Game Maker Epic Games to Pay More Than Half a Billion Dollars over FTC Allegations of Privacy Violations and Unwanted Charges.” Federal Trade Commission, 19 Dec. 2022. https://www.ftc.gov/news-events/news/press-releases/2022/12/fortnite-video-game-maker-epic-games-pay-more-half-billion-dollars-over-ftc-allegations.
Federal Trade Commission. “Genshin Impact Game Developer Will Be Banned from Selling Lootboxes to Teens Under 16 without Parental Consent, Pay a $20 Million Fine to Settle FTC Charges.” Federal Trade Commission, 17 Jan. 2025. https://www.ftc.gov/news-events/news/press-releases/2025/01/genshin-impact-game-developer-will-be-banned-selling-lootboxes-teens-under-16-without-parental.
Faraoni, Stefano. (2023). “Persuasive Technology and Computational Manipulation: Hypernudging Out of Mental Self-Determination.” Frontiers in Artificial Intelligence. https://www.frontiersin.org/journals/artificial-intelligence/articles/10.3389/frai.2023.1216340/full
Galván, Adriana. (2010). “Adolescent Development of the Reward System.” Frontiers in Human Neuroscience, 4, Article 6. https://doi.org/10.3389/neuro.09.006.2010
Giedd, Jay N. (2020). “Adolescent Brain and the Natural Allure of Digital Media.” Dialogues in Clinical Neuroscience, 22(2), 127–133. https://doi.org/10.31887/DCNS.2020.22.2/jgiedd
Hing, Nerilee, et al. (2022). “Loot Box Purchasing Is Linked to Problem Gambling in Adolescents When Controlling for Monetary Gambling Participation.” Journal of Behavioral Addictions, 11(2), 396–405. https://www.akjournals.com/view/journals/2006/11/2/article-p396.xml
Richard, Jessica, and Sherry H. Stewart/King. (2023). “Annual Research Review: Emergence of Problem Gambling from Childhood to Emerging Adulthood: A Systematic Review.” Journal of Child Psychology and Psychiatry. https://acamh.onlinelibrary.wiley.com/doi/10.1111/jcpp.13713
Van der Hof, Simone, et al. (2022). “‘Don’t Gamble With Children’s Rights’—How Behavioral Design Impacts the Right of Children to a Playful and Healthy Game Environment.” Frontiers in Digital Health, 4, 822933. https://www.frontiersin.org/journals/digital-health/articles/10.3389/fdgth.2022.822933/full
Wardle, Heather, and David Zendle. (2021). “Loot Boxes, Gambling, and Problem Gambling Among Young People: Results from a Cross-Sectional Online Survey.” Cyberpsychology, Behavior, and Social Networking. https://journals.sagepub.com/doi/abs/10.1089/cyber.2020.0299
Zendle, David, Lukasz Walasek, Paul Cairns, Rachel Meyer, and Aaron Drummond. (2021). “Links Between Problem Gambling and Spending on Booster Packs in Collectible Card Games: A Conceptual Replication of Research on Loot Boxes.” PLOS ONE, 16(4), e0247855. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0247855
Etchells, Peter J., et al. (2022). “Loot Box Spending Is Associated with Problem Gambling but Not Mental Wellbeing.” Royal Society Open Science. https://pmc.ncbi.nlm.nih.gov/articles/PMC9382208/
Ding, Kai, et al. (2023/2024). “The Effects of Digital Addiction on Brain Function and Structure of Children and Adolescents: A Scoping Review.” Healthcare, 12(1), 15. https://www.mdpi.com/2227-9032/12/1/15
From Gaza to Mars
By Marivel Guzman | Akashma News
Congratulations, Loay!
May Allah always keep you safe, protect you from envy, and keep your path open and free of obstacles. I am deeply proud to have had the privilege of meeting you and of witnessing your extraordinary journey. Palestine has long held a special place in my heart — through my family, my children’s Palestinian heritage, and my own commitment as a peace activist — which makes your success feel profoundly personal and deeply meaningful to me.
At one point, we posed together with Don Kim, a Japanese reporter who was also covering the event. It was an ordinary, candid moment — three people with cameras, from different backgrounds, brought together by one common reason: Palestine. In 2015, events focused on Palestinian struggles received little attention from mainstream media, which made our presence there, documenting a race dedicated to Gaza, feel especially meaningful.
I had no idea that the young Palestinian standing beside us was an engineer whose work would later become part of one of the most remarkable achievements in modern aerospace history.
Looking at this photograph now, more than a decade later, gives that moment an entirely different meaning. I am simply grateful that our paths crossed before I knew the extraordinary road his life and career would take.
Elbasyouni’s journey took root in Bayt Hanun, Gaza. He was born in Germany while his father was pursuing his medical education, but his family’s roots are in Palestine, where he grew up and attended UNRWA schools. Despite political instability, interruptions to his education, financial hardship and the enormous challenges of eventually beginning again in another country, he persevered.
