My opinion

By Dr. Deepak Gupta
Corresponding Author Dr. Deepak Gupta
Wayne State University, - United States of America 48201
Submitting Author Dr. Deepak Gupta

Paul Ekman, Lie To Me, Gut Feeling, Automated Face-Expression-Reading Software, Facial-Recognition-System, Medical Student, Medical Faculty, Medical Trainee,

Gupta D. Great Responsibility with Exposing Human Emotion: Explore Futuristic Automated Face Reading. WebmedCentral MEDICAL EDUCATION 2016;7(7):WMC005166

This is an open-access article distributed under the terms of the Creative Commons Attribution License(CC-BY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Submitted on: 19 Jul 2016 06:34:59 PM GMT
Published on: 20 Jul 2016 04:45:57 AM GMT


For the sake of its incorporation into clinical diagnosis and management when practicing medicine, Ragsdale et al [1] studied human emotions based on under-appreciated explicitness in the subtleties of human face, a phenomenon recently popularized by Dr. Paul Ekman. I have been interested in Dr. Ekman's courses [2] since my addiction to television series "Lie To Me" [3]. However, I have been hesitant to delve into learning the intricacies of human emotions because the learner cannot unlearn the learning or un-know the knowing despite the learned being bestowed with the great responsibility of self-limiting the unlimited access to the privacy of human mind. Conceptually, when deciding to tread this path, one has to remember that one may only sharpen the innate "gut feeling" to read human face for exploring human mind because Ragsdale et al [1] reported that more than-half participants recognized portrayed emotions correctly before workshop, and that too unknowingly as reflected by less-than-one-third participants succeeding in knowledge questions. After workshop, face-expression-reading skill itself got sharpened in more participants than the acquisition of its knowledge (80% vs. 70%) [1], suggesting objectivity lagging behind subjectivity when reading human mind. Presence of prior training not helping to sharpen skills more [1] highlights natural "gut feeling" suffering with inherent trait of non-attainable near-perfect learning despite "zealous" medical students demonstrating more improvement in skill acquisition than "experienced" faculty or "indifferent" trainee-volunteers. The underlying reason for absence of superlative confidence ratings [1], while self-evaluating non-self-interpretations, could be apprehension "what if I would act based on my imperfect interpretation." This brings me to the finality requesting Dr. Ekman to develop futuristic face-expression-reading software (as similar to facial-recognition-system [4]) on air-gapped computers deriving data from cameras locked onto the faces of informed, consented individuals for pre-defined scenarios/indications because automated reads of the facial expressions, while prompting the blissfully untrained humans into actions based on the computerized interpretations, would thankfully not educate human eyes or human brains for unknowingly yet recurrently crossing the final hurdle and breaching the privacy of considerably-inviolable sanctity of human minds/emotions of people around them.


1. Ragsdale JW, Van Deusen R, Rubio D, Spagnoletti C. Recognizing Patients' Emotions: Teaching Health Care Providers to Interpret Facial Expressions. Acad Med. 2016 Mar 15. Accessed July 19, 2016.

2. Paul Ekman International, PLC. Our core modules. Accessed July 19, 2016.

3. Paul Ekman Group (PEG). 'Lie to Me'. Accessed July 19, 2016.

4. Wikipedia®. Facial recognition system. Accessed July 19, 2016.

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2 reviews posted so far

Facial recognition
Posted by Dr. Edwin Diasa on 06 Aug 2016 12:19:29 PM GMT Reviewed by WMC Editors

Facial Recognition in Medicine
Posted by Dr. Thomas F Heston on 21 Jul 2016 04:23:56 PM GMT Reviewed by WMC Editors

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