As major language models like GPT-4.5, Claude 3, Gemini 1.5, and Sonar Pro mature, a concern is beginning to circulate among advanced users: are the responses generated by different AIs becoming too similar? Are we entering a stage where AI, paradoxically, generates less diversity of thought?
What does “homogenization” mean?
It is the phenomenon where, despite using different models, the responses tend to be similar in:
- Tone (polite, technical, neutral)
- Structure (introduction + list points + conclusion)
- Content (use of common references and scientific consensus)
- Avoidance of risk or ambiguity
This may be due to training with very similar datasets, security filters, and user preferences for "safe" answers.
Why does this happen?
-
Convergent training corpus : most models are trained with filtered web text, academic papers and code, reducing creative variety.
-
Optimization for RLHF : models learn to generate what humans rate as "correct", not necessarily as "original".
-
Security policies : to avoid hallucinations, risky or speculative answers are penalized.
-
Similar interfaces : similar prompts + identical interfaces = similar responses.
Is it a real problem?
It depends. For tasks like summarizing texts, explaining a concept, or creating functional code, homogeneity is synonymous with accuracy. But in areas like creativity, research, or critical analysis, diversity of thought is key .
What are companies doing?
- Anthropic : Claude seeks to "reason rather than please" in his latest versions.
- OpenAI : Custom GPTs and "creative" mode aim to diversify style.
- Google : Gemini Studio allows you to modulate the temperature and style of the outputs.
- Perplexity : its factual approach with Sonar Pro reduces bias towards “general consensus”.
How can I, as a user, avoid this?
- Vary the type of prompt and ask for divergent opinions.
- Use different models to compare perspectives.
- Customize your GPT or explore agents with intentional bias (economic, philosophical, etc.)
In summary, the homogenization of IAG is a real trend, but also an opportunity for creators, researchers, and demanding users to challenge its limits.