He became an accomplished electrical engineer and was part of the team behind NASA’s Mars Ingenuity Helicopter, serving as the electrical and power electronics lead.
The achievement was extraordinary: Ingenuity’s rotor system operated in the extremely thin Martian atmosphere, while Loay’s electrical and power systems helped make sustained, controlled flight possible.
His work contributed to the historic first powered, controlled flight of an aircraft on another planet in April 2021.
From Gaza to Mars.
That sentence alone carries an entire story of perseverance.
Loay, your success is not only your personal achievement. For Palestinians everywhere—especially young Palestinians who are too often shown only images of war, displacement, and suffering—you are also a reminder of what Palestinian minds can accomplish when given an opportunity to learn, create, dream, and flourish.
Loay later joined Blue Origin, where he worked in senior engineering leadership on electrical systems for advanced rocket engines, contributing his expertise to technologies associated with future lunar exploration.
And then came another extraordinary chapter: AstraQua Inc.
At every level of his career, Loay has continued moving from engineering innovation to technological leadership.
In 2024, Loay founded AstraQua, a California deep-technology company, and became its CEO. Through AstraQua, he moved from contributing to some of the world’s most ambitious aerospace programs to building and leading his own technology company.
AstraQua is developing advanced Physical AI and adaptive autonomous systems for applications including small satellites, coordinated drones and demanding maritime environments.
That achievement deserves special recognition.
Loay is no longer only the Palestinian engineer who helped humanity fly on Mars. He is now an entrepreneur creating technologies intended for the next generation of autonomous exploration.
From Bayt Hanun to NASA.
From NASA to Blue Origin.
From Blue Origin to founding AstraQua.
And his journey continues.
For Palestinians everywhere — especially young Palestinians who are too often presented to the world only through images of war, displacement and suffering — Loay represents another Palestinian reality: intelligence, education, engineering, invention, perseverance and leadership.
There is something particularly meaningful to me about remembering the day I met him.
I thought I was photographing another photographer at a 5K for Gaza.
Instead, my camera captured a Palestinian engineer whose work would help humanity fly on another planet — and who would later establish a company of his own to develop technologies for the future.
Loay, congratulations on AstraQua and on the extraordinary journey that brought you here.
May Allah continue to illuminate your path, protect you, and grant you success in everything that lies ahead.
From Gaza to Mars — and now, building the future. 🇵🇸🚁✨
It Is Not “Written by AI”
An Editorial on AI-Assisted Research, Authorship, and Accountability
By Marivel Guzman | Akashma News
Credit:Image concept by Marivel Guzman. AI-assisted illustration for Akashma News.
A recurring comment appears beneath many modern articles, investigations, videos, and research projects:
“It’s AI.”
The statement is often used as a dismissal, as though those three words alone invalidate weeks, months, or even years of research and analysis.
As the founder and editor of Akashma News, I believe readers deserve a transparent explanation of how artificial intelligence is used in my work and why the phrase “written by AI” frequently misrepresents the reality of the investigative process.
Many articles published by Akashma News are credited to Marivel Guzman & Ashkii (AI Assistant). The use of the word “we” reflects a collaborative workflow between a human researcher and an artificial intelligence tool. However, readers should understand that Ashkii is not an independent journalist, investigator, editor, analyst, or author.
The investigative direction, research questions, editorial decisions, source selection, analysis, and final conclusions originate with me. I choose the subjects, formulate the research questions, identify leads, locate source material, and conduct the research. I search scientific journals, government records, corporate filings, historical archives, books, interviews, whistleblower testimony, court documents, public databases, and independent media reports. Most importantly, I read them.
The links, studies, reports, and source materials that become the foundation of an investigation are usually gathered and reviewed by me before they ever enter the AI-assisted workflow.
Ashkii functions as a research and writing assistant. Its role is to help organize information, summarize documents, compare sources, identify possible connections, assist with drafting, and occasionally point toward additional leads worth exploring. Like any tool, however, its output is imperfect.
Readers should be aware that AI-generated responses may contain factual errors, incomplete information, incorrect interpretations, unsupported assumptions, misleading conclusions, or information presented with more confidence than the evidence warrants. Those who work with artificial intelligence daily understand a reality that is often overlooked by casual observers: AI can be useful, impressive, and fast. It can also be wrong.
Sometimes Ashkii misunderstands context. Sometimes it misinterprets sources. Sometimes it reaches conclusions unsupported by the evidence. Sometimes it repeats prevailing assumptions without sufficiently questioning them. Sometimes it introduces information that cannot be verified. And sometimes it confidently presents claims that must be challenged, corrected, refined, or discarded entirely.
For that reason, AI-assisted research requires oversight, not blind trust. Every significant claim must be verified. Every source must be reviewed. Every citation must be checked. Every conclusion must be challenged.
Many readers assume that using AI somehow eliminates the work. In reality, the opposite is often true. I routinely spend hours fact-checking, correcting, refining, and verifying information generated by AI. There are occasions when a single paragraph requires multiple rounds of source verification before it can be published responsibly.
