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Scan for outdated or missing drivers - takes under a minuteDriver Scan →Clear out junk files and repair common Windows errorsFree Scan →Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →Sociologist Tressie McMillan Cottom’s warning is about who gets to shape an AI-driven future—not proof that billionaires have a coordinated plan to control humanity. A December 21, 2025, Futurism article by Joe Wilkins reports remarks Cottom made at an Urban Consulate panel in Detroit. Its headline’s claim that the wealthy are trying to “seize control of everything” is a forceful interpretation, not an allegation the article substantiates with evidence of a unified scheme.
Who made the warning, and where?
Tressie McMillan Cottom is a sociologist. The remarks at issue were made during an Urban Consulate panel in Detroit featuring Cottom and writer Jason Reynolds, according to Futurism’s account. The report was published on December 21, 2025. This was a public discussion, not a newly published academic study.
Futurism includes a link to the panel video: the Urban Consulate discussion on YouTube. The exact video title, date, and full context are not established here, so the article’s account is the basis for describing what Cottom said.
What Cottom was arguing
As reported by Futurism, Cottom challenged the idea that society’s future is already settled simply because powerful people describe AI’s advance as inevitable. She argued that wealthy and influential actors may benefit when people accept that framing: resignation can make a future that could be debated or resisted seem like a fait accompli.
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Her concern is political as much as technological. AI systems do not need independent intentions to affect people’s lives. The consequential questions are who owns them, who chooses where they are used, who captures the gains, and who has recourse when they cause harm. Futurism also reports Cottom’s description of a “post-human” future as one in which humans remain but are treated inhumanely—not necessarily a prediction that people will go extinct.
She presents refusal as a source of hope: people need not accept claims that the future has already been decided. That is a call to preserve political agency, not evidence that a particular outcome is guaranteed.
What “seizing control” could mean in practice
The headline’s phrase is broad. It can be translated into concrete areas of power, but these are analytical categories, not findings demonstrated individually by the panel remarks.
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- Ownership: Control over models, cloud computing, chips, data, and distribution can give a limited set of firms influence over which systems are available and on what terms.
- Work: Employers may use AI to allocate tasks, monitor workers, assess performance, or reorganize jobs. Whether that shifts bargaining power depends on how the tools are deployed and what workers can contest.
- Information: AI can shape what people encounter through search, recommendations, news production, education, and other information channels.
- Administration and surveillance: Governments and companies may use automated systems for scoring, identity checks, prediction, or monitoring. The stakes include transparency, privacy, and the ability to challenge a decision.
- Institutional dependence: When organizations rely on private AI infrastructure they cannot meaningfully govern or replace, vendors may gain leverage over essential services.
- Agenda-setting: Investors and technology companies can influence which futures appear realistic or unavoidable through their products, spending, and public claims.
These mechanisms can concentrate power without requiring every executive or wealthy investor to share one motive. Establishing how much control exists in a particular case requires evidence about ownership, deployment, outcomes, and accountability—not just a prediction about AI.
Four different meanings of “inevitable”
Arguments about inevitability often blur distinct claims. Cottom’s reported warning is most pointed at the political and moral versions, where a forecast is used to make public acceptance seem compulsory.
- Technical: A capability may become possible. That alone does not determine whether it should be built or used.
- Commercial: A company or industry may choose to deploy a system. A business decision is not the same as a social mandate.
- Political: People are told that society must accept a deployment because there is no alternative. That proposition can be challenged through policy, public pressure, or collective bargaining.
- Moral: Harmful consequences are treated as justified because they supposedly cannot be avoided. A forecast does not by itself excuse those consequences.
Saying “AI is already here” may describe the presence of AI tools; it does not settle where they belong, who should control them, or whether people must accept every use.
What the headline establishes—and what it does not
Futurism identifies Cottom, reports her remarks, and frames them as a warning about the wealthy and AI. But the article does not name billionaires, cite documents, identify a coordinated set of actions, or establish a plan to take total control. Its headline turns a structural and political argument into a sweeping allegation.
That distinction matters. Concentrated ownership, workplace monitoring, automated decisions, or dependence on private infrastructure can be investigated as specific problems. They do not, by themselves, prove that “the wealthy” act as one organized group or that AI has already given anyone total control. The panel remarks are commentary, not a systematic evidentiary record about the conduct of particular people or companies.
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Random freezes, missing sound and display glitches usually trace back to one bad driver. Find and replace yours safely.Free scan · under a minuteIt is also possible to criticize concentrated power without assigning a single intention to every investor or executive. Market incentives, institutional choices, and regulation can produce unequal outcomes even when actors disagree about their goals. A stronger factual claim about deliberate coordination would require evidence of coordination.
How to assess a particular AI deployment
The useful response to a broad warning is to examine the decisions that make a system consequential. For a workplace tool, a government service, or a platform feature, ask:
- Who owns and operates the system, and who can change or replace it?
- What decision does it influence, and who receives the benefits?
- Who bears the costs of mistakes, surveillance, job changes, or lost access?
- Can an affected person understand the decision and appeal it to someone with authority to change it?
- Can workers, communities, or service users opt out or participate in setting the rules?
- Are there independent audits, clear accountability, and a non-AI alternative where appropriate?
Possible collective responses include bargaining over workplace uses, public procurement standards, transparency and audit requirements, privacy protections, limits on high-risk surveillance, appeal rights, and public participation in deployment decisions. These are practical avenues for turning refusal of inevitability into governance; they are implications of the argument, not a policy list attributed to Cottom in the report.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Why the historical analogy needs limits
Futurism reports that Cottom invokes chattel slavery to illustrate how an institution can be presented as natural or fixed and later challenged. The analogy’s point is about political imagination and refusal: what powerful people describe as permanent may still be subject to collective struggle.
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It is not an equation between AI and slavery, nor empirical evidence about AI ownership. Historical comparisons can illuminate how power is defended, but they risk overstating a case if differences in the systems and harms are ignored.
Could AI spread power as well as concentrate it?
Yes. Open-source systems and competition can broaden access, and AI tools may help people obtain services or expertise. Regulation can constrain some uses. At the same time, broad access to a tool does not guarantee that its infrastructure, profits, or governance are broadly shared; open systems can also lower the cost of misuse. Concentration can emerge from economic incentives without a single coordinated intent, while unreliable systems can still create dependence if institutions adopt them.
These possibilities make the argument a question about institutions and choices, not a simple prediction that AI must either liberate or dominate people. Whether a deployment improves access or entrenches control depends on its ownership, rules, effects, and the ability of affected people to challenge it.
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