Want to Strengthen American Democracy? The Science of Collaboration Can Help
This article is part of the magazine, "The Future of Science In America: The Election Issue," co-published by LeapsMag, the Aspen Institute Science & Society Program, and GOOD.
American politics has no shortage of ailments. Many do not feel like their voice matters amid the money and influence amassed by corporations and wealthy donors. Many doubt whether elected officials and bureaucrats can or even want to effectively solve problems and respond to citizens' needs. Many feel divided both physically and psychologically, and uncomfortable (if not scared) at the prospect of building new connections across lines of difference.
Strengthening American democracy requires countering these trends. New collaborations between university researchers and community leaders such as elected officials, organizers, and nonprofit directors can help. These collaborations can entail everything from informal exchanges to co-led projects.
But there's a catch. They require that people with diverse forms of knowledge and lived experience, who are often strangers, choose to engage with one another. We know that strangers often remain strangers.
That's why a science of collaboration that centers the inception question is vital: When do diverse individuals choose to work together in the first place? How can we design institutions that encourage beneficial collaborations to arise and thrive? And what outcomes can occur?
How Collaborations Between Researchers and Community Leaders Can Help
First consider the feeling of powerlessness. Individual action becomes more powerful when part of a collective. For ordinary citizens, voting and organizing are arguably the two most impactful forms of collective action, and as it turns out there is substantial research on how to increase turnout and how to build powerful civic associations. Collaborations between researchers familiar with that work and organizers and nonprofit leaders familiar with a community's context can be especially impactful.
For example, in 2019, climate organizers with a nonpartisan group in North Carolina worked with a researcher who studies organizing to figure out how to increase volunteer commitment—that is, how to transform volunteers who only attend meetings into leaders who take responsibility for organizing others. Together, they designed strategies that made sense for the local area. Once implemented, these strategies led to a 161% year-over-year increase in commitment. More concretely, dozens of newly empowered volunteers led events to raise awareness of how climate change was impacting the local community and developed relationships with local officials and business owners, all while coming to see themselves as civic leaders. This experience also fed back into the researcher's work, motivating the design of future studies.
Or consider how researchers and local elected officials can collaborate and respond to novel challenges like the coronavirus. For instance, in March 2020, one county in Upstate New York suddenly had to figure out how to provide vital services like internet and health screenings for residents who could no longer visit shuttered county offices. They turned to a researcher who knew about research on mobile vans. Together, they spoke about the benefits and costs of mobile vans in general, and then segued into a more specific conversation about what routings and services would make sense in this specific locale. Their collaboration entailed a few conversations leading up to the county's decision, and in the end the county received helpful information and the researcher learned about new implementation challenges associated with mobile vans.
In April, legislators in another Upstate New York county realized they needed honest, if biting, feedback from local mayors about their response to the pandemic. They collaborated with researchers familiar with survey methodology. County legislators supplied the goals and historical information about fraught county–city relationships, while researchers supplied evidence-based techniques for conducting interviews in delicate contexts. These interviews ultimately revealed mayors' demand for more up-to-date coronavirus information from the county and also more county-led advocacy at the state level.
To be sure, there are many situations in which elected officials' lack of information is not the main hurdle. Rather, they need an incentive to act. Yet this is another situation in which collaborations between university researchers and community leaders focused on evidence-based, context-appropriate approaches to organizing and voter mobilization could produce needed pressure.
This brings me to the third way in which collaborations between researchers and community leaders can strengthen American democracy. They entail diverse people working to develop a common interest by building new connections across lines of difference. This is a core democratic skill that withers in the absence of practice.
In addition to credibility, we've learned that potential collaborators also care about whether others will be responsive to their goals and constraints, understand their point of view, and will be enjoyable to interact with.
The Science of Collaboration
The previous examples have one thing in common: a collaboration actually took place.
Yet that often does not happen. While there are many reasons why collaborations between diverse people should arise we know far less about when they actually do arise.
