By Dr. Sacha Noukhovitch, Founder and President of STEM Fellowship

This article was also published by the Canada Science Policy Centre, a hub for discussion, recognition and dialogue on science policy in Canada. You can see Dr. Noukhovitch’s article, and others, on their site here.

Information Immunity

There are not one, but two pandemics taking place at the moment. One is COVID-19 in the physical reality and another is COVID-19’s information communication and interpretation that takes place entirely online. Both have significant effects on individual and public health.

Words and images shared online have shaped the behaviour of the general public and manifested itself through recent waves of toilet paper stockpiling that spread in a chain reaction across regions and countries. Online information or misinformation on COVID-19 has become a defining factor for mass decision making, money flows and production changes.

It is common knowledge that toilet paper stockpiling was caused by COVID-19 fears but an empirical comparison of regions and countries most affected by overstocking does not correlate with those most impacted by COVID-19. Based on this, I suggest the concept of innate and adaptive immunity to online data and information: how the public consumes and responds to the entire spectrum of science communication from fact to misinterpretation to pseudoscience to fake news. Innate information immunity would be based on an individual’s ability for critical thinking and data analysis that correlates but does not always equate to the level of education. Adaptive information immunity develops through individual and group learning as a person experiences and processes information shared online.

Generational Gap – Digital Divide

By looking at the Canadian shoppers who stockpiled supplies due to the coronavirus outbreak, it is possible to define three distinct reactions: moderate stockpiling among 25-44 year olds; a low reaction among 45-64 year olds; and the most significant among those who are 65 and above. It is obvious that the differences in consumer behaviour between these groups were determined by the coronavirus information they consumed from news and social networks and their interpretation of manufacturers’, politicians’ and medical professionals’ assurances. All in all, we see three different information immunity reactions.

It is reasonable to assume that on average, there should not be much difference in innate information immunity between the groups. The education system has not changed much in the past 60 – 70 years, offering the same core learning subjects and  generally teaching the same critical thinking techniques. Therefore, innate information immunity should not be a factor in the difference in consumer behaviour and stockpiling between age groups.

On the other hand, adaptive information immunity that includes collective learning elements such as news media, social networks and email chains varies a lot from one age group to another. Moreover, the breakdown in consumer reactions we saw between groups of 25-44 year olds, 45-65 year olds and those 65 and above corresponds well with information consumption preferences. Facebook and Twitter user statistics roughly delimits the first group. It is reasonable to assume that the adaptive information immunity of those over 65 would be determined by news media and what is hardly possible to quantify – email chains and forwards that are notorious for “personal experience” stories. Finally, the 45-64 year olds happen to be least hooked up on social networks and are considerably less exposed to vital information. Different collective learning sources naturally result in different adaptive information immunity that create a generation gap in information interpretation and decision making as well as a digital divide in the evidence base for it.

Perfect Storm in Science Communication

We face an unprecedented magnitude of scientific information that has drastically affected the world economy, politics, and civil life. Using an immunology model perhaps does not explain to the full extent the pros and cons of public science communication, but it brings us closer to understanding how this first-of-its-kind information pandemic was caused by COVID-19.

Historically, traditional forms of communication did not allow for viral spread of information. Even at the peak of Cold War instability, the dissemination of information about the nuclear explosion and radiation had significantly less socioeconomic and psychological effects. Today, the Internet and proliferation of social networks creates a fertile ground for large scale rumors, confirmation of biases through feed-back loops and overwhelming the public with an abundance of information that stands in the way of surfacing facts. The COVID-19 pandemic is perhaps the first time that scientific information went viral unprotected by the typical peer-review and expert assessment that has safeguarded science communication before.

The COVID-19 pandemic has disrupted the peer-review process with pressure from two sides. On one side, there are predatory publishers who bypass the peer-review process and release unconfirmed research in pursuit of revenue. On the other side, there are bloggers and businesses who generate fraudulent and pseudoscientific theories with the intent of going viral to boost their readership or sales. The high public demand and urgency for direct connections between scientific theories and practical personal health decisions during the COVID-19 pandemic enables these pressures to shape public knowledge and decision-making.

Information Reality(ies)

Due to the difference in information sources, the three groups discussed earlier exist in different information realities. These information realities do not vary much in the part of public health and real science communication information. The real difference lies in community interpretations and misinterpretations that come with fake news. Pseudoscience is great at offering theories that sound plausible by triggering associations with known facts while passing under the radar of innate information immunity, which should otherwise cast doubt on the accuracy of the information. It offers simple solutions to complex concepts backed by seemingly popular opinion and is spread within each of the three groups. Unfortunately, real science communication typically does not take into consideration a group’s information consumption preferences. As a result, it is not given priority when an individual is acquiring adaptive information immunity. One interesting flip side to pseudoscience theories that are accepted within each of the three groups – when transplanted into a different group’s reality, it is easily identified as fake news.

A unique sensibility to pseudoscience is demonstrated outside of the three defined groups by 17-24 year olds who have the strongest potential for critical analysis of facts and adaptive information immunity. Their active participation in formal and informal education naturally results in the application of the scientific method and critical thinking in forming their adaptive information immunity. Furthermore, the innate information immunity of 17-24 year olds is still under development and varies from individual to individual quite significantly. That makes the task of concocting plausible pseudoscience that will work for the majority of this age category practically impossible.

Youth as Agents of Information Immunity

Highly engaged in online communication, youth have the potential to become information immunity agents for the general public. Empowered with an evidence-based approach and relevant scientific information, they can significantly contribute to scholarly communication and the boosting of adaptive information immunity, which is a critical first-level defence against pseudoscience.

However, without an emphasis on proofs when teaching scientific theories, students learn to take new information for granted and are unable to distinguish between factual information and pseudoscience consumed online. Reinforcement of their role as agents of information immunity requires developing their natural analytical abilities. This could be achieved through student-driven and Open Data-based experiential learning programs within Open Science research fields. Students who engage in scientific fields beyond those covered in High School acquire adaptive information immunity to relevant topics they will encounter online.

COVID-19 presents an opportunity for students to use socioeconomic and social network Open Data like Twitter for experiential learning in bioinformatics and sociology. One program that offers this opportunity is the National Undergraduate Big Data Challenge: Personal and Public Health Decisions in a New Open Data Reality which runs until July 2020. Using Open Data from government, non-profit, and corporate sources, students across Canada will submit original research exploring the complexities of public and personal health decisions.

Youth involvement in science communication will be a critical element in preventing future information pandemics. Empowered by big data, youth will be able to assert factual positions among their peers and with other generations. Their adaptive information immunity that is based on the most relevant scientific findings will be spread within their communities, both physical and online, to stop the spread of misinformation, and align public decision making with scientifically-based recommendations.

References

1. Leading provisions purchased due to the coronavirus outbreak in Canada as of March 2020 https://www.statista.com/statistics/1105818/coronavirus-main-provisions-in-canada/

2. Shoppers who have bought supplies due to the coronavirus outbreak in Canada as of March 2020, by age group https://www.statista.com/statistics/1106130/coronavirus-stockpiling-in-canada-by-age/

3. Distribution of Facebook users in the United States as of February 2020, by age group and gender https://www.statista.com/statistics/187041/us-user-age-distribution-on-facebook/

4. Percentage of U.S. adults who use Twitter as of February 2019, by age group https://www.statista.com/statistics/265647/share-of-us-internet-users-who-use-twitter-by-age-group/

5.  Immunology https://www.creative-diagnostics.com/immunology.htm

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