Measuring Trustworthiness or Automating Physiognomy? A Comment on Safra, Chevallier, Grèzes, and Baumard (2020)
Interpersonal trust - a shared display of confidence and vulnerability toward other individuals - can be seen as instrumental in the development of human societies. Safra, Chevallier, Gr\`ezes, and Baumard (2020) studied the historical progression of interpersonal trust by training a machine learning (ML) algorithm to generate trustworthiness ratings of historical portraits, based on facial features. They reported that trustworthiness ratings of portraits dated between 1500--2000CE increased with time, claiming that this evidenced a broader increase in interpersonal trust coinciding with several metrics of societal progress. We argue that these claims are confounded by several methodological and analytical issues and highlight troubling parallels between Safra et al.'s algorithm and the pseudoscience of physiognomy. We discuss the implications and potential real-world consequences of these issues in further detail.
Code (1)
Similar Papers 제목 키워드 기반
Automating Horizon Scanning in Future Studies
We introduce document retrieval and comment generation tasks for automating horizon scanning. This is an important task in the field of futurology that collects sufficient information for predicting drastic societal chan…
ArticlesComment GenerationRetrievalSAFRAN: An interpretable, rule-based link prediction method outperforming embedding models
Neural embedding-based machine learning models have shown promise for predicting novel links in knowledge graphs. Unfortunately, their practical utility is diminished by their lack of interpretability. Recently, the full…
Knowledge GraphsLink PredictionScalable and interpretable rule-based link prediction for large heterogeneous knowledge graphs
Neural embedding-based machine learning models have shown promise for predicting novel links in biomedical knowledge graphs. Unfortunately, their practical utility is diminished by their lack of interpretability. Recentl…
ClusteringKnowledge GraphsLink PredictionPredictionLeveraging Reward Models for Guiding Code Review Comment Generation
Code review is a crucial component of modern software development, involving the evaluation of code quality, providing feedback on potential issues, and refining the code to address identified problems. Despite these ben…
Comment GenerationReproducibility and Automation of the Appraisal Taxonomy
There is a lack of reproducibility in results from experiments that apply the Appraisal taxonomy. Appraisal is widely used by linguists to study how people judge things or people. Automating Appraisal could be beneficial…
Descriptive