This is going to be a thread about unconscious bias in science. I had written before about bias in science (kristof.blogs.nytimes.com/2016/08/04/rac…), but this will be different. I want to share two recent instances in which I had to confront my own unconscious biases, and some reflections.
The first one was after a group of us, three men and two women, received an award and were interviewed. After the article came out one of my female colleagues called me and asked if I thought there was anything odd with the narrative of the article.
I had read it and noticed nothing wrong, so I read it again, this time fact-checking. I still could not see a problem. She forward me an email she sent the (female) journalist. In the email she pointed out, correctly, that only the men were quoted.
I note again, as embarrassing as it is for me to admit, that I had read it twice, and even when prompted by my colleague, had not seen that glaring problem.
The second incident was conference I organized. During the meeting, several female colleagues courageously came up to us to correctly point out that the representation of women among the speakers was abysmal. Until they pointed it out, I had not seen it.
It is important to acknowledge that it was women who called me out. Could other men had done it? Maybe, but they didn’t. I am not arguing this should be a woman scientists job, but I am arguing for the importance of diversity in science. We are all better for it.
I am not proud of these events, and it is embarrassing to share them publicly. I share them in hopes they lead to broader conversations about “being” biased, about “being” prejudiced, and how we approach that in conversations and in systematic approaches
Here, I have to draw a little from language to make my point. In Spanish, the English verb “be”, like “being biased” can be one of two different verbs, depending on the connotation: “ser” or “estar”.
“Ser” is a largely immutable state, is a defining property of the individual. “Yo soy puertorriqueño”. “Estar” is used for mutable, changable states. “Yo estoy en New Haven”. In English, both of these states would be referred to as “I am”
I think we approach “to be biased” in science with the Spanish verb “ser”, when we should approach it with the verb “estar”. I am one who thinks we all have biases, the same way that, in science, we “are” all ignorant in some topics, no matter how illuminated we think we “are”.
It is easier to see bias in retrospect. It is easy to read Ramón y Cajal “Advice for a young investigator” and pick up on all the 19th century machismo. Much harder to identify how scientists, in 100 years, will talk about our biases.
But unless we are the first generation of scientists in the history of humanity that are not biased, we probably all have them, and we always will. If then we approach bias as a binomial/immutable state—we are prejudiced vs we are not, —we distort our identities in dangerous ways
"Ser" biased prevent important acknowledgement of our mutable states and our capacity to recognize ignorance, grow and change. Ramón y Cajal himself said, “I reserve the precious and inalienable right to evolve at the compass of new things I learn as times change”.
In science, acknowledging ignorance & wanting to do something about it leads to growth. In this twitter medium, where it is easiest in a few characters to “ser”, I want to use this thread in hopes that that acknowledgement, when applied to bias, helps reframe the conversation .
I also use the thread to reach out/thank scientists who have been sharing their systematic approaches to help us all do better in identifying and addressing our unconscious biases. Please continue, many of us are listening.
Special thanks to @valentatormenta, @ewang422, @moefeliu, @Sefini, @JenCWaters (and many others) about important, illuminating and growth discussions for me on these topics.
It is scary when you do not know what you do not know. It is less scary if you have colleagues to help you be better.
