PostNormal Times: Journeys in Truth-Seeking

PostNormal Times is a podcast for our complex reality and unpredictable world—a world where the stakes are high and innovation is crucial. Andrew Vosko, PhD, associate provost and director of transdisciplinary studies at CGU, and his guests explore ideas that transcend traditional academic boundaries and address our most pressing needs. Get ready to challenge your assumptions.

In episode 2 of PostNormal Times, Andrew Vosko and Gwen Garrison, associate professor at the School of Educational Studies, discuss her truth-seeking trajectory from theology to data science. What can neuroscience, software, and grandfather clocks teach us about how to be transdisciplinarians? Listen to the full episode below and subscribe via Spotify, iTunes, or RSS.

ANDREW VOSKO: Welcome to PostNormal Times, a podcast for our complex reality and unpredictable world, where stakes are high, and innovation is crucial. In this series, I get to sit down with some of my favorite minds to explore new ideas that transcend traditional academic boundaries and address our most pressing needs. I’m Andrew Vosko, associate provost and director of transdisciplinary studies at Claremont Graduate University. Welcome to the show.

I’d like to welcome everyone today to a podcast where we don’t discuss business as usual, but discuss the world in a transdisciplinary context.

I’m very, very happy to be introducing our guest, Gwen Garrison, a faculty member in the School of Educational Studies at Claremont Graduate University, who has a fascinating story, a really cool history, and who is a wonderful conversation buddy that I have known since she came here four years ago.

But you were a Claremont regular, you’re an OG, right?

GWEN GARRISON: Yes, I’m a grad.

ANDREW: So, that’s a story. I always like our guests to tell a little bit of where they’re coming from. Because whenever I look at a CV, I don’t do it justice. There are always three points that always stick out: Where did you do your undergrad, and what was your PhD in? Those kinds of things. But yours is already interesting, and I know a little bit about you, so I know it’s way more interesting than the “three points.” And so I want to know how you came to Claremont as a student first: What brought you here? And then, how your life and career trajectory went forward from that experience and how it took you back. But you don’t have to do the “dark and stormy night” for us – just get us acquainted with what’s so cool about you because I know you’re really cool.

GWEN: Thank you, and wonderful to be here, Andy, so thank you for inviting me to the podcast.

So, I think there probably are two or three characteristics that define both my academic path and life journey. The first one, I would say, is someone who cared about words and truth through both of those. That sent me from high school into college to do a BA degree in English and English literature – largely trying to find the metaphors in life that actually help us understand our reality and how to make meaning out of it.

But, looking back, I can see this trajectory that really came through my family. I came from a family of lawyers, small-town lawyers who were just trying to make a difference. All of my family has been involved in public service of some kind, so we have a real sense of conveying the truth in the community so that it matters and changes lives. So, that’s a trajectory that ran all the way through my master’s degree and then subsequently my doctorate degree: trying to find meaning, and truth-making.

And interesting side note about this is in my doctorate, here, at Claremont. I, of course, did things like higher education and systems dynamics and understanding broad kind of strokes of things. But I really leaned into the methods and I took a lot of quantitative and qualitative methods – now we call mixed methods – and I had previous kinds of ways of looking at things. So, they gave me a lot of lenses. And when that started – that really is where I see the transdisciplinary approach coming through – so, being a truth-seeker, finding it in the first levels of evidence, and learning how to process that.

Then, the third I would say is that I’ve always had a passion for what we call data storytelling: How do we bring visual evidence because that’s how most of us kind of approach evidence. We don’t approach it like my dad approached it as a lawyer, who is reading difficult texts, but we approach it from the things we see and what our mind makes sense of. And so I’ve always had an interest in how we make charts, graphs, and maps much more accessible.

And I take that one all the way back. My favorite thing to read when I was a young child was National Geographic. I could not wait to get the National Geographic. I couldn’t understand half the text, but it was a picture book that told beautiful stories through pictures, images, and graphs. And the charts made sense to me – even as a young person.

Being a truth-teller, getting that going, understanding the way to do data storytelling – that’s where I’ve arrived at. Now, how do I teach the next generation to do that?

