Underreliance on mechanistic models: Comment on Ferguson (2015)

Area of Science:

• Cognitive Psychology
• Computational Neuroscience
• Philosophy of Science

Background:

• Public perception of psychology is often negative.
• Ferguson suggested overreliance on mechanistic models contributes to this view.
• An alternative perspective posits that explanations lack crucial mechanism information.

Purpose of the Study:

• To challenge Ferguson's view on public perception of psychology.
• To argue that a lack of mechanism information in psychological explanations hinders understanding.
• To identify parallel distributed processing connectionist neural network models as a source of mechanism information.

Main Methods:

• Conceptual analysis of psychological explanation.
• Literature review on mechanistic models and connectionist neural networks.
• Argumentation based on the role of mechanism information in scientific understanding.

Main Results:

• Psychological explanations are often interpretive rather than explanatory due to missing mechanism details.
• Parallel distributed processing (PDP) connectionist neural network models provide a framework for incorporating mechanism information.
• This approach can enhance the explanatory power of psychological theories.

Conclusions:

• The public's negative view of psychology stems from explanations lacking mechanism information.
• Incorporating mechanism details, potentially through connectionist models, can improve psychological explanations.
• This shift from interpretation to explanation is vital for advancing psychological science and public trust.