One of the other classes I'm taking in the Ford School of Public Policy, PP750, is called the Psychology of Climate Change and it goes over a lot about the content of these communication techniques - but here, I got the unique opportunity to look at these tactics from an information processing perspective.
We mentioned the idea of using stories to communicate today in class. In PP750, we also talked about the use of analogies (like stories) being helpful to communicate complex ideas - especially when it comes to really mathy things, like, "how much CO2 can we dump into the atmosphere before we're completely overloaded?"
In a study that tried to address people's misconceptions about this topic, researchers developed an analogy that compared the atmosphere with a bathtub filling with water. In the late 1990s, a simulation was built so people could play with it themselves. Below is a picture of the interface.
Yes, yes, it's not pretty - and it's not very preferred (it is originally from 1997!). While it's not perfect and could use some updating, I think the benefits of this kind of simulation outweigh its crude design. A person can play and pause the simulation as they'd like, to take in the information at their own pace. They can go back and start over - and more importantly, when the simulation hits 2007, they can control in three different ways: they can allow increased CO2 emissions, level off emissions, or reduce CO2 emissions. While they can't determine how much to increase/reduce by, the "reduce" option shows the bare minimum we need to stay at 450ppm (parts per million), which has kind of been our "doomsday" number. If you want to play and mess around with the simulation yourself, you can do so here!
In 2013, another study was done based around this idea of comparing the atmosphere to a bathtub. The groups for the study were: control (information about CO2 accumulation with no analogy or graph), information with the analogy only, graphical representation only, and analogy with graphical representation (Guy et al., 2013). It was expected that within the general public, that the combination of the analogy and the graph would be the most helpful for comprehension - however, they found that analogy only was actually the most effective tool for communicating this issue (Guy et al., 2013). Just the presence of the graph seemed to have an adverse effect on people's comprehension (Guy et al., 2013).
I think this is a big indicator for how we need to communicate these issues, even if it makes the job a little tougher. Although a lot of climate science comes from mathematical models and data, we need to translate these things so everyday people can understand them, and that may mean even tossing out the things many scientists hold near and dear; like graphs. We want to think that the data, presented graphically, can be considered legible and only take "common sense" to understand, but I think that even that is still too deep into our expertise.
Of course, translating that hard data is only half the battle. We also need to get people to genuinely care about the issue, and frame it not in just a way that they can understand, but so that they take this knowledge and turn it into action.
But... I think, for now, we should take one step at a time.
Reference:
Guy, S., Kashima, Y., Walker, I., & O’Neill, S. (2013, October 17). Comparing the atmosphere to a bathtub: Effectiveness of analogy for reasoning about accumulation. Climatic Change, 121(4), 579-594. doi:10.1007/s10584-013-0949-3:
Thanks for sharing these examples! I've been thinking a lot about how expertise negatively affects different disciplines, whether it be climate science, economics, policy, etc. It seems like the expertise excludes many people from the conversation by creating a high barrier to entry with understanding information. I find it interesting to think about how in SNRE we have to take analytics and statistics courses to build our "toolkit" of understanding different kinds of information and data. Yet this makes an assumption that we will need to have analytic frameworks of these kinds to be effective change makers and will encounter them in our work. Moreover, while these tools may help us understand what other researchers and experts have found, the real question is whether they can help us explain concepts more easily to the public and enhance work in communities (if that's your focus). It can't just be unidirectional, and I would hope that these courses also emphasize the role of translation in any discussion of analytics. In general, most graphs fail to meet any of the guidelines shared in class on Monday: starting where people are at, invoking imagery, not overwhelming people, creating preferred or restorative environments, making it easy to tell a story, or developing coherence. Given the data above that analogies work better than graphs, maybe another take-away here is that it's not just what or how you share information but WHO you share it to. For experts, graphs may fit naturally with their mental models, but for everyday people, we need to focus on images and concrete portrayals of situations that are relatable. On the flip side, do we ever think about the power dynamics of disseminating information in the other direction? Community testimonies often aren't taken seriously because they tell personal stories instead of "selling" an expert audience with data (which also gets at the legitimacy debate of quantitative and qualitative methodologies). I feel like instead of making either group learn a new way of thinking, perhaps there are universal mediums like stories or other frameworks where people can meet in the middle and have a conversation using the same language. We can still recognize that everyone is an expert in something without it hindering our ability to communicate effectively.
ReplyDeleteThanks for sharing this interesting information and your personal experience. The reality that experts are often bad at sharing their expertise resonated with me as well on multiple levels. A couple specific things came to mind for me:
ReplyDelete1) Framing, including sharing information through analogies, is a powerful tool to share information. But it also has its limitations across cultures which is a point I am often thinking about in my global work. Translation is also an important aspect that may possibly elude the expert seeking to reach a global audience. For example, the bathtub analogy likely won't resonate with a village in Senegal. Granted, this wasn't the intended audience but I often find myself thinking about how the great tools we develop can get shared broadly.
2) The other thing that came to mind was story telling and capturing these stories from experts who are not always perceived as experts. People's lived experiences make them their own expert and story telling is an excellent way to capture their expertise. The Most Significant Change technique is a qualitative evaluation method to capture change through story telling. This tool seems to me like an example of design that engages and communicates across experts (lived experience experts with donor/funding experts). It's a great technique if you aren't already familiar with it that engages us as information processors.
Interesting topic, Katelyn!
ReplyDeleteGoing back to monday's class material, the bathtub analogy seems to address in multiple ways the types of information humans favor on learning processes:
- The graphical nature of the informations presented is inherently fascinating
- The information is presented in a visual/spatial fashion
- The bathtub analogy places the information in a familiar setting
- The information is coherent and legible
- The presentation is complex enough (you can try multiple scenarios) and the outcome of the different scenarios is mystery until one tries them in the simulation.
