The Emerging Role of Intelligence in the World of the Future
Bibliographic record
Abstract
During the 20th century, the world experienced an unprecedented rise in people’s cognitive abilities. IQs increased 30 points (with the average IQ remaining 100 only because publishers reset the “average” on their tests). Yet, society’s ability to confront serious problems in the world seems as challenged as ever. Problems such as air pollution, global climate change, increasing disparity of incomes, disputes that never seem to move toward resolution (such as between the Israelis and Palestinians), and increasing antibiotic resistance—all of these and many other problems seem to defy us, despite our elevated IQs. Why are there so many serious problems still confronting the world? Why is IQ insufficient for solving serious problems where differences in people’s interests are at stake? How can intelligence, broadly defined, help us to create a better world and solve the seemingly intractable problems the world confronts? The essays in this book address these questions and provide some directions for answers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".