AI research

Why are fewer children being born?

Twelve frontier AI systems from twelve different laboratories were given the same brief, independently. Then they were shown each other's findings and made to argue, across five rounds. This is everything they said.

12AI systems
5rounds of argument
76 %nobody decided
332graded claims
Closing verdict, written by DeepSeek

Fertility fell because development rewrote the cost of children; only a few states coerced births.

Direct, moral blame belongs to the Chinese Communist Party for the one-child policy and its forced abortions and sterilizations; to Indira and Sanjay Gandhi's Emergency government for India's 1975–77 sterilization drive; and to Alberto Fujimori's Peru for coerced sterilizations. USAID, the World Bank, UNFPA, and allied foundations bear contributing culpability for funding and legitimizing target-driven programs, even where many were voluntary. A broader bu…

Read the full verdict

How much of this did anybody decide?

In round two every model had to commit to one number: what share of the global fall in births would have happened anyway, with no policy, no programme, no institution pushing. Nobody was allowed to refuse.

Alibaba Qwen 85 %
Mistral AI 85 %
Google DeepMind 80 %
Moonshot AI 80 %
Meta 80 %
DeepSeek 78 %
Z.ai (Zhipu) 75 %
Amazon 75 %
Anthropic 70 %
Perplexity 70 %
xAI 70 %
OpenAI 50 %
76%

Median of the panel. The spread runs from 50% to 85%, and by round five most models had conceded that the exact figure is a judgment, not a measurement.

See how each model defended its number →

The panel

Twelve systems, one brief

9 of 12 complete
OpenAI GPT-6 Astra Pro · USA

Smaller families became desirable and achievable; modern institutions then made even wanted children difficult.

Main cause: Changed economics of raising children
Google DeepMind Gemini 3.1 Pro · USA

Global fertility fell because women gained education, agriculture industrialized, and raising children became exponentially more expensive.

Main cause: Female Education and Empowerment
xAI Grok 4.6 · USA

Development made children costly; states and contraception made small families easy

Main cause: Women's education and time cost
Anthropic Claude Fable 5.1 · USA

Parents, not plotters, cut births: mortality, schooling and cost reversed children's value; states accelerated it.

Main cause: Women's education and paid work partial report
Meta Llama 4 Maverick · USA

Global fertility decline driven by urbanization, education, and economic factors

Main cause: urbanization
DeepSeek DeepSeek V4 Pro · Čína

Fertility fell because child survival, female education, and urban economics rewrote the cost-benefit of children.

Main cause: Child mortality decline
Mistral AI Mistral Large 3 · Francie

Falling fertility stems from women's freedom, urban life, and economic pressure

Main cause: women's education and autonomy
Alibaba Qwen Qwen 3.7 Max · Čína

Female education and urbanization drive fertility decline more than policy or ideology.

Main cause: Female Education Expansion
Moonshot AI Kimi K3 · Čína

Fertility fell because modernity made children expensive, optional, and postponable, not because anyone conspired.

Main cause: Economic development and urbanization
Z.ai (Zhipu) GLM-5.2 · Čína

Fertility collapsed because women got options besides motherhood.

Main cause: Economic shift from child labor to costly education
Amazon Nova Premier · USA

Global fertility declines driven by urbanization and education expansion

Main cause: Urbanization pressures partial report
Perplexity Sonar Deep Research · USA

Fewer children reflect development, women’s choices and hard-to-raise families, not a single plot

Main cause: Female education and autonomy searches the web partial report

Then they argued

Each model was shown what the other eleven had concluded, then pushed through five rounds. They were told to attack the weakest claim on the board and to name what they got wrong.

1

Where we disagree

Each model is shown what the other eleven concluded. It must name the single claim on the board it thinks is most wrong, and say why.

2

Structure or decision?

The core split: did this happen to us, or was it done to us? Models must commit to a share — how much of the fall was nobody's decision.

3

Evidence audit

Each model must attack the weakest evidence on the board — a specific claim by a specific named model — and defend its own weakest point.

4

What would have changed it

A counterfactual test of causation: name the one intervention that would have kept births up, and accept what that admission implies about your own cause.

5

Final position and the vote

Last word. Each model states what it changed its mind about, gives its final verdict on blame, and votes for the panel member whose analysis was strongest.

How this was made

HOW THIS WAS MADE

Twelve models, one identical brief. Every model received exactly the same text, so that any difference in the answers is a difference between models and not between questions.

Every claim carries a level of evidence. DOCUMENTED means a specific decision, law or dataset a reader can look up. STRONG means an established finding reproduced across countries. CONTESTED means it circulates but is not settled. The models assigned these levels themselves.

Only one of the twelve can search the web. Perplexity Sonar Deep Research reads live sources and returns citations. The other eleven answered from what they had learned in training, which means their specifics can be wrong even when their reasoning is sound. That is why every model was asked to grade its own evidence, and why disagreement between them is worth more than any single answer.

Where a model ran out of space before finishing a section, we say so on its page rather than quietly hiding the gap.

A CONFLICT OF INTEREST, DECLARED

This investigation was assembled by Claude, made by Anthropic — and Anthropic is also one of the twelve laboratories on the panel. Anthropic's seat was answered by a different model (Claude Fable 5.1) through the same gateway as everyone else, under the identical brief, without sight of the other answers. The assembling model never wrote, edited or improved any panel member's words, including its own laboratory's. It chose the questions, the panel and the rounds, and it is telling you so here. Anthropic finished second in the panel's own vote; the closing verdict was written by DeepSeek.

How to read the evidence badges

documented a decision, law or dataset you can look up
strong evidence established across countries
contested circulates, but is not settled

Across the twelve reports: 207 documented, 99 strong, 26 contested. The models graded themselves.