ANDREW: That’s so fascinating. There used to be a group of us who’d get together over happy hours and discuss the secret sauce of humanistic training. I was an Asian language and literature major as an undergraduate, and that’s the first way I think about things when you are talking about storytelling and making sense of narratives. For me, it was about foreign language acquisition. That’s how I always thought about everything. That made me preoccupied with how I make sense of something. It’s Japanese; studying Japanese is so very, very different than studying English. And there is this kind of learning curve. At some point I realized that for everything I had to suspend disbelief, I realized that there was a very core connection: If I started off trying to translate everything from my space of comfort, then I’d miss half of the nuance and most of the cultural context and all of these other problems of the direct translation. But if I assumed everything was just so out there, that it was a clean slate, then I also missed the underlying human things that linked us. So, understanding my own understanding of that has driven me to be preoccupied all the time with how meaning is made in different spaces and how stories are told very differently but make sense in the end because we’re all human.

As a scientist, it’s one of the things that made me love writing reviews and integration. I love a lit review; it’s one of my favorite things to do. I hear students all the time saying, “I have a lit review to do, oh my gosh, it’s terrible!” But it’s my favorite thing to do because it’s the sense-making process of this world.

It’s too bad you weren’t in that happy hour, but I’m going to invite you informally to start doing this again, because I think these kinds of conversations are so fun and they speak to the boundary crossing that really shapes our lives. Because,you don’t just kind of do methods, you really do methods! You’re an expert in methods, and you do this mixed method thing extraordinarily well, and you are hired to do these mixed methods and for very, very large organizations across the country, and possibly, internationally?

GWEN: I have done internationally.

ANDREW: So, you understand this one side that is very much based on narrative; you integrated this into something that we tend to unfairly call “left brain / right brain” kind of stuff. I’m always fascinated by people who find themselves in these spaces. Was your mindset always one that was, “OK, I’m game for this, this is cool”? Was there someone who really changed you? And was there an instance that made your outlook really change in life? How did you get there? Were you somebody who had a transdisciplinary mindset?

GWEN: Yes, I would say that. I would also say that as a woman, there was a very conscious decision that if I wanted to access the conversations at the table where decisions were being made. I had to get the advanced degrees in order to get access to the table. In other locations and times that wouldn’t have necessarily been part of the journey for that many people. I think it’s opened up now, and I feel myself part of the generation who raised the path. So, let me tell how I got from CGU to Washington DC, and being part of several large educational associations, and now working with many of those associations that I still work with as part of my consulting. When I do my consulting work, I always can bring a student along with me; I make provisions for that, so they get to learn on the job.

There’s a wonderful thing about educational studies – so not just education, but educational studies – itis truly a field that borrows the disciplines and thinking from other fields. That really served me personally, it fit me, it said that I’ve got to go learn whatever I need to learn in order to make this work. Education is framed a lot by psychological processes, which are datasets of 100 to 200 and usually direct collection. And there was little emphasis on working with what we typically call now administrative data. But our organizations are awash in administrative data and there are so few people who are harnessing and making sense of it and so to actually start working with administrative data, I had to learn economics, I had to learn a bit of political science, I had to learn a bit of sociology. And my work in Washington DC took me to the Census Bureau. I had to learn how to talk with demographers about personal characteristics and how do we collect them, and the craft of actually writing a good survey question that gets many people to participate, not just a few who understand the question through the process.

So, all of those things is the opening to the transdisciplinary: I needed – to use the metaphor we often use – I needed lots of things in my tool belt besides methods. I needed lots of conceptual frameworks to actually approach these problems and actually move data across systems so that we could see the pictures and stories it was trying to tell us. To this day, I’m the only one who has access to certain kinds of data on faculty that puts their compensation and studied their progression in rank, and what were the barriers to compensation and progression and rank at the major educational industry sector. … And I had to do that with data coming off of six major systems, linking it all together, where we have over 200,000 cases. It takes a lot of savvy because everything can be at that point, everything can be statistically significant, but it’s not meaningful.

ANDREW: Right.

GWEN: I had to learn about things like effect sizes, which is something that sociology makes a lot of use of, or industrial psychologists make a lot of use of, but not necessarily psychologists because we don’t deal with data systems that big. So, I had to keep going in my methods and I had to keep learning different tools, mindsets, and ways of seeing how meaning-making is constructed from other areas for me to see. And so it was partly ambition. I’d say the other part was a fear of failure, getting the interpretation wrong because I did not open myself up to another way of seeing.

