Mushon Zer-Aviv is an activist, artist, and designer. He's currently at work on devising new ways of understanding change and the future—ways that account for the limits of forecasting and consider the "darkness" of the future as a place for hope and possibility. He also discusses systemic bias, the value of small talk, his appreciation for Rebecca Solnit, Naomi Klein, and Milton Friedman, and how his work brings provocation and action together.
Kristin Gecan:
Welcome to the last episode of our first season of With Intent, a podcast from IIT Institute of Design about how design permeates our world—whether we call it design or not. I'm Kristin Gecan. If you haven't yet, now's the time to subscribe. That's how you'll learn more about our second season, which we're hatching now. Let me thank all our listeners this season. I'm so glad you've decided to join us as we've explored what design and designing is this season, often with non-designers.
You can do a couple of things to help us make the next season even better. One is to write to me and give me your feedback. Find my email at id.iit.edu/podcast. Another is to tell someone about this podcast, especially someone you know who could use design. Updates on season two to come soon.
Now, this week, I talk to Mushon Zer-Aviv. Mushon is a designer. He's also an artist and activist working in media and technology. His many projects and provocations converge on imagining the future. Or, more correctly, futures. That is, any number of possible futures. Plural. But, though imagining the future is central to his work, Mushon has readily admitted that he finds it hard to do. We talk a lot about how he's done it through different projects, and we also consider Milton Friedman as an unlikely inspiration. We discuss the line between provocation and action.
But first, let's explore the curious notion of a futurist who finds imagining the future difficult.
So, you've said that, from your vantage point in Israel, it's been hard for you to imagine the future, and I think you're specifically alluding to Israeli, Palestinian conflict. But, of course, imagining the future is very central to your work. And so, I wonder if you could just tell me a little bit about how you have overcome this difficulty in imagining the future, and come to focus on the work that you do now?
Mushon Zer-Aviv:
That's a great way to start. I don't know about overcoming, but definitely working from Israel... During the '90s, when I was growing up, when I became a teenager, and then grew up and studied, we went through a period of hope that was crushed with the assassination of Yitzhak Rabin, incidentally exactly 26 years ago today. And, the thing is, when I grew up, I was expecting the occupation to end, and I was expecting to have a future that would be much more aligned with my ethics and with the kind of country I want to live in. This has not happened since, and I think many Israelis have become very, very cynical, and very suspicious about hopes for the future, and about change in general. This is a landscape that not a lot of Israelis are challenging, and I feel an urgent need to do that, as someone who chose to come back to Israel after more than five years in New York, and build my life here again, start a family here, and hope to have a good future in a place that I love. But is very problematic. That's kind of the background.
I don't know if I've solved it. They haven't missed the news, the occupation is still there 54 years later. But, I definitely feel like there's a need, especially for creative practitioners, to develop different ways of thinking about the future, because the cynical framework is not something that is very inspiring, both for creative practice and for views of change. So, that's a bit of the motivation.
Kristin Gecan:
So, this is a podcast, obviously, so no one can see us right now, but I'm going to move to one of the projects that you've been working on. I want to ask you, how normal do you look, and why does that matter?
Mushon Zer-Aviv:
I think, to me, I'm pretty normal. I got pretty used to the way my face look, and I think for a lot of people that's the case. But, the project you're referring to is The Normalizing Machine, or the recent iteration of the project that is called simply Normalizing. That's a project where I'm trying to teach machines to identify, "How do normal people look like?" That's obviously a provocation that refers a bit to the technologies of face recognition, specifically, and more generally, to artificial intelligence and machine learning. Machine learning is trying to automate patterns that are important to us. There's a lot of excitement around this technology because it makes a lot of things very efficient, it can do a lot of routines that are very tedious, it can do really fast and in really large scale. But then, when we rush to extend it to every element of our lives, we forget the biases that are embedded within these technologies.
And, these technologies are built around an idea of normalization. That is statistical normalization. They work statistically, they expect a pattern. And, they're built to do a pretty good job for things that meet that pattern. When things don't meet that pattern, then they'll exclude it. Sometimes, these technologies will try to find things that don't fit that pattern. But, the idea of normalization, that is embedded into technologies of machine learning, are really something we need to reflect on.