This is why a science of collaboration centered on inception is essential. Some studies have already revealed new insights. One thing we've learned is that credibility is important, but often not enough. By credibility, I mean that people are more likely to collaborate when they perceive each other to be trustworthy and have useful information or skills to share. Potential collaborators can signal their credibility by, for instance, identifying shared values and mentioning relevant previous experiences. One study finds that policymakers are more interested in collaborating with researchers who will share findings that are timely and locally relevant—that is, the kind that are most useful to them.
In addition to credibility, we've learned that potential collaborators also care about whether others will be responsive to their goals and constraints, understand their point of view, and will be enjoyable to interact with. For instance, potential collaborators can explicitly acknowledge that they know the other person is busy, or start with a question rather than a statement to indicate being interested. One study finds that busy nonprofit leaders are more likely to collaborate with researchers who explicitly state that (a) they are interested in learning about the leaders' expertise, and (b) they will efficiently share what they know. Another study underscores that potential collaborators need to feel like they know how to interact—that is, to feel like they have a "script" for what's appropriate to say during the interaction.
We're also learning that institutions (such as matchmaking organizations) can reduce uncertainty about credibility and relationality, and also help collaborations start off on the right foot. They are a critical avenue for connecting strangers. For instance, brokers can use techniques that increase the likelihood that diverse people feel comfortable sharing what they know, raising concerns, and being responsive to others.
Looking Ahead
A science of collaboration that centers the inception question is helpful on two levels. First, it provides an evidence base for how to effectively connect diverse people to work together. Second, when applied to university researchers and community leaders, it can produce collaborations that strengthen American democracy. Moreover, these collaborations are easily implemented, especially when informal and beginning as a conversation or two (as in the mobile vans example).
Existing research on the science of collaboration has already yielded actionable insights, yet we still have much to learn. For instance, we need to better understand the latent demand. Interviews that ask a wide variety of community leaders and researchers who have not previously collaborated to talk about why doing so might be helpful would be enlightening. They could also be a useful antidote to the narrative of conflict that often permeates discussions about the role of science in American politics.
In addition, we need to learn more about the downstream consequences of these collaborations, such as whether new networks arise that include colleagues of the initial collaborators. Here, it would be helpful to study the work of brokers – how they introduce people to each other, how much they follow up, and the impact of those decisions.
Ultimately, expanding the evidence base of the science of collaboration, and then directly applying what we learn, will provide important new and actionable avenues for strengthening American democracy.
[Editor's Note: To read other articles in this special magazine issue, visit the beautifully designed e-reader version.]
DNA- and RNA-based electronic implants may revolutionize healthcare
Implantable electronic devices can significantly improve patients’ quality of life. A pacemaker can encourage the heart to beat more regularly. A neural implant, usually placed at the back of the skull, can help brain function and encourage higher neural activity. Current research on neural implants finds them helpful to patients with Parkinson’s disease, vision loss, hearing loss, and other nerve damage problems. Several of these implants, such as Elon Musk’s Neuralink, have already been approved by the FDA for human use.
Yet, pacemakers, neural implants, and other such electronic devices are not without problems. They require constant electricity, limited through batteries that need replacements. They also cause scarring. “The problem with doing this with electronics is that scar tissue forms,” explains Kate Adamala, an assistant professor of cell biology at the University of Minnesota Twin Cities. “Anytime you have something hard interacting with something soft [like muscle, skin, or tissue], the soft thing will scar. That's why there are no long-term neural implants right now.” To overcome these challenges, scientists are turning to biocomputing processes that use organic materials like DNA and RNA. Other promised benefits include “diagnostics and possibly therapeutic action, operating as nanorobots in living organisms,” writes Evgeny Katz, a professor of bioelectronics at Clarkson University, in his book DNA- And RNA-Based Computing Systems.
While a computer gives these inputs in binary code or "bits," such as a 0 or 1, biocomputing uses DNA strands as inputs, whether double or single-stranded, and often uses fluorescent RNA as an output.