ANDREW: You were always very motivated to meet the needs of whatever the task was asking of you. And was that very organic for you? You always could see it very clearly: “OK, here’s the problem, here’s the answer, here’s how I learn it.” Did you have that confidence that you were just capable of learning all these things? You know, some people say, “Don’t ever give me a paper to write or don’t ever give me a dataset. I can’t deal with computers.” People have very clear boundaries in their own heads of what they’re capable or willing to do, and some people are a little bit more likely to cross those. It doesn’t sound like that with you. Am I right in assuming that?

GWEN: I would say that by temperament I’m up for a challenge. I’m not easily intimidated by hard things. I can’t exactly tell you where I got that confidence from. I think it was driven by just survival. I came from a chaotic family system, and in order to actually make it through that family system I had to keep sidestepping things and moving around things, keep learning resources that I needed to have. So, I think that might have been part of it.

There’s a short little story that I’ll tell that kind of sets up this mindset. My uncle made my mother a grandfather clock, it’s a beautiful clock, and for whatever reason it did not keep time correctly. So, I’m 16 years old and I think, because I had taken apart engines and put them back together and fixed them, I have natural, mechanical stuff in my fingers.

ANDREW: I could never… if you want something to never work again, you should give it to me. I appreciate people who can do that.

GWEN: So, I decided I’m going to take apart the mechanisms of this grandfather clock because I think I can figure out what is the thing that needs to be tweaked. So, on the dining room table, I carefully take it apart in sequence, moving all the way around the dining room table. Three hours later, I can’t get this thing back together. My mom was away at work and I come back and I’ve got pieces left on the table that came out of the clock, that are no longer in it. I was mortified because we didn’t have the money to actually hire somebody to come put this back. But my mother had to spend the money, had to call the clockmaker to come and put this back. He laughed and  said, “Honey, you know, this thing is a very complicated machine.” So, to let you know that it was a bit of wanting to help, but also this kind of hubris, that I could figure out how to understand something if I just sat with it long enough. That clock my mother has bequeathed and sits in my house to this day to remind me to be humble about things I don’t know, to ask more questions, and to ask for help when it’s not in my wheelhouse. So, I pass that clock when I leave the house, and when I come in it greets me to remind me how to do today.

ANDREW: Humility is such a big deal. I, like you, used to work with some organizations involved with – in fact, we worked for the same organization, although in parallel paths and in different ways at the same time – and that was for the Association of American Medical Colleges. One of the areas that I worked in was inter-professionalism when I was in medical education, and I know that you have some background working with all these different areas yourself. Inter-professionalism is a pretty close cousin to transdisciplinarity: It’s how you get a physician a nurse and a pharmacist to work together well. At the time that I started getting involved with this – my pathway to transdisciplinarity was inter-professionalism; that was my doorway in – even though I had these different kinds of experiences. I found that one of the things that was coming up over and over again in the simulations we were trying, or the pointers we would give to students, was that identity was a really big deal, and kind of an epistemic humility was a really big deal. But understanding epistemic potential was also a really big deal, and capacity.

So, for instance, if I were a nurse, I would come in the room and say, “I am the care expert. That’s what I do: I speak in the language of care. I care for the patient. I care for the patient’s family. I can translate all care needs to the physician and to the pharmacist and whoever.” And the physician would be like, “I am the diagnose, that is my gift.” And people would come in with these ideas of, “the physician is …,” “the nurse is …” And , “My ability to do this stops as an anesthesiologist, and when I need to do a consult with a neurologist, this is where it stops …” But then you come into a situation where someone’s crying, and the medical student would say to the nursing student, “Can you please get them a tissue ….” Like, wait a minute! You could give them a tissue too – understanding your identity as a profession but also understanding yourself as a human. And you don’t have to stop at one just because you have another. And a lot of people had trouble with that. That kind of translated in this transdisciplinary space: that you’ve got a lot of knowledges inside of you, and you might be an educational specialist, or you might be a linguist, or a literary scholar, but you’re also a spouse, you’re also a grandparent, you’re also a child. You have these different knowledges that are in you, and that trick of being able to use these in an integrated way is one of the things that sets aside the transdisciplinarian from somebody who’s just kind of lost.