Specifically, with The Normalizing Machine, or I would refer specifically to Normalizing, which is available on the web on [inaudible 00:06:24]. You go online, on your mobile browser, so you enter the website and you join the experience by taking a selfie. The selfie would then be added to a database of previously recorded other participants. And then, you would be required to choose between previously recorded participants, comparing their noses, comparing their eyes, their foreheads, their mouths, and so on. You would get two pairs of noses, for example, and then you'll need to swipe towards the one that looks more normal. That's how you're basically classifying and helping to create this arrogated image of normalcy.
At the end of a few rounds like that, you would get the result of how normal do you look, and your face will be added to a map that is trying to both create clusters of similarly looking people, and to identify, "How normal do they look?" That map is algorithmically organized, so there are pretty disturbing patterns that appear there, because it quickly tries to separate male and female, try to separate by race. It's interesting to see what patterns does it find. And, because the map is organized as a two-dimensional grid, we see a blob of men, a blob of women, and then a cluster of [inaudible 00:08:02]. So, all of sudden it becomes really disturbing, in the sense that this is how the machine looks at human faces. It identifies Asian features, and then that's another blob. And, kind of segregating them geographically on that map, based on the analyzed features.
So, I hope this work allows us to reflect on these kind of patterns that we do quite naturally, with or without technology. But maybe, ask ourselves, "Do we want to automate these things? And, what is the price of this automation? What should we automate? What shouldn't we automate?" And so on.
Kristin Gecan:
What you're talking about, I think, is the sort of programmed bias of some of the technology that is available to us today, and how we can't necessarily blame the machines themselves for that, because some human has programmed those machines. So, through this project you're trying to reveal those biases that are part of what have been programmed into machines?
Mushon Zer-Aviv:
Yeah. So, what's special, I think, about the technology of machine learning, is exactly the fact that there's only so much that is programmed into them. Much of the rules that these algorithms apply are statistical, so they're very much based on the data they're fed. What I was trying to do with [inaudible 00:09:36], to emphasize both data collection and data classification, to remind us that we are feeding these machines. We are the ones who are normalizing, not only by swiping right and left on these pairs of face segments that are prepared and with this weird question, "Who looks more normal?" We basically do that all the time. Not only in Tinder, which also has this swipe right, swipe left, but also on the like button, a comment, even swiping through a feed creates patterns of normalization.
So, these patterns of normalizations create data that is analyzed. This is what feeds these machines. They are based not on algorithmic bias, but on automated human bias. And, I think, beyond the dark vision of machines taking over, propagating bias, it's important to remember it's our bias, we just chose to put it inside a black box. So, the first thing I'm trying to do there is to make the black box a bit more transparent, and to really reflect on what's happening inside. But also, remind us that systemic bias was with us before algorithms. And, the work itself reflects on the history of forensic photography from the 19th century, and shows how this idea of face identification has morphed into face classification, and has led us down pretty dark paths in history, much before we started talking about computers. In a way, I would even say that I'm happy that we're talking about systemic bias and that it creates this slightly populistic, but then exciting, articles in Wired magazine. Because, systemic bias has become finally multidisciplinary, it's not just something that bureaucrats do behind their desks. It's something that involves data scientists, and designers, and other practitioners that were not very involved in these questions before. It's, in a way, an interface for us to deal with them again.
Kristin Gecan:
So, what you're kind of saying too is that it's not that that there was bias originally input into the machine, or the computer, or the technology, it's that, one, you're asking someone to swipe to make a decision about what's normal, that's where the bias comes through, right?
Mushon Zer-Aviv:
It's a balance between the two. Because, I'm not claiming that there's a way for us to not be biased, on a personal level. Your question is exactly touching on this point. On one hand, we try to identify patterns, this is how our brains work. We try to understand what is foreign, what is common, what to expect from what we see around us in the world, the kind of experiences that we have. And, this is really how our brains work, for better or worse. The idea of de-biasing is useless. We will always bias based on the experiences that we have. But, the decision to alienate this process into black boxes, into machines, as if there is this truth of what is normal, I think that's where the problem is. So, in a way, there's bias in the way we look at the world, and there's bias in systems of normalization, and this idea of normalization. And, merging the two has consequences that I hope participants in the piece can reflect on.
