Facts and falsehoods coexist on the Internet with perplexing similarity. Could social media — where misinformation is too often spread — be a place to help build trust in science and the research enterprise? Debra Karhson, PhD, a Stanford postdoctoral scholar in psychiatry, thinks so.
Karhson explored a method for authenticating the social media profiles of communicators to help users identify sources of accurate scientific information. Her essay on the idea, “A verification vaccine for social contagion,” won second place in this year’s Lasker Essay Contest, presented by the Albert and Mary Lasker Foundation.
I recently caught up with Karhson to learn more about her winning ideas.
Where did the idea for your essay come from? What inspired you to write about this topic?
As a translational neuroscientist researching autism spectrum disorder, one of my primary challenges (especially in interpersonal conversations) is overcoming the wealth of false and information on the subject. Most of these conversations end with me enumerating the ways in which most individuals can identify trust-worthy sources of empirical (evidence-based) data, knowing very well that it is a task not always undertaken. This year’s prompt for the Lasker Essay Contest provided me with the opportunity to deeply research the technological advances in the digital dissemination of data and think about potential solutions accessible to both professional and personal audiences.
Like any engineering-trained scientist, I first wanted a firm understanding of the available data that explores the relationship between scientists and public trust. My literature review started with reports from the Pew Research Center, which was an extraordinary resource on this particular topic. In parallel, because I am categorized as a millennial, I wanted to understand the social media tools already available for authentication (e.g., the Twitter verification badge) as well as their critiques. The blue badge of verification is as iconic as the floppy disk ‘save’ button, but can’t be used for the purposes of scientific reliability.
Finally, I was interested in comparing and contrasting both sets of knowledge with information on the digital advances in “trust technology” trending on aggregators like Wired, TechCrunch, and MIT Technology Review. Once I had all of that information, the challenges (and potential solutions) facing translation of ‘hard’ data to public discourse became readily apparent. The combination of a visual cue with the transparency of blockchain seemed like the most elegant and favorable idea.
What’s important to you about how science is communicated in the general population?
Much like a yawn or laugh can rapidly spread through a crowd, social media is the perfect vector for the spread of information swiftly. Yet, the task of examining the veracity of information has not advanced as quickly nor become any easier. So, while the general public has access to more information, deciphering what is fact has also become more difficult.
The most amazing things in research occur within the details and they can be so easily missed when science data are communicated poorly or ineptly. Particularly, in the case of autism spectrum disorder, where the basic biology remains unclear, the clear communication of what is known as well as new breakthroughs are often muted amongst over-amplified misinformation.
Do you have other ideas for how the lay population can verify the reliability of scientific information on social media?
When I consider the reliability of scientific information, the top two items I examine in any piece of information I encounter are: the source type (i.e., primary or secondary) and the date. With my training as a scientist, I prefer to read the primary source information for myself, starting with the most current available. Primary sources provide direct or firsthand evidence while secondary sources, as described here, “describe, discuss, interpret, comment upon, analyze, evaluate, summarize, and process” the information from primary sources. This strategy of examining the type of source and the date usually helps to minimize the amount of author bias, clarifies the authority, and often provides a direct line of communication to an author on the paper (e.g., the corresponding author).
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