How AI Aggregation Affects Knowledge
Daron Acemoglu, Tianyi Lin, Asuman Ozdaglar, James Siderius
TLDR
This paper shows how AI aggregation, when used as training data, impacts social learning, finding that fast-updating global AI can hinder knowledge.
Key contributions
- Extends the DeGroot model to include an AI aggregator that learns from and influences population beliefs.
- Identifies a critical threshold in AI updating speed, showing fast aggregation hinders robust learning improvement.
- Demonstrates that local, specialized AI aggregators consistently improve social learning outcomes.
- Warns that replacing specialized local AI with a single global aggregator can degrade learning quality.
Why it matters
This research is crucial for understanding the systemic effects of AI on collective knowledge formation. It provides actionable insights for designing AI systems that support, rather than hinder, social learning. The findings highlight the importance of careful architectural choices in AI deployment.
Original Abstract
Artificial intelligence (AI) changes social learning when aggregated outputs become training data for future predictions. To study this, we extend the DeGroot model by introducing an AI aggregator that trains on population beliefs and feeds synthesized signals back to agents. We define the learning gap as the deviation of long-run beliefs from the efficient benchmark, allowing us to capture how AI aggregation affects learning. Our main result identifies a threshold in the speed of updating: when the aggregator updates too quickly, there is no positive-measure set of training weights that robustly improves learning across a broad class of environments, whereas such weights exist when updating is sufficiently slow. We then compare global and local architectures. Local aggregators trained on proximate or topic-specific data robustly improve learning in all environments. Consequently, replacing specialized local aggregators with a single global aggregator worsens learning in at least one dimension of the state.
📬 Weekly AI Paper Digest
Get the top 10 AI/ML arXiv papers from the week — summarized, scored, and delivered to your inbox every Monday.