It's important to remember that artificial intelligence, while being kind of a symbol of cutting edge technology, it has a very, very conservative bias by design. So, what these technologies can do is only look at patterns of the past and expect them to continue. So, basically propagate the past into the future. The working assumption is that the patterns that we've identified in the past will continue into the future. That's true also of every prediction algorithm. They can say, "We can see the patterns repeating themselves," or, "We cannot see the patterns repeating themselves." In a way, metaphorically, we can say it's like one and zero. It's either continuous, or it doesn't continue. It's never two. It's never more than the present. It's never more than the past. And, this connects back to the question of futures, in a way, it doesn't allow... If we're thinking through the framework of prediction algorithms, we will never find a better future. We will never find the leadership that would allow us to deal with the many challenges of the 21st century, and the climate crisis is the first of them.
That's an important element, because when we're thinking through the prediction of temperature rise, which is a very important value that we can get out of these statistical systems, the fact that we can sense and collect data, and identify patterns about temperature rise, is amazing. We wouldn't even have had the climate urgency that we're trying to push towards if we didn't have that. But, if we expect this graph to also show us how to get out of this, or inspire some kind of change, that would never happen. In a way, when we're looking at the different scenarios that are compared in the temperature rise prediction, the subtext of this graph is, "Choose your apocalypse." So, it's either that we're going to face a horrible apocalypse, or a very, very horrible apocalypse. That's also only based on this idea of the status quo is changing, and our way of life would not be able to maintain itself. But, a graph like that, or machine learning like that, or data-driven predictions in general, cannot imagine what is not from the past, technically. Technically, they are conservative in that sense.
So, especially for designers, and I see designers as being always about the future, we need to understand that there's only so much these technologies and these approaches can take us. And, the burden is on us to get back to thinking outside of the prediction mindset. Not against the prediction, but really understanding that this is just a part of the picture. So, there's forecasting, and there's foresight. Designers need to do more foresight to complement the forecasts of data scientists.
Kristin Gecan:
So, I want to talk a little bit more about that, what you're talking about forecasting and foresight, and I think we called this, in the Latham panel discussion that we had, anticipatory skills. In that conversation, we talked at length about futuring, and we closed with a quote from Milton Friedman, that you've cited. I'm going to repeat that quote, which is, "Only a crisis, actual or perceived, produces real change. When that crisis occurs, the actions that are taken depend on the ideas that are lying around. That, I believe, is our basic function, to develop alternatives to existing policies, to keep them alive and available until the politically impossible becomes politically inevitable." This, interestingly, came from his 1982 preface to his book Capitalism and Freedom. So, I want to hear more about how this quote inspires you in some ways, and connects to your work? So, let's talk about that a little bit.
Mushon Zer-Aviv:
It's a playful gesture to use that quote, because I sign every word, except the attribution, right? So, I don't share Milton Friedman's politics, neither does Naomi Klein, who wrote The Shock Doctrine, where I came across this quote in that book from 2006, if I'm not mistaken. She refers to how this idea of crisis capitalism took shape. She has a lot of issues with Milton Friedman, but I think she finds that quote inspiring as well. It's inspiring because it understands that the way free market capitalism and neoliberal politics have been looking at the future is much more open-minded and much more anticipatory than other ideas. We've heard a lot about think tanks. These think tanks have been ready to take advantage of opportunities. Opportunities that have been serving very, very narrow private interests, but this is a call to action to understand that if we have different ideas, if we believe that other futures deserve a chance, we need to be prepared. And, to be prepared is not only to think through the framework of the status quo or the prediction, it's understanding that the futures are always much more varied, and we can't really predict them. It's much easier to make that point after 2020.
Our future may look very, very different than our present. And, I think one of the tragedies... And, I'll come back to that point, because I think it's very important. One of the tragedies is that the same predictions that demand the climate urgency, are also the same predictions that limit our imagination. I'm looking at trying to develop different methods to look at the future, ones that are more challenging the status quo and challenging the boundaries of the discourse that we've been having, the data-driven discourse. I'm in the process of writing a book about these things that are using key terminologies from design to develop a design theory of change. I'm using terms like "Flow," and, "Friction," that are used a lot in interaction design. And, other terms like "Affordances" and, "Signifiers," again, coming from understanding agency from the perspective of interaction design. And then, trying to look through them at political agency, and specifically about the flow of the future. So, can we look at these dynamics between flow being the inertia of time, or habit, or power? And then, friction as being the elements that do not conform to that inertia, that may slow it down, or may even diverge it, to some degree.
