Assessing the Authenticity of an Interviewee
In a 2014 Auto Bild interview, Elon Musk revealed he assesses the authenticity of an interviewee’s claimed experience by asking for a detailed description of the most difficult problem(s) the interviewee previously worked on and solved. According to Musk, “The people who really solved the problem know exactly how they solved it and can describe the little details.” He elaborated, “If there’s a track record of exceptional achievement, then it’s likely that that will continue into the future.” Mr. Musk’s brilliant generalized question applies to any facet of human behavior.
When I was a new Assistant Professor of Medicine in 1985, one of my administrative assignments was interviewing applicants for a research-oriented post-doctoral fellowship. I asked every candidate a specific question that directly encapsulated the crux of the research position: “What is your favorite statistical analysis, and why?”
Unless one understands the relationship between hypothesis, research method, measure theory—and statistical analysis, it is impossible to design a proper research study, or to analyze or understand study findings and their resultant implications.
Research in every area of science, including medicine, involves:
- constructing a research hypothesis—that is, stating what is expected to happen in an investigation before data are collected, based on a thorough review and synthesis of all published research concerning the focus of investigation;
- designing and conducting an experimental procedure, free of issues which create paradoxical (false) findings, to obtain data to test the research hypothesis;
- synthesizing, presenting, and analyzing the experimental data;
- making sense of findings which support, and that fail to support, the hypothesis;
- and designing future research which will yield more informative results.
Being an Authentic Interviewee or Presenter
Another of my administrative assignments was coaching soon-to-be first-time student and faculty presenters at a professional conference or a colloquium, regarding responding to questions they don’t understand or for which they haven’t a compelling response.
I advise first-timers that for any question asked it is crucial to clearly understand:
- what one knows regarding the question, accurate to the extent possible given experimental design, measurement, and analysis imperfections;
- and, most importantly, what one doesn’t know regarding the question.
“Winging” an unknowingly incoherent response to a question asked of one afore a panel of experts is a common self-injurious behavior.
It is crucial to understand what one doesn’t know: if one doesn’t know what one doesn’t know, then it is impossible to know what one does know.
If a question is asked for which a response is not available, not definitive, or impractical (e.g., due to complexity), replies which may prevent a question from hijacking one’s presentation are:
- “I appreciate your important, interesting, and complex idea, which I must look into when I return to my laboratory”; or
- “I appreciate your important, interesting, and complex idea, which I hope we can discuss after I complete my presentation.”
However, if a question is asked for which a competent response is ready to present—as Mr. Musk stated, details are the crux of a professional response.
In my experience enthusiasm borne of inherent interest and true expertise—is infectious.
Know what you know; know what you don’t know; be respectful and have fun…
Paul R. Yarnold, Ph.D
March 3, 2021