- P-ISSN1226-9654
- E-ISSN2733-466X
- KCI
인과 구조 작동 방식이 인과 추론의 정확성에 미치는 효과
The Effect of a Functional form of Causal relation on Accurate Causal Reasoning
도승이 (성균관대학교)
초록
개인과 기업 그리고 국가 정책의 성공은 판단과 예측의 정확성에 달려있다고 해도 과언이 아니다. 하지만 사람들은 판단과 예측을 할 때 주어진 정보 외에 추가적인 정보를 탐색하지 않으며, 심지어 주어진 정보조차 무시한다. 판단과 예측의 정확성을 향상시키기 위해서는 이러한 정보 무시 경향성의 인지적 과정에 대한 이해가 필수적이다. 본 연구는 고등 인지 과정의 새로운 규범적 모델로 떠오르고 있는 인과 베이즈 모형(causal Bayes nets)의 틀에서 정보 무시 현상의 인지적 과정을 연구하였다. 실험 1에서는 인과 베이즈 모형이 적용되기 위한 세 가지 경계 조건인 인과 구조와 파라미터의 충분성 및 인과 구조 작동 방식의 명확성을 만족시키는 상황을 구성한 후 인과 추론을 실시하였다. 선행 연구와는 다르게 실험 1에서는 정보 무시 현상이 관찰되지 않았다. 실험 2는 인과 구조가 작동하는 방식을 변경하였다. 실험 2는 인과 구조가 자발적으로 작동한 실험 1과는 달리 인과 구조가 실험 참여자의 개입에 의해서만 작동하였다. 실험 2에서는 정보 무시 현상이 관찰되었다. 이는 선행 연구에서 보고된 정보 무시 현상이 인과 구조 또는 관련 변인들이 작동하는 방식에 대한 인출이 되지 않아서 발생했을 가능성을 시사한다. 본 연구는 또한 인과 관계 표상에 대한 인과 베이즈 모형의 가정이 실제 사람들의 표상과 다를 가능성이 있음을 시사한다. 본 연구는 인과 구조가 작동하는 방식에 대한 인지적 이해를 바탕으로 판단과 예측의 정확성을 향상시키는 후속 연구가 필요함을 보여 주였다.
- keywords
- The causal Bayes nets, neglect of relevant information, predictions, 정보 무시 현상, 인과 베이즈 모형, 인과 구조 작동 방식, 예측 추론
Abstract
The success of an individual, a business and even a country depends on the accuracy of judgments and predictions about the future. Reasoners, however, often fail to search for additional pieces of information to make an accurate prediction. Moreover, they tend to neglect a relevant piece of information even if it is available. Thus, it is critical to understand the cognitive process behind the neglect phenomenon in order to increase the accuracy of predictions. The present study aimed to investigate the process that underlies neglect of relevant information based on a newly emerging normative model, the causal Bayes nets. In Experiment 1, we constructed a situation where the three boundary conditions of the causal Bayes nets were satisfied: the sufficiency of a causal structure, parameters, and the clarity of the functional form of causal structure. The results revealed that participants did not neglect a relevant piece of information when they made a predictive inference. Experiment 2 was identical to Experiment 1, except for the functional form of causal structure. The causal structure in Experiment 1 was activated by itself while the structure in Experiment 2 was activated only when it was intervened. With the intervention-based causal structure, participants showed neglect of a relevant piece of information to make a predictive inference. Our results suggest that neglect of a functional form of events in question is responsible for the failure to consider relevant information. Our results also suggest that the assumptions that the causal Bayes nets make about representations of causal relations may not be consistent with the actual representations of reasoners. Our results suggest that a future study is necessary to investigate how understanding of the functional form of causal structures influences prediction accuracy.
- keywords
- The causal Bayes nets, neglect of relevant information, predictions, 정보 무시 현상, 인과 베이즈 모형, 인과 구조 작동 방식, 예측 추론
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