There’s a pejorative idea that the person is a forever student. I think it’s so wrong to say that. Because you could be a forever student if you don’t have a grounding. But when you have a grounding and you can integrate these different things into each other, then you’re kind of invincible, then then you can take apart a grandfather clock. No, it’s not the end of the world, because you will get there and because you can ask other people when you need to, you can also learn from them and turn that into you, so that you don’t have to think of this as a journey for someone else, but you understand how they fit into your own growth as well. I think that having that understanding makes somebody in a clinical health world unstoppable: They can both give a tissue and diagnose and it’s totally fine, and then you get great ratings as a physician.

But on the other side of it, that humility takes you into a new place, too, because you’ve learned so much from having that kind of humility. I’m saying this all because I think there’s another component of you that I wanted to get to and that’s that you have a background in theology as well. This is so cool, because in the transdisciplinary world – and Basarab Nicolescu talks about this early on; he says there are all kinds of knowledges that we have, and imagination is a form of knowledge – your belief system is a form of knowledge. Understanding theologically how the world works is a form of knowledge. We prioritize different knowledge in different ways depending on what the context calls for. But we have a tendency to default prioritize in ways that might not necessarily be fair for certain situations, because we think there’s one there’s one version of reality and that’s what exists for everybody at the same time.

But that’s not the way knowledge works. You have to access the levels as you need to access those levels, and we share in some of those levels and we don’t share in some of those other levels. So, theological knowledge is a really interesting one, because sometimes it’s involved in an academic space, sometimes it’s not involved in an academic space, sometimes it’s involved with a personhood space, sometimes it’s involved in a relationship space. How do you relate that training in the theological space to the training that you provide the people here at CGU, or to just the way that you go about getting knowledge in your life?

GWEN: I think I would answer that first as the motivation that sent me to theological training and then how that motivation and grounding persists in what I do today. Like I said earlier, the ability to see the truth and seek the truth, was fundamental inside of me. I think there’s a family component that was nurturing that along the way, and so I wanted to understand how people,  clergy in particular, made sense of the world, especially around the sense of suffering. I needed to have a way to understand that piece and I needed to have a way to understand ethics or how then shall we live. I went to theological school. I didn’t always get the answers that I hoped I would get there. That’s partly why I don’t always talk about this. My theology and ways of perceiving the human condition have evolved a great deal since 30 years ago in the theological space. Part of that was that I have grown to understand that there are more ways to access the divine than just the way I grew up or the way that I was socialized into that space and that there are ways I can connect to people in that area than just a prescribed way of knowing that area but a much broader sense of that piece. And that has served me for the last 30 years of my life. First is, understanding that “Gee they’re not so certain about the answers that they think they have”  and that there are actually more ways to do the interpretation of the sacred literature than what I was always exposed to through that piece. And again, it’s that openness of allowing the text to come to me rather than always imposing a structure on top of that, so that kind of fundamental temperament runs through.

Where it serves me today is primarily how I view work and people, and that is relationships come first. The rest of the work will get done and it’s up to me to have a strategic mind to make sure we always – as I tell my students, we’re going to start in Los Angeles and we’re going to try to get to San Francisco, but there’s at least three routes we can get there and we’re going to go between those routes. So, it’s my job to keep the human in front of me while we’re making the journey to San Francisco. And I applied that in my course thinking. So, it is it’s about being open to connect with the individuals who are there where they are at, how they present and come to me, and to remain open to that relationship and how it works.

Like you, I would say probably the most unsettling time that we’re in right now for the last four or five years is that many people have shut down. You can’t arrive at that authentic space.

ANDREW: There are two things that are coming back: One of them is humility. There’s something about the value of humility – certainly an intellectual humility that keeps following you through whatever you do. The other I didn’t mention yet, and that’s your capacity to see through perspectives – you said lenses before – that you can get there different ways. It speaks to this transdisciplinary idea of inter-perspectivity. The idea of inter-perspectivity is that you’re capable of assuming one lens to look at something, but once you identify what that lens is by its very nature, you’re also identifying that it’s just one degree out of 360, so that there’s 359 other ways to look at what you’re looking at – I mean not exactly that per se, but, you know, the metaphor works because you realize that you’re just one and that the reality is much larger than this and you have the capacity to move across them if you want to move across them and it has the advantage of going from one degree. It’s certainly worthwhile to do that. Our knowledge tells us that, but you also realize by you admitting that you’ve done the one degree that there’s a lot of others there that also need to be looked at for you to understand this truth.

