otherQ6to verify
Pedreschi et al. 2024/25 — human-AI coevolution framework (Artificial Intelligence journal / arXiv)
Recommender systems and AI assistants create a continuous bidirectional feedback loop — user choices generate the data that train AI models, which then influence future user choices — such that the user-AI dyad cannot be modeled as one-way tool use. The authors argue this requires methodological tools from complexity science and network theory to capture the feedback dynamics.
Conceptual/methodological framework (not a single quantitative finding); the paper surveys feedback dynamics across recommender systems, social media, and assistant interactionsN/A — framework paper; quantitative results are inherited from cited empirical work (Glickman & Sharot, Shumailov et al., others) rather than newly produced.
- Sample
- Review / framework paper; no primary-data sample.
- Methodology
- Conceptual framework + literature review proposing complexity-science and network-theory methods for capturing feedback-loop dynamics in human-AI systems.
What this means
- Names the unit-of-analysis shift explicitly: from 'human uses tool → outcome' to 'recursive system dynamics over time' — the encyclopedia's Part I §1.3 methodology argument has a direct citation here.
- Provides the framing under which the empirical findings (Glickman & Sharot bias-amplification, Shumailov model collapse, Cito & Bork code collapse) form a single coherent research program rather than scattered results.
- Methodological recommendations align with the AHI reviews' shared 'gap statement': a credible 6-24 month panel study must measure human + AI + environment as one coupled system.
Source
Artificial Intelligence (Elsevier) / arXiv 2306.13723 · Dino Pedreschi & and colleagues · 2024 · peer-reviewed
Context
- What came before
- Pre-2023 HCI / recommender-systems literature evaluated AI systems via offline-eval-on-static-data + A/B-test-deltas. Feedback-loop dynamics were named but rarely instrumented as load-bearing variables.
- What comes next
- This is a framework paper, so its 'quantitative finding' is inherited from cited empirical work — verify each downstream citation independently when used as load-bearing. Primary value is methodological grounding for Part I §1.3.
- Where this lands
- Encyclopedia Part I §1.3 (methodology gap — the named source for the unit-of-analysis shift) and Part V (research frontier methodology section).