And then, understand that friction, like Milton Friedman's crisis, can be a problem, but it can also be an opportunity. So, reading and finding friction, identifying friction, can be the framework for which to find agency again, either by understanding that friction stands in our way to protecting our flow, or continuing the flow that is desirable or preferable, and then identifying friction is a good opportunity to get rid of it. Or, that understanding that friction is the opportunity to change the flow. I'm looking at different flows that have been so optimized beyond our ability to change them, and I'm looking at definitely about issues of inequality. Inequality is hard to change because our economic system has optimized itself for inequality. It's not a mistake. And then, it's really hard for us to change it because it's built to have no friction. When we're talking about what's happening online, [inaudible 00:22:49], and the crisis of reality, and post-truth, and so on.
And, beyond that, the climate crisis. The climate crisis is the result of a flow that we've been optimizing for hundreds of years. We've been trying to push the environment away, because the environment, and nature in general, has created a lot of friction in our lives. Anything from [inaudible 00:23:17], through habitat, through trying to live in different climates. We've been amazing at pushing that friction away. It's been an ongoing struggle, that we haven't really taken into account that there might be some consequences. I'm trying to think outside of the framework of guilt around our relations with the environment, and to focus on... I don't think that nature is pure, or that we should go back to nature because it's amazing and everything that we've done is wrong, but I think we need to discover friction again. We need to interrogate our flow, and to really understand how to change that flow. Because, if we're using the metaphor of rivers... I'm referring a lot to rivers as this metaphor. So, the flow of the river has a certain trajectory, but it would not have had this inertia, this stream, without friction, because otherwise we would have had a swamp or just a sea.
We have inertia, we have a direction, because mountains, and rocks, and other elements, are creating friction that creates a direction. So, in a way, we need to understand, "How do we bend rivers? How do we read our agency in the flow? And, how can we direct it again?"
Kristin Gecan:
So, just to think about this metaphor of rivers a bit more, and what you're calling frictions and flows, and I know you've also used the term, "Global frictions," can you give me some examples of flows and frictions, or global frictions in the world today?
Mushon Zer-Aviv:
So, when it comes to global friction, I've been thinking about it that what we're experiencing with COVID-19 is really, really unique, in the sense that we've never had global friction before. I've been trying to find other examples, but I couldn't find another example where it's not only that we were all in the same stream, as in all humanity in the same stream, but all of us are facing the same new problem. So, it's a problem that we haven't faced before. There were other pandemics, but none of them were as global and world-encompassing as this one. And, this is also, of course, a result of globalization. It has become the new statistics that are universal, like the weather. It's the perspective we looked at our lives through. And, I think this is an opportunity because looking at this global friction might give us some clues on, "Why do we not render climate change as global friction yet? Why don't we render the problems of inequality and the airtight capitalism and how it's incompatible with the world that we live in?" We don't render that as global friction, even though it does affect us all, but we don't see the world through that perspective.
Kristin Gecan:
And, you're saying global friction is something that we could sense, or feel, or have smalltalk about?
Mushon Zer-Aviv:
Yeah, I think smalltalk is important, in that sense. Smalltalk, as in, "I don't know what I have in common with this person yet, but I know that I can talk with them about the weather." Or, "I know I can talk with them about COVID-19, because it's obvious that this is an essential part of this person's life and the way they woke up this morning and look at the world." That is not the case with climate change. That is not the case with economic system. Funny enough, just a few weeks ago, I think we had a second global friction for a few hours, and that is the big Facebook blackout. The fact that so many people could not go on Facebook, Instagram, WhatsApp, and so on, that, to a large degree, was global friction, but a very different one. But again, we can see the connection between globalization and global friction.
To your question about the rivers... So, this is really a part of the framework that I'm trying to develop as part of my book, I'm trying to think of topologies of rivers as topologies of change, or images of change. So, at this point, I have five topologies. The first one is the status quo, we can imagine it as a river that no matter how it bends or meanders, the main stream is strong, it doesn't change. So, this is the idea that the future would not change much, so that's the idea of the status quo. The second one is collapse. Basically, the river runs dry, so an idea that this stream would not be able to maintain itself and would run dry. The third one, I currently call resilience, the river diverges, but we have a clear idea that it would converge back further down the stream.