I wonder if your students get a sense of that appreciation for inter-perspectivity when they take your classes on data visualization or on the eval curriculum that you’ve put together. Did they have this kind of really sophisticated opportunity to appreciate the inter-perspectivity of data the way that you carry this in your life?

GWEN: Well, I certainly hope that if it’s not directly understood, it’s indirectly caught. But I also would say that the more advanced students have been working in and around data, they get that much quicker, that having multiple tools in the toolkit in order to look, gather, combine, and see data is almost imperative now. You just can’t come at it with just one piece. So, I hope that they do. I hope that over the four courses, they have those aha kind of bringing it all experience. That’s what the practicum for the degree program is designed to do, is to draw it all together. So, by the end, if they’re one of my students then, they’re arriving there and then they build on that.

ANDREW: I know your students. It’s a loaded question because they’ve worked with me before. They’re fantastic. They’re so skilled at doing this kind of thing. I am curious about your own journey along data and if the idea of data that you had and the kinds of data that you worked with from the time you started doing this kind of work in the space between education and evaluation – the mixed methodologies – if data changed. I don’t think the term big data was very popular 30 years ago, and now I mean saying things like microdata, on the other side of it, also wasn’t even worth mentioning in the same way. So, what has that been like for you to see the change, and what do you notice for the trends? What you see is important for us to understand – because we are in a data world right now, and that’s an opaque term to me. It has an association with The Matrix, but that’s not necessarily beyond a metaphor that I could really describe easily. You’re in it. You’re teaching people to live in it. You’re teaching people to make ethical decisions within it and be leaders within it. So, what do you notice?

GWEN: So, one of the tools in the toolkit is what information technology tells us about how to work with data because much of data now is digitized. And when it’s digitized, it allows us access in ways that we didn’t have before, because computers can do heavy lifts of it. But it also is challenging to work with because we don’t necessarily have all the structures that we need to thread the conversation within the data.

So, information technology tells us there are basically two buckets of data: There’s structured data and unstructured data. Structured data is something that in my training I am very used to. We’ve pre-coded it in a survey in order to expedite our analysis process. And so, it’s structured in a way that we can take in a complete phrase of something and give it a numeral because computers are really good at working with numbers, and if we have done that structure well, our analysis can be very powerful. The part that we’re all struggling with – and computers are very fast and they can make a lot of progress in that – is in the area of unstructured data. Unstructured data is any form of text that hasn’t got a code. You have to look at it – and this is where the human mind is actually pretty good at making sense of things. You look at it and we can go, “Oh, they’re talking about how their customer service experience was terrible or was terrific,” but we have to actually code computers to make sense of words and word patterns. We call that natural language processing, but unstructured data is also audio recordings and video recordings. How do we make and grab sense of that? Or entire Twitter feeds that we have to figure out? What is this conversation really illuminating? Because people say things that are quirky. We try to say things that are funny and people [react} and we move right on from that. So, that’s not the text we want to capture or code, we just want to know that somebody’s trying to introduce a little levity.

So, what we have in the challenge is we have a lot of unstructured data that is in one system or one compartment, or even structured data that are in a particular system that cannot talk easily or be combined with another system of data. So, one of the big efforts in the IT world is what we call interoperability, or the ability of data on one side of the system to be moved and used in another system. And if we concentrate on the core system, that’s where the truth is. For instance, in the educational setting, it’s our student information systems. That’s where we want people to tell us their names and it’s their data. They own it. And then we can move it to another system to support the analysis and work in another system and combine it with other things. Our systems are built with engineers, software engineers, who architected those things very differently.

I’ll give you a typical example: When I was working with a lot of software engineering, our primary system had a character limit for a last name of 25 characters. That pretty much destroyed anybody with an Indonesian name background.

ANDREW: Or hyphenated name.

GWEN: And so they would migrate over to another system and they would appear there as not whole. And they experience the data as not whole, like, “Please stop referring to me as this … I’m really this. … And “Can’t you change that.” And so it took a while. This is where our software engineers had to catch up with the reality of the impact someone’s own data has when it’s mischaracterized and how we solve that. So that led me on this journey to how do we get better data that really reflects and improves the quality of our decision-making as we connect across systems. And that primarily is my work now, trying to hook these things up in better ways across systems to tell better stories and to tell truthful stories.