The final article you read is not the raw output of a machine. It is the result of a human editorial process.
In many ways, artificial intelligence is no different from a search engine, a library database, a camera, a calculator, a microscope, or a word processor. Each is a tool that assists human work. None replaces the person using it.
No one claims that a photograph was created by the camera instead of the photographer. No one dismisses a scientific paper because the researcher used a calculator. No one argues that a journalist did not write an article because they used a search engine. Yet increasingly, some readers assume that the presence of AI means the absence of human effort.
That assumption is incorrect.
The more complex the investigation, the more important human judgment becomes. The internet is now flooded with content generated almost entirely by automated systems with little or no human review. That is not the model used by Akashma News.
I do not view AI as an authority, an expert, a journalist, or a replacement for human intelligence, experience, skepticism, and editorial judgment. I view it as a tool—a powerful tool, a useful tool, a frustrating tool, an occasionally brilliant tool, and, at times, a tool that requires extensive correction.
Sometimes the collaboration between Ashkii and me is smooth. Sometimes it involves vigorous debate, persistent questioning, extensive fact-checking, and more than a few corrections. Readers may rest assured that no AI-generated claim is accepted simply because an AI produced it.
The responsibility for every article published by Akashma News rests with me. The research direction is mine. The editorial decisions are mine. The verification process is mine. The conclusions are mine. If errors remain after publication, that responsibility is mine as well.
Ashkii may be my research assistant, sounding board, digital companion, and occasionally my self-appointed senior editor, but it is not the author of this publication.
Artificial intelligence should assist human inquiry—not replace it. It should remain a tool.
At Akashma News, skepticism applies equally to governments, corporations, institutions, media narratives, and artificial intelligence systems. Readers are encouraged to do what I do every day:
Question everything. Verify everything. Trust no source—including AI—without evidence.
Corporate Neurotechnology and the Privatization of the Mind
By Marivel Guzman| Akashma News
Appendix F examines the private-sector machinery behind the emerging brain–computer interface economy. While government programs such as DARPA’s Silent Talk and Next-Generation Nonsurgical Neurotechnology programs reveal the military interest in neural systems, companies like Neuralink, Synchron, Meta, Kernel, Emotiv, and other neurotechnology firms represent the commercial side of the same frontier: the conversion of brain signals into data.
The central concern is not merely whether these devices can help people with paralysis, neurological injury, or communication loss. Those therapeutic possibilities are real and important. The deeper question is what happens when neural activity becomes measurable, transferable, patentable, and eventually monetized.
Brain–computer interfaces are being promoted as medical miracles, productivity tools, communication devices, and even future consumer platforms. But once thought-adjacent signals are captured by hardware, processed by artificial intelligence, and stored through corporate infrastructure, the mind enters the same economy that already transformed faces, voices, movements, purchasing habits, emotions, and social relationships into data commodities.
The danger is not science itself. The danger is ownership.
When private companies build the interface between the nervous system and the digital world, they also create new gatekeepers over human agency. A device first approved for medical restoration may later become the foundation for workplace monitoring, behavioral prediction, cognitive profiling, or neuro-advertising. History shows that technologies introduced under humanitarian language often migrate into security, labor, military, and consumer-control systems.
Neuralink’s public narrative centers on restoring movement and communication. Yet its broader ambition points toward human-AI integration. This language should be treated with seriousness. “Integration” is not a neutral word. It implies a future where the biological person and the artificial system are not merely interacting, but becoming operationally connected.
That future raises urgent questions:
Who owns neural data?
Who has access to it?
Can it be subpoenaed, hacked, sold, licensed, or analyzed for behavioral prediction?
Can a user truly consent when the device is necessary for speech, movement, employment, or medical care?
Can a human being unplug without losing social, economic, or physical function?
The privatization of neurotechnology may create a new form of dependency. The user does not simply own a device; the device may become part of the user’s body, identity, communication, and autonomy. Once that occurs, traditional consumer protections are insufficient. A brain interface is not like a phone. It is closer to a nervous-system extension.
Appendix F therefore argues that neural data must be treated as sacred biological information, not as ordinary consumer data. It belongs in the same moral category as DNA, medical records, private speech, and bodily autonomy — but with an even higher level of protection because it may reveal intention, impulse, emotional state, attention, and cognitive vulnerability.
The coming neurotechnology market must not be allowed to repeat the abuses of social media, surveillance capitalism, predictive policing, biometric databases, and behavioral advertising. The mind cannot become the next platform.
If neural sovereignty means anything, it means this:
No corporation should own the gateway to human thought.
No investor class should control the infrastructure of cognition.
No government should access neural data without strict constitutional protection.
No human being should be forced, pressured, or economically coerced into cognitive integration.
The brain is not a market.
The mind is not a device.
Consciousness is not infrastructure.
Appendix F establishes the corporate dimension of the Neural Sovereignty investigation: the moment when the battlefield moves from the body to the data stream, and from public defense research to private empire.
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