So, think about COVID-19 and this idea of, "Flatten the curve." "Flatten the curve," was promising us, basically, not only that we might meet the demands of the health system, but that the curve... I'm arguing that the curve we actually looked at is the part of the curve that actually flattens back to zero. So, there was an implied and mistaken promise in, "Flatten the curve," that, "It's just one curve and we're back to our lives." I think we fooled ourselves into believing that. Which, is great, otherwise maybe we wouldn't have taken this urgency, and we know that many of us have not taken on this urgency. But, globally, I think humanity has definitely stood up to the challenge, to a large degree. So, that's resilience, this idea that, "We will be back to the main stream."
The fourth one is adaptability. If we imagine the river, it's kind of the river delta. A lot of streams that are diverging from the main stream change that is so rapid and so unpredictable, that it's really, really hard to plan ahead, and we need to focus on our conceptual flexibility, our future's literacy, our ability to really look at how the environment changes, and to reconfigure our lives again. That's what actually happened with COVID-19. The fact that there was another curve, and another curve, and another curve, at some point we realized that we are on a completely different flow. We have never come back to the pre-COVID... This whole myth of post-COVID, Post-COVID is not pre-COVID. Post-COVID is a new thing.
The fifth one is transformation. Transformation, if we go back to the metaphor of the river, we always thought that we're in the main stream, but then we connect to another stream and we find out that we were always a brook of a different river. Life can change dramatically in the future, and that could be because of external forces, and it could be because of political forces, economic, cultural, and societal. We can really think of different forces that would dramatically change our lives. So, I think it requires some humility and a lot of imagination to understand that there is no, "The future." Nothing in the current stream promises that [inaudible 00:31:19] stream continue. I'm trying to suggest that these different topologies are a way to look at many aspects of our lives. So, we can use them to really open our imagination to other possibilities beyond the status quo.
Kristin Gecan:
In my view, we have the smalltalk that focuses on the weather, because it's sort of, as you said, easy and everybody's sort of experiencing it. But, there's also some hope embedded there always that the weather will get better, or that it'll change, at the very least, it won't always be that way. Maybe I'm just saying that because I'm in Chicago and that's what we say, "It won't stay like this, we know that." And then, maybe we talk about COVID because we have that same hope that it will change, or that we're seeing things change. And, maybe we don't talk about climate change because it's less easy to feel, and it's less easy to maybe have hope there. I just wonder if you have any thoughts about these ideas, and, I guess, both about the importance of hope as we're doing futuring work, but then also making that futuring work accessible to people beyond academia. Because, sometimes I just feel like it can come off as very elitist, like, "Oh, you have time to sit around and think about the future," but it's like, "Oh no, we should all be thinking about the future, this is our future."
Mushon Zer-Aviv:
So, one thing that I really like about the framing of anticipation in the field of futures studies, is that anticipation is not something that is only human. I'm not even talking about creative professions, and definitely not even about humans, but biological systems and ecological systems have a sense of anticipation, as in the way they prepare for the future, the way they anticipate the future. I definitely share that concern about this elitist futuring. In a lot of cases, this idea of speculative design has been this armchair speculation that allows itself to imagine dystopias, and they feel very, very critical. But, how does it translate to action? How does it translate to finding agency?
And there, in the context of hope, I think hope is a very, very important concept. I'm specifically very... I relate to the way it was framed by Rebecca Solnit. Rebecca Solnit has a book called Hope In The Dark, and in it she quotes Virginia Woolf, who said, "The future is dark, which is the best thing the future can be." What she means by that, or the way Rebecca Solnit uses it, is that not that the future is dark as in a bad thing, the future is something that we don't know, unlike prediction algorithms that are kind of trying to project light into the darkness of the future. And, if this projection is... I'll get back to the temperature rise prediction. It's lit, there's light, we can see what's coming up, but it's very dark when it comes to what we can hope for. If the future is dark, it means that there's possibility in the darkness. There's possibility and uncertainty. There's possibility in not knowing, and that's another element that calls us to really take into account that this data-driven world that we find ourselves living in is very, very limited in what it can offer us politically, what it can offer us creatively. And that, I think, really requires us to embrace the darkness as the best thing the future can be.
And, also find our agency, not only in the future, and not only politically, but in technology. Understand that technology can only go so far. It's amazing to be able to use these forecasts, and we should use them wisely and widely, even more than we do today. But, understand that this is just a part of the discussion, the other part really requires us to use our creative reading and our imagination to scope possibilities for the future, to identify opportunities to create the ideas lying around. This is where Milton Friedman's quote, I think, is really, really inspiring for political change, rather than for maintaining his brand of capitalism.
