A framework for quantifying individual and collective common sense.
Proc Natl Acad Sci U S A
; 121(4): e2309535121, 2024 Jan 23.
Article
em En
| MEDLINE
| ID: mdl-38227650
ABSTRACT
The notion of common sense is invoked so frequently in contexts as diverse as everyday conversation, political debates, and evaluations of artificial intelligence that its meaning might be surmised to be unproblematic. Surprisingly, however, neither the intrinsic properties of common sense knowledge (what makes a claim commonsensical) nor the degree to which it is shared by people (its "commonness") have been characterized empirically. In this paper, we introduce an analytical framework for quantifying both these elements of common sense. First, we define the commonsensicality of individual claims and people in terms of the latter's propensity to agree on the former and their awareness of one another's agreement. Second, we formalize the commonness of common sense as a clique detection problem on a bipartite belief graph of people and claims, defining [Formula see text] common sense as the fraction [Formula see text] of claims shared by a fraction [Formula see text] of people. Evaluating our framework on a dataset of [Formula see text] raters evaluating [Formula see text] diverse claims, we find that commonsensicality aligns most closely with plainly worded, fact-like statements about everyday physical reality. Psychometric attributes such as social perceptiveness influence individual common sense, but surprisingly demographic factors such as age or gender do not. Finally, we find that collective common sense is rare At most, a small fraction [Formula see text] of people agree on more than a small fraction [Formula see text] of claims. Together, these results undercut universalistic beliefs about common sense and raise questions about its variability that are relevant both to human and artificial intelligence.
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Texto completo:
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Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Inteligência Artificial
/
Conhecimento
Limite:
Humans
Idioma:
En
Revista:
Proc Natl Acad Sci U S A
Ano de publicação:
2024
Tipo de documento:
Article