Adamala’s research focuses on developing such biocomputing systems using DNA, RNA, proteins, and lipids. Using these molecules in the biocomputing systems allows the latter to be biocompatible with the human body, resulting in a natural healing process. In a recent Nature Communications study, Adamala and her team created a new biocomputing platform called TRUMPET (Transcriptional RNA Universal Multi-Purpose GatE PlaTform) which acts like a DNA-powered computer chip. “These biological systems can heal if you design them correctly,” adds Adamala. “So you can imagine a computer that will eventually heal itself.”
The basics of biocomputing
Biocomputing and regular computing have many similarities. Like regular computing, biocomputing works by running information through a series of gates, usually logic gates. A logic gate works as a fork in the road for an electronic circuit. The input will travel one way or another, giving two different outputs. An example logic gate is the AND gate, which has two inputs (A and B) and two different results. If both A and B are 1, the AND gate output will be 1. If only A is 1 and B is 0, the output will be 0 and vice versa. If both A and B are 0, the result will be 0. While a computer gives these inputs in binary code or "bits," such as a 0 or 1, biocomputing uses DNA strands as inputs, whether double or single-stranded, and often uses fluorescent RNA as an output. In this case, the DNA enters the logic gate as a single or double strand.
If the DNA is double-stranded, the system “digests” the DNA or destroys it, which results in non-fluorescence or “0” output. Conversely, if the DNA is single-stranded, it won’t be digested and instead will be copied by several enzymes in the biocomputing system, resulting in fluorescent RNA or a “1” output. And the output for this type of binary system can be expanded beyond fluorescence or not. For example, a “1” output might be the production of the enzyme insulin, while a “0” may be that no insulin is produced. “This kind of synergy between biology and computation is the essence of biocomputing,” says Stephanie Forrest, a professor and the director of the Biodesign Center for Biocomputing, Security and Society at Arizona State University.
Biocomputing circles are made of DNA, RNA, proteins and even bacteria.
Evgeny Katz
The TRUMPET’s promise
Depending on whether the biocomputing system is placed directly inside a cell within the human body, or run in a test-tube, different environmental factors play a role. When an output is produced inside a cell, the cell's natural processes can amplify this output (for example, a specific protein or DNA strand), creating a solid signal. However, these cells can also be very leaky. “You want the cells to do the thing you ask them to do before they finish whatever their businesses, which is to grow, replicate, metabolize,” Adamala explains. “However, often the gate may be triggered without the right inputs, creating a false positive signal. So that's why natural logic gates are often leaky." While biocomputing outside a cell in a test tube can allow for tighter control over the logic gates, the outputs or signals cannot be amplified by a cell and are less potent.
TRUMPET, which is smaller than a cell, taps into both cellular and non-cellular biocomputing benefits. “At its core, it is a nonliving logic gate system,” Adamala states, “It's a DNA-based logic gate system. But because we use enzymes, and the readout is enzymatic [where an enzyme replicates the fluorescent RNA], we end up with signal amplification." This readout means that the output from the TRUMPET system, a fluorescent RNA strand, can be replicated by nearby enzymes in the platform, making the light signal stronger. "So it combines the best of both worlds,” Adamala adds.
These organic-based systems could detect cancer cells or low insulin levels inside a patient’s body.
The TRUMPET biocomputing process is relatively straightforward. “If the DNA [input] shows up as single-stranded, it will not be digested [by the logic gate], and you get this nice fluorescent output as the RNA is made from the single-stranded DNA, and that's a 1,” Adamala explains. "And if the DNA input is double-stranded, it gets digested by the enzymes in the logic gate, and there is no RNA created from the DNA, so there is no fluorescence, and the output is 0." On the story's leading image above, if the tube is "lit" with a purple color, that is a binary 1 signal for computing. If it's "off" it is a 0.