Kristin Gecan:
I think you consider yourself both an activist and an artist, among other things, and...
Mushon Zer-Aviv:
Designer.
Kristin Gecan:
And designer. How do you decide when to make art, or design other things, and when to take action?
Mushon Zer-Aviv:
I think a lot of my more discursive work is also an attempt to raise a conversation that is important for me to figure out. But, at the same time, I feel like a lot of the work that we should do at this point, politically, has to do with political imagination, has to do with this idea of, "How do we break the patterns of despair in places like Israel and Palestine, in the context of the economic crisis, in the context of the environmental crisis, in questions of race, and gender, and ability, and so on?" I think I'm looking at what happens in the left all over the world, and specifically in the US, and I see, on one hand, so many desire for change, but it's wrapped in so much anger and so much despair, and such a huge level of fragmentation. Even when we're talking about gender fluidity, it's been discussed in such binary terms, like, "We demand to know your pronouns. We demand for you to be an ally." There's something about these dichotomies that we're not able to think beyond.
What I'm trying to develop in my current research is thinking through flows. It's slightly less Western, I think, in its approach. I can't call myself very much an expert in Eastern philosophies, but I think they're much less devoted to this idea of segmentation, binaries, categorization, and so on. And, really trying to see change in volumes, in philosophies, in increments, rather than, "You're not an ally, and therefore you're canceled." So, I'm not sure I answered your question. But, I think in many of my works, not necessarily the ones we discussed today, I'm trying to expose actual agency. One of my works that we have not discussed, and I might mention it briefly, is called AdNauseam. AdNauseam is an ad blocker, that not only blocks ads, but also clicks every ad that it comes across. And by that, pollutes the profile that ad networks are trying to gather on you. It's a collaboration with Daniel Howe and Helen Nissenbaum. And, this idea of [inaudible 00:39:18] is very a different approach to privacy networks., when other solutions, like encryption, are basically trying to limit, to create boundaries, and to limit information flows [inaudible 00:39:32]. And, AdNauseam are trying to just increase the stream so much that it becomes meaningless.
I think we can think about it as dance versus a very strong stream. We can have protection in different models of information flows. I think we're going online, and we're using technology, not to hide, necessarily, but in a lot of cases to connect, to network. I think there's something sometimes very religious about the approaches that are taken under the framework of cybersecurity, or encryption, or crypto culture. It becomes like, "Why don't you encrypt your emails? How do you expect to have privacy if you don't encrypt your emails?" That becomes something that is kind of blaming the victim and coming back to this individuation. What I like about AdNauseam is that AdNauseam really creates power by the numbers. I'm not only polluting my profile, I'm polluting the idea of normalization. I'm really messing with the ability to create a normal consumer of information. And, the more we do that, we don't only protect ourselves, we also fight fire with fire. You want big data? Let's see how big can data really get.
Kristin Gecan:
Yeah. I think this is really interesting, because... I think you did answer my question, because what I did was I presented you with a dichotomy that then you [inaudible 00:41:08] to say, "I'm doing both. This is a provocation that is actually also taking action." I think is kind of what you're saying. So, I think you're saying what your work does, whatever shape it takes, is both in some ways.
Mushon Zer-Aviv:
Hopefully.
Kristin Gecan:
And so, I wanted to ask you too about another project which came out, I think it's almost 10 years ago now, the collaboratively written book Collaborative Futures. We've been talking about politics and change in the future, and so I wanted to just... I had to ask, after taking a look at that book, whether you would consider... Because, I know the book tries to define collaboration. Whether you would consider Occupy a collaboration?
Mushon Zer-Aviv:
Yeah, for sure, Occupy is a collaboration. But, since you mentioned Occupy, if you allow me, I have a spiel about Occupy.
Kristin Gecan:
Okay.
