In a recent seminar that I was giving, a professor and scientist in the audience was offended when a slide I was showing stated that people will ignore data/information that does not match their model. He asked me if I was implying the scientists ignore data.
He went on to tell me that he would get fired in his job if he did that, and that a scientist would “never ignore data.”
I was intrigued by how strongly he reacted, but decided that it enough off topic to not pursue it.
And now I run into this interesting “The Truth wears off” article published in “The New Yorker.”
Here is an except from the article:
But now all sorts of well-established, multiply confirmed findings have started to look increasingly uncertain. It’s as if our facts were losing their truth: claims that have been enshrined in textbooks are suddenly unprovable. This phenomenon doesn’t yet have an official name, but it’s occurring across a wide range of fields, from psychology to ecology. In the field of medicine, the phenomenon seems extremely widespread, affecting not only antipsychotics but also therapies ranging from cardiac stents to Vitamin E and antidepressants.
How does one explain such phenomena? Does this support my premise about seeing in the data what matches our model? It sure is one explanation!
The other issue that the article raises is the unstated assumption, which is another topic touched upon in “Exploring the Gap between Science and Religion.” And that is what is the nature of truth, and does science deal with truth in the fist place. This question is posed by the blog: “What is the nature of truth? Is it self-evident?”