ANDREW: There was a class that was taught on big data through the Transdisciplinary Studies program a couple of years ago, and there’s a conversation around ontologies. Now, I had never learned ontologies in an information technology paradigm before. I learned about this in a philosophical paradigm.

We were referring to ontologies as the language that’s used to code for what’s possible in one information system versus another information system. And that was one of my big aha moments, to realize that the problems of translation between information systems aren’t all that different. They’re nice models in a lot of ways for problems and information between people. Because if your reality is one way, and my reality is another way, which, of course, it is to a certain extent, there will be things that we share and there are things that I will never really know the way you know them and vice versa. Some kind of translation has to happen.

Having studied foreign language as my major area  comes back into play and being, like, “Oh, this is a convergence of a lot of disciplinary ideas.” There’s a philosophical, there’s a linguistic, and there is an information systems way of looking at it. And there’s the “one degree” I can look at. Now, I’ve got three of those degrees to start trying to triangulate around what it is that would happen in there. And it was really an appreciation of information systems with the piece that was missing. Let’s say this is all the same kind of problem-solving that we do.

This is what a therapist does when they have a client who’s coming in to try telling about their world when they’re empathizing with them. It’s almost the same kind of thing that you have to do when you’re trying to get datasets to make sense to two different systems. That was this wow moment for me. We can manufacture them, and realizing that we can manufacture them, do we have the capacity in our interpersonal relationships to create reality translations the same way we can do in an information system?

GWEN: I think it’s complicated. Both are complex and it is totally complex and complicated.

ANDREW: So, we’re in a world of data and it’s a very interesting observation you made that this is one of the main areas of this translational problem, where, how do you get things to fit together? But I’ve had so many conversations with you that are around the space of change, of what’s the next thing coming, and what’s preventing good from happening, and, you know, what’s keeping “old” in. Does it have to be changed? How do we maintain the things that we want to maintain? What got you interested in change?

GWEN: Change is hard, and some of us – I think, including me – are forced to adapt because of certain realities, ­either to adapt in positive ways or try to avoid certain things happening. Again, it’s kind of like, “Oh, the stove is hot. I shouldn’t touch the stove again, and can I make sure I recognize all manner of stoves and not just the one that I grew up with.” I think for me, in this data storytelling, one of the things that I had long conversations about in the meta space is, how is it that you can tell people, for example …

I had a colleague who studied smoking cessation. So, you can tell lots of people smoking is bad. It hardly changed smoking rates. But when they were able to make it personal, able to make a connection with it, then they started to see positive movement and that people were just not wanting to be another statistic. Well, of course, but people don’t think of themselves as a statistic, so that’s a way we aggregate to try to make sense of the problem. But that isn’t the way the story actually is grabbed by someone.

So, I think it partly was studying that piece and learning from people in the public health arena about what are the drivers for change and what are the barriers to change for things that should be good for us to do and the multiple mixed messages that come out of that that make it really murky. And so, part of my life in the innovation world was moving technology systems through software engineering to understand how software engineers think, how they code, how they design, and how they take what I need to happen on the business side and actually translate that. But then once that’s in the space, how do I get the people who are the end users to adopt it? It’s that adoption piece that I’ve always been fascinated with because you can actually have a lot of people who are really interested in this and a lot of engineering is poured into it, but it fails to move the dial for somebody who needs it to happen for them. And that is that complexity, that dynamic, this human involvement

My first foray into that, as we were designing websites, was the user interface, the UX. I had my first UX training and I go, “All this makes complete sense.” None of us come to these websites looking at it like an engineer or software engineer looks at it. We look at, you know, how do we get information in the system? How is it organized? Where do I associate the organization, and then, probably the big thing that Google introduced us to was how valuable a search engine is, back behind on a website, so I don’t have to try to go through screen after screen to find how an engineer interpreted what they thought I needed and was after. It was, no, let me tell you. Let me actually search for that myself and use the lexicon in my head, and hopefully, those lexicons meet up at some point. So, that UX training and search engine optimization training led me to“how do we translate through this space” and “how do we meet the end user?” So, it was thinking about the change barriers and processes that hit into that.