Mushon Zer-Aviv:
So, about two months before Occupy had started in Wall Street, a big social uprising started in Israel. For the exact same reason, because of economic inequality, because of housing crisis, because of divides between rich and poor, and the methodology was very similar as well. It was tent cities all around Israel. At some point, this social uprising had more than 80% approval rates all around Israel. It was really, really a substantial political uprising. And then, Occupy started two months after and propagated all around the US, and then all around the world. When we were faced with this term, "Occupy," and we wanted to say this is a part of a global movement, and we had a lot of ties with Occupy all around the world, we could not call Occupy, Occupy. For the main reason, that we already have an occupation, and it's not symbolic. In a way, the use of the term, "Occupy," really rendered something for us that was kind of disturbing, that the occupation of the public space was symbolic gesture, as much as it was physical, as much as it was in physical space, as much as it was amazing in many, many ways it was stuck in the symbolic realm, and it did not render into clear political affordances.
Unlike the non-affordances of the occupation of the West Bank, in Gaza. Unlike the power of the strike that has clear economic affordances. If we go back further in time, unlike the peasants standing at the gates of the noblemen with torches and pitchforks, and they're marking a very, very clear affordance, "Either we're going to burn you and everyone inside this castle." That's what Occupy and the Tent movement in Israel were echoing symbolically, but without the affordance of actual power. So, this removal from power, and our embeddedness in the symbolic realm, has been one of the challenges of both the Occupy movement and the tent cities in Israel, and many political protests since. I think, to a large degree, we need to get... This kind of connects to your previous question, we need to connect back not only to the symbolic meaning or the symbolic gesture, but also to affect change in the material world.
AdNauseam works as a protest, but it also messes with the data, with profiling, and it actually costs money. It actually messes with trust between these ad networks and advertisers. So, I think we need to find these opportunities beyond this alienation to understand how we not only change the conversation, which is important, but actually change the power balances on the ground. An example that came out of Occupy that does that is Debt Collective. So, Debt Collective an initiative that raises donations to buy people's debts. They buy them on penny on the dollar, and at this point I think they've relieved more than a billion dollars in debt. Not by paying billions of dollars, but actually through buying debts in a very low price. So, the thing that I see there as very relevant to these conversations about affordance, and signifiers, and political agency, is that this is kind of hacking the economic system—this is kind of looking at the economic system and finding the hidden affordances for affecting change, very much like hackers would look at a computer network and find the weaknesses, find the exploits. So, back to understanding not only symbolic impact, but also material one.
Kristin Gecan:
I just want to ask about all the different work that you're doing and have done, and that's some of the projects that we've talked about today, as well as you're the co-founder of a design studio called shual.com, co-founder of shiftspace.org, creator of youarenothere.org. So, there's many things that you're working on. You're also, I think, faculty at a few different schools. So, thinking about all these different roles, all these different projects, how do you think about your work? And, what's the thread that ties them together? What drives you after all these things?
Mushon Zer-Aviv:
I'm so happy that you're asking this question now and not like a year ago, because a year ago I think I would have had to answer that, "I really don't know, and it really disturbs me." But, at some point, I realized there's something that connects all of the threads of my work, and that is these questions about friction. I think this tension between friction and flow, and that's also why I realized that this should be my biggest project now, which is the book. I can talk about my futuring work through that, I can talk about AdNauseam, I can talk about teaching through that. [inaudible 00:47:52] senior faculty at [inaudible 00:47:54] College, which is a substantial part of how I see my practice. And, even more client work that I've done as a designer. I've designed maps for Waze seven years ago. And even then, we can talk about transportation in terms of flow and friction. And, cartography, and information design in general, as topics that I've been working on a lot, kind of include these tensions between our attempt to look at the world and try to say, "Oh, this is a city. This is a village. This is a town."
But, on the other hand, the same point of interest, the same point on the map would also have variable for population, and variable for space. And, this tension between how we look at volume and how we name things, that is very much the day-to-day challenges of information designers. It really inspires me to look at many elements of my work, and try to see what are we kind of pulling into language, and what should stay ambiguous? And, what can even be represented not by words or numbers, and maybe should stay in the dark, as in the place of hope?
Kristin Gecan:
How do you define design?
Mushon Zer-Aviv:
So, the way I define design is both to plan towards the future, and to take action towards the future. I look at design as to design. To design is to plan. To design is to take action.
Kristin Gecan:
Yeah, as a verb.
Mushon Zer-Aviv:
Design as a verb.
Kristin Gecan:
Thank you to Mushon Zer-Aviv, a 2021 Latham Fellow at ID, for joining me today. You can learn more about Mushon on the IIT Institute of Design website, id.iit.edu/podcast. Please subscribe, rate, and review With Intent on your favorite service. This is a new show, and your support really helