Nature pointed me to an eloquent correction by a biology researcher. “What really matters is the science and getting it as right as possible. Avoid mistakes with careful science. Correct them with honesty and humility.”
Research in telecom often needs correction but that rarely happens. Currently, I am researching
- A professor who thought data dominated by in-home Wi-Fi showed broadband problems and made policy recommendations based on the misunderstanding.
- Wireless carriers using seriously out-of-date data to demand tens of billions in unnecessary subsidies for 5G. Everyone in the industry knows that T-Mobile committed to 99% 5G coverage, with Verizon & AT&T likely to come close to matching. Subsidies for 5G, except in the very few areas without towers, are almost always waste. Big in Europe.
- $5-15 billion NTIA might spend for homes that have a perfectly fine broadband connection via cable. This is due to errors in the FCC broadband fabric due to incorrect measures of broadband capacity. Davidson & Rosenworcel know this but don’t appear to be fixing it. Not good enough for government work.
“I make many mistakes,” the Butler said to Humphery Bogart in The Big Sleep. I’ve certainly made my share. Three years ago, I wildly overestimated the reach of mmWave 5G and hence its prospects. The only substantial data I had was from Verizon, an interested source. It turned out to be highly spun. I should have been more careful. (I did strongly correct.)
Here’s the statement shared by Professor Joan E. Strassmann
Retraction has a stigma about it. We’ve developed science with self-correcting mechanisms that are robust to misconception. Part of that means being honest about our errors. When I discovered the contamination, I could have quietly moved on and likely nobody would have ever known. Some selfish, anxious part of me wanted to do that. But I believe in the importance of intellectual honesty and owning my mistakes and never seriously flirted with the idea of burying them.
That is not to say it was easy. First, discovering the problem was a gradual process, in part because it did not even occur to me that something I had spent so much of my time and self-esteem on could have gone so awry. Early clues that something was wrong troubled me but were easy to explain away as some lesser error, particularly because the sequencing analyses that ultimately revealed the contamination were new to me. The first few results that did not turn out as I expected I assumed were because I had made some mistake in my code, had failed to set some needed argument, or failed to understand one of the multitude of assumptions inherent to doing bioinformatics. Each would send me off on some tangent trying to understand some new aspect of the program I was using.
Eventually, though, the simpler, uglier explanation occurred to me: I had messed up. I had messed up bigtime. Not with a few lines of code that could be fixed with some careful Google research. I had messed up the experiment itself, many months and dollars ago. Once that possibility had occurred to me all of my recent weird results made sense, and it was easy to confirm the worst. We would have to retract the paper.
Naturally I felt like a failure. I knew that I had done the research in good faith, and I believed that the ideas behind it had genuine merit, but I could not shake the idea that I had let down people who had invested in me. I’ve had to deliver the news to laymen and scientists alike – professors, post docs, fellow grad students, family members, the editors of the journal where we published the contaminated results. The response has been uniformly supportive. Nobody (but me) has scolded me for poor technique or for wasting time or money. Instead people have made excuses for me (“was it because of COVID?” was a popular one.) Nonetheless, the feeling that I had sinned was a hard one to dispel.
Here is the silver lining: I learned something, which is what science is about. I learned that the stigma I perceived was predominantly coming from my own ego. I learned how kind people could be about an honest mistake. I did the right thing, and none of the awful consequences I imagined following came to pass. I insisted on eating at least some crow (No, it wasn’t because of COVID), but in the end what really matters is the science and getting it as right as possible. Avoid mistakes with careful science. Correct them with honesty and humility. Have some faith that your fellow scientists will understand. And then get back to the lab.