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Digital Phenotyping: an Epistemic and Methodological Analysis
Simon Coghlan1, Simon D'Alfonso1
1School of Computing & Information Systems, Faculty of Engineering and Information Technology, The University of Melbourne, Victoria, Australia.
Philosophy & Technology
|November 17, 2021
Summary
Digital phenotyping offers insights into human psychology and behavior by analyzing digital data. Careful consideration of its epistemic and methodological aspects is crucial for accurate understanding and application.
Area of Science:
- Psychology
- Digital Health
- Philosophy of Science
Background:
- Digital phenotyping is proposed to revolutionize understanding of human psychology and wellbeing.
- Existing literature primarily focuses on ethical implications, neglecting epistemic and methodological aspects.
Purpose of the Study:
- To investigate the epistemic and methodological foundations of digital phenotyping.
- To analyze the knowledge potential and limitations of digital phenotyping for understanding human psychology and behavior.
Main Methods:
- Development of a tetra-taxonomy of knowledge acquisition scenarios from digital data ('digitypes').
- Analysis of causal, correlative, and constitutive relations between digital information and psychological/behavioral phenomena.
- Examination of inference modes within these scenarios.
Main Results:
- Identified four scenarios for knowledge acquisition through digital phenotyping.
- Digital phenotyping shows potential for insights into psychological states and new category discovery.
- Highlighted risks of unwarranted conclusions and distorting effects in digital sensing.
Conclusions:
- Digital phenotyping's promise hinges on accurate forecasting, diagnosis, causal explanation, and revealing constituents of human experience.
- Requires careful attention to epistemic and methodological rigor to avoid misinterpretation.
- Potential to advance psychological knowledge if limitations are addressed.
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