ANDREW: One of the things that you mentioned that also just rang very true from the design capacity standpoint is the ability to empathize with what you’re doing. I think for a while now we’ve realized that for certain things, the information deficit model is not really what makes change, because if that were the case, we’d all be amazing beacons of health. There would be so many things that would be different in this world if it were the “know better, do better.” It’s necessary but it’s not sufficient for these kinds of things to happen. So, to get in the mind of the person who’s there, that’s really the trick. But that’s not easy. There’s a potential within using Google to do a little bit of that, but this also harkens back to relationships. This also hearkens back to “people come first” because the work will be a part of that, and yet that empathizing step is being in the business of humans and celebrating that as its own valid science without it having to be called psychology, even though there’s certainly a psychological component. The social sciences are involved with this as well. But there is a very human-centered – using that term human-centered design – that is necessary to make changes with humans. Otherwise, we’re neglecting the most basic unit of what we are when we’re trying to make those changes.

So, you recognize empathy, it sounds like, from this process, but then there’s a scaling question I have too. Let’s say you get the story of a person, and you get how to reach that person, and then, OK, I reach the person, but now innovation doesn’t happen with a single case, it happens on a scale.

GWEN:  In some regards, I’ve always considered myself as an early adopter space because I like to try new things. Most of the time, give me a piece of software and I’ll knock it around, or give me a technological connection challenge and let me knock it around for a little while. Then we move into the early adopters, and then the late adopters, and then, you know, the laggards are the people from NCIS. Gibbs is still using a flip phone instead of a smartphone. You’re never going to get them until it’s absolutely necessary. (At least he’s not using a landline and he’s carrying around the phone.) So, the issue that fascinates me, particularly in the spaces in the educational sector that I’m in, is what we call the “innovation chasm.” It’s when innovation drops to the bottom and it doesn’t make it over to the side of early adopters.

I’ve been in spaces that are resource-rich. In other words, they know how to get through the chasm because they have a very structured plan of how they’re going to harness the financial and the human resources to get through the chasm, to get to the other side of the chasm, and get early adoption going. What I am fascinated by now is how you get through the chasm when you’re in education or a nonprofit – and not wealthy nonprofits, but your typical nonprofit, and you’re just trying to get through, you’re trying to get to the other side with your good idea, but it doesn’t have the resources. How do we do that, and how do we think about matrixing those resources and doing the scaling incrementally to build on success? Because, if not, we all dump out at the bottom of the chasm, and then we’re all discouraged. And creativity, by the people who are early adopters, starts to really take a beating because it turns out that our egos are a little more fragile around those kinds of things that we create. We all have this birthing instinct, I think, in us and we all want to kind of give rise to something. When it dumps out or it dies and there isn’t something that we can do about it to help it live, I think that’s hard on all of us, hard on the psyche.

So, I am particularly interested in working and rereading this literature to see how, in low-resourced areas, we need to behave differently than in the high, resource-intense areas. How do we need to come at and approach the problem? And I think that there are other metaphors, and other ways of seeing this, another lens that may be helpful, here, another lens we both share is around idea diffusion. So, where does idea diffusion come in here that we need to spread this out a little bit more?

ANDREW: I’m going to go esoteric here for a second because it reminds me of the work I used to do in a previous life. It was my dissertation in neuroscience, and it was how your brain interprets light signals to tell it what time of day it is. And we call this process entrainment, and so, the light-dark cycle – the sun comes up in the morning goes down in the evening – those cues, like sunup and sundown, are the thing that actually tell your brain – you just need it twice a day – to sync in with the beginning of the day and sync with at the end of the day, or whatever you call the sun cycle. And then it regulates all the temporal processes in your body. How does it do that? And it turns out there’s one very densely packed brain structure with thousands and thousands of neurons that can be divided up of what kind of functions it has. So, it used to be said that this one brain structure is responsible for timekeeping. You could dissect it out a little bit, and I was a neuroanatomist, and find that within the structure, there are separations of function.

Part of this timekeeping system is a very, very robust pacemaker, so no matter what, it will function on the cycle that it knows to function on. And you can take these neurons out of the brain and put them in a dish, and they’ll continue to be good soldiers and they’ll continue doing it no matter what. There’s another part of this structure that’s on the opposite side, that’s not great at being robust and keeping time, but it’s super responsive to changes in the light cycle, and it actually gets inputs from the retina itself. Neurotransmitters are released and suddenly it’s just super sensitive to change. In between them, there’s a gradation of these kinds of hypersensitive, low-robust neurons that work their way up to not very sensitive, more-robust neurons. And the signal of entrainment comes through and it actually takes a journey twice a day between these sensitive to robust neurons that create a very stable system of daily synchronization or what I think of in this way, a bio mimicry example of change, that there’s this separation of function at work.

You need the people that are going to do what they’re going to do robustly and that’s part of your system, and you need the people – as you mentioned, the early adopters – who are very sensitive to change as another part of it. And in between those two, the area that nobody cares about, because it’s not as clearly defined, is the spectrum of change that happens in between. And you get this whole weird mix of other kinds of neurotransmitters in there. It’s the most diverse part of this brain structure, that in-between space, there are so many solutions that biology comes up with for the innovation chasm problem on its own, that it’s like you have a different recipe for each version of this. It’s not algorithmic, but in a way, it mimics this phenomenon that you’re talking about in a social setting, it would be so fun to look at the suprachiasmatic nucleus as a model for the innovation chasm, because I do think that we overuse the term innovation, and we look at it like a black box, like something happens, voila. It’s true there are mysteries to innovation and there are people who study it like yourself who understand that there’s a process involved, but it never ceases to be an area of creativity and of wonder and of infinite models of how it could possibly work, because it’s the problem that nature has to solve over and over again, and as nature has to solve it over and over again, so do social systems have to solve it, and that’s the beauty of this kind of transdisciplinary thing.

The big themes that we study are the ones that will carry you through everything. There’s always a sense-making component to something. There’s always a need to ask for help. There’s always a need for humility. There’s always a need to realize that you’re seeing a part of the picture. There are always solutions that have been generated that you can model after. There’s always a capacity for new solutions. These are the big themes, I think, in a transdisciplinary mindset that when you come back to them, you realize you don’t have to know an entire textbook of education or sociology or something, but if you get some of these kind of mega themes, or I call them the threshold concepts of life, then that toolset you have isn’t just a hammer, it’s a Swiss Army knife hammer.

GWEN: We’re all MacGyvers.

ANDREW: Give me some gum and some measuring tape do anything with them… I love having these. You spark so much fun in the way that I can think about things because you so clearly explain how to look at a situation, and how to do it in a way that is evidence-based, that can be in a structured way, the way that you structured data, but it also makes it accessible to someone like me, who might not be in the same data spaces that you are. I’d imagine that your students benefit from something like this as well, that you allow them to see the connections of the world because you present things in such a way that leaves it so open for their imaginations and their creativity to get involved with the process.

GWEN: I think that captures well the fundamental approach that I bring to the educational process. I remain open to the co-creation space that’s happening between me and the student – and students – because there is an individual dynamic, and there’s a group dynamic that happens. And, to me, that’s what gets me up every morning. I’m co-creating that space, and in that co-creation, not only with students, but I take that and remain open throughout my day with my colleagues. It has served me well to just allow life and the energy of life to come to me. And I will say some of it isn’t really energetic and I avoid that. I’m a standard human being and I avoid pain when I don’t have to come around to it.

In the class, I try to create learning communities that are co-creative and allow the students to thrive there. What I also try to do in that co-creative learning space is make it easy to, what we call in the improvement science world, “to fail fast and learn well.” So, in other words, if it doesn’t work, to not put a lot of weight on that, but get enough feedback to know how you can stand up and keep going. And I think that working with complex problems and complicated spaces – and organizations are complex problems and complicated spaces – and sometimes, we face often low-resourced space, is you’ve got to fail fast and learn well and keep going and celebrate along the way the achievements when they get there.

ANDREW: That’s a good axiom for anybody trying to do work in a nonprofit. Every day, you get up, “I’m gonna fail fast and well today!” But, you know, understanding that you can fail upward, you can keep failing in a way that’s generative, and sometimes it’s not failure.

Gwen, thank you so much for joining us today. It’s always fun to chat with you, and I can’t wait to do it more. I’m excited to see where all of our futures take us, and I’m so glad to know you as a part of this process.

GWEN: Thank you, Andy, for the time. It’s been a pleasure.

ANDREW: Thanks for listening to this episode of PostNormal Times. Thanks to our guests, and thanks to our support from Claremont Graduate University. If you enjoyed boundary crossing with us and want to hear more, make sure you follow us, spread the word, and tune in to our next episode.

This podcast transcript has been edited slightly for clarity.