From there, it follows the guidelines tha Katie described. Ultimately, then, it is an appropiate way of sharing information with non experts.
I find it curious that the participants in the Guy et al. (2013) study found that only the analogy was helpful in understanding climate change, and that the graph/analogy combination was not most helpful. It's even more curious that the graph actually inhibited people's understanding of the science. As Nicolas said, data visualization can be inherently fascinating. However, I suppose it primarily depends on if the graph is a preferred information environment.
ReplyDeleteIn one of my previous jobs, my office struggled with presenting information graphically in a way that was both accurate and visually intuitive. Often, when we gravitated toward including layers of detail, the graph became an eyesore, hard to distinguish, and difficult to understand. I imagine it would especially feel difficult to comprehend for members of the public to interpret if they did not already have an extensive scientific background to draw upon. Unfortunately, it seems that adding the detail that experts appreciate can impede the graph's legibility and coherence. It sounds like this may be what occurred during the Guy et al. (2013) study.
Thanks for sharing your motivations, Kaitlyn! My undergrad degree, Engineering Management, comes from a similar space: bridging the gap between non-engineers and engineers.
ReplyDeleteThe science-public interface discussed here and the background I come from share many of the same issues. I too found it curious that the addition of a graph decreased the participants understanding - like Jessica noted, it could be that the details that experts found worthwhile overwhelmed the non-experts. It is difficult to strike a balance between what we, as experts, find relevant and a selective presentation of the facts that still gets the point across, even if it leaves out some of those details.
Overall, I think what "science" needs at this point is a really good PR manager. Bill Nye, Neil deGrasse Tyson, and Carl Sagan, to name a few, (apologies for my lack of knowledge of female contributors to scientific communication) have made great strides towards making science more approachable, but nobody has really tried to make it "sexy". When I say that, I don't mean it in the literal sense - what I mean is the glossy, front-page, graphic-designed treatment that pop culture has come to embody. We NEED that for science, but we also need to balance that with staying true to facts. I'm not really sure how we toe that line, but it's been done before. Science use to be COOL. Look at the second half of the 20th century. Look at the home science kits. Experiment books. Look at Popular Science and Popular Mechanics. Science Fiction. 2001, A Space Odyssey. These things were created in response to demand. There was mass appeal to science, particularly space.
I think we need to figure out what we were doing then (government propaganda certainly played a role, e.g. "the Space Race") and find ways to apply it to climate change.
Thank you! This are many very interesting idea in your post. I can’t agree more that the use of analogy and simulation are really helpful in expressing abstract concepts or scientific concepts.
ReplyDeleteRegarding the concept of climate change. The name “greenhouse effect” itself is one great example that using analogy to deliver massage. This concept definitely helped to understand the concept of global warming even when I was in seven grade. We can recall many concepts that are named by analogy. For example, like hedgehog dilemma: when two people get to intimate and close, it hurts.
The mechanism behind the analogy is that it facilitates understanding by linking new concepts to already existed IR or the network of IR, cognitive maps. It also makes sense that attach the new concepts to the cognitive maps rather take time building a new one will help the public to immediately understand. Professor Hofstadter also pointed out that no matter what forms of information has being shared (visual images, listening to stories), as long as they activate the interrelated concepts, further concepts will be bring up to the surface. (Link:https://prelectur.stanford.edu/lecturers/hofstadter/analogy.html)
What an important post and discussion, thank you for sharing this, Kaitlyn! I feel so much related to this.
ReplyDeleteFor the last six years before went back to school, my job was exactly in this situation, bridging the gap between expert and non-expert, and I can reflect so much on the last week module.
One thing that is hard from non-expert to understand is the experts' obsession to data and fact. Not to say that data and fact is not important, of course it is important, but from my experiences I learn that data and fact is not the most appealing for non-experts' internal representation, and even if the non-experts learn something from the data, like Erin said, learn something doesn't mean they will do something. Know more just mean that they learn more, and it doesn't always have a direct relation to an action, or trigger an action. For example, environmental NGOs in Indonesia really love to translate the complicated forest loss data into bite size data for the audience and rephrase it into "we lost the paradise forest as much as 20 football field every second due deforestation", with the expectation that people will feel more relevancy. Using this data, we might be successful to make people shocked and learn about how big the forest loss is, but this kind of information will not stay long in their cognitive map, perhaps because it has no direct relevance to them, they don't know what the alarming rate is, and even if it is at alarming rate, so what? The same thing when we say climate change is happening, and then mention about the city that you live in is going to sink, it might mean nothing to non-expert as (1) the bigger the problem is, the less useful our action look like, (2) gradual and future effect will not make people feel the urge to think that this is important. Thus, as Missy say, story telling is important, we need to develop a narrative to make non-experts understand.
The importance of narrative to make the data stronger and relevance for non-experts was brought up by a lot of Slovic's works. This is well explained by the say: a single death is a tragedy, a million deaths are statistic. Statistics and data won't move non-experts, but once we put a name on a face, it will trigger them to take action. For example, on donation case, when we could bring the data and narrative all together "A little girl named Aisyah lost her house, and both of her parents due to a huge tsunami in Aceh. She and 655.000 other people need your help." Narrative (story telling) is important to make the data becomes emotionally appealing and relevant for non-experts so they are triggered to do something. However, most of the time it is harder to convince the so-called experts that we need to twist and put narrative for the message to public, because non-experts don't need the whole data, or even too much data will not be effective.