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@emollick
The problem is that the incentives push for "more" over "better" Paper: https://t.co/slzrdakwUJ
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@emollickposted on X
Very cool analysis of the submissions to a major management journal that shows how much the system of science, built for humans, is under strain as a result of AI. AI can be used to do better science or it can be used to just do more stuff. The danger is that "more" is winning https://t.co/0DbheDzbLR
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Community Sentiment Analysis
Real-time analysis of public opinion and engagement
Sentiment Distribution
90% Engaged
90% Positive
Positive
90%
Negative
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Neutral
10%
Key Takeaways
What the community is saying — both sides
Supporting
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High AI usage correlates with lower readability
the data look like a near-perfect inverse: as AI-driven output surges, clarity and readable ideas drop sharply, suggesting we’re trading comprehension for throughput.
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Incentives favor measurable volume over meaningful insight
systems reward counts and speed, so outputs that are easy to track win even if they dilute scientific rigor.
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Fix the gates, not just the models
stronger filters, accountability, and redesigned reward structures are needed so AI amplifies quality instead of just quantity.
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Use AI to scale review, not only production
proposals include AI-assisted peer review and automated screening to triage low-utility submissions before they drown human reviewers.
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Reviewer capacity is the rate limiter in code and science
when producer rate jumps but human review doesn’t, queues and length-of-diff heuristics replace real quality checks; the practical remedy is compact review schemas that compress checks into cheaper units.
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Startups and institutions face the same pressure
AI makes shipping cheap, but validation cycles (customers, judgment, patent offices, journals) didn’t speed up, so volume can masquerade as progress and overwhelm gatekeepers.
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Quantity isn’t always worthless
the photography-teacher analogy reminds us that doing more can sometimes yield better results; the right balance is designing workflows where iteration improves quality rather than buries it.
Opposing
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Top Reactions
Most popular replies, ranked by engagement
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@borancakir
Same thing is happening in startups right now. AI made it cheap to ship more, but the cycles that actually tell you if something's any good (customers, real review, judgment) didn't get faster. Everyone who confused volume with progress is hitting that wall at the same time.
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@heygurisingh
This highlights how incentives shape outcomes, and without changes the system may reward volume over genuine insight
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