While still in research, TRUMPET and other biocomputing systems promise significant benefits to personalized healthcare and medicine. These organic-based systems could detect cancer cells or low insulin levels inside a patient’s body. The study’s lead author and graduate student Judee Sharon is already beginning to research TRUMPET's ability for earlier cancer diagnoses. Because the inputs for TRUMPET are single or double-stranded DNA, any mutated or cancerous DNA could theoretically be detected from the platform through the biocomputing process. Theoretically, devices like TRUMPET could be used to detect cancer and other diseases earlier.
Adamala sees TRUMPET not only as a detection system but also as a potential cancer drug delivery system. “Ideally, you would like the drug only to turn on when it senses the presence of a cancer cell. And that's how we use the logic gates, which work in response to inputs like cancerous DNA. Then the output can be the production of a small molecule or the release of a small molecule that can then go and kill what needs killing, in this case, a cancer cell. So we would like to develop applications that use this technology to control the logic gate response of a drug’s delivery to a cell.”
Although platforms like TRUMPET are making progress, a lot more work must be done before they can be used commercially. “The process of translating mechanisms and architecture from biology to computing and vice versa is still an art rather than a science,” says Forrest. “It requires deep computer science and biology knowledge,” she adds. “Some people have compared interdisciplinary science to fusion restaurants—not all combinations are successful, but when they are, the results are remarkable.”
In today’s podcast episode, Leaps.org Deputy Editor Lina Zeldovich speaks about the health and ecological benefits of farming crickets for human consumption with Bicky Nguyen, who joins Lina from Vietnam. Bicky and her business partner Nam Dang operate an insect farm named CricketOne. Motivated by the idea of sustainable and healthy protein production, they started their unconventional endeavor a few years ago, despite numerous naysayers who didn’t believe that humans would ever consider munching on bugs.
Yet, making creepy crawlers part of our diet offers many health and planetary advantages. Food production needs to match the rise in global population, estimated to reach 10 billion by 2050. One challenge is that some of our current practices are inefficient, polluting and wasteful. According to nonprofit EarthSave.org, it takes 2,500 gallons of water, 12 pounds of grain, 35 pounds of topsoil and the energy equivalent of one gallon of gasoline to produce one pound of feedlot beef, although exact statistics vary between sources.
Meanwhile, insects are easy to grow, high on protein and low on fat. When roasted with salt, they make crunchy snacks. When chopped up, they transform into delicious pâtes, says Bicky, who invents her own cricket recipes and serves them at industry and public events. Maybe that’s why some research predicts that edible insects market may grow to almost $10 billion by 2030. Tune in for a delectable chat on this alternative and sustainable protein.
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Further reading:
More info on Bicky Nguyen
https://yseali.fulbright.edu.vn/en/faculty/bicky-n...
The environmental footprint of beef production
https://www.earthsave.org/environment.htm
https://www.watercalculator.org/news/articles/beef-king-big-water-footprints/
https://www.frontiersin.org/articles/10.3389/fsufs.2019.00005/full
https://ourworldindata.org/carbon-footprint-food-methane
Insect farming as a source of sustainable protein
https://www.insectgourmet.com/insect-farming-growing-bugs-for-protein/
https://www.sciencedirect.com/topics/agricultural-and-biological-sciences/insect-farming
Cricket flour is taking the world by storm
https://www.cricketflours.com/
https://talk-commerce.com/blog/what-brands-use-cricket-flour-and-why/
Lina Zeldovich has written about science, medicine and technology for Popular Science, Smithsonian, National Geographic, Scientific American, Reader’s Digest, the New York Times and other major national and international publications. A Columbia J-School alumna, she has won several awards for her stories, including the ASJA Crisis Coverage Award for Covid reporting, and has been a contributing editor at Nautilus Magazine. In 2021, Zeldovich released her first book, The Other Dark Matter, published by the University of Chicago Press, about the science and business of turning waste into wealth and health. You can find her on http://linazeldovich.com/ and @linazeldovich.