Will artificial intelligence be a blessing or concern in assistive robots for play?
Bibliographic record
Abstract
Os avanços recentes e popularidade da Inteligência Artificial (IA) oferecem possibilidades animadoras para melhorar a tecnologia, mas, também, trazem preocupação. Neste artigo, usamos nossa pesquisa para apresentar os benefícios potenciais do uso da IA em tecnologia assistiva para crianças com deficiências brincarem e examinar possíveis preocupações éticas em torno dos dados exigidos pelos algoritmos de IA. Uma vez que o brincar é um fator chave no bem-estar infantil e no desenvolvimento cognitivo, as incapacidades secundárias podem surgir como consequência de deficiências motoras. Robôs assistivos para manipulação aumentativa podem ser fundamentais para proporcionar às crianças com deficiência física oportunidades de brincar, mas precisamos adotar uma abordagem baseada em princípios e centrada no usuário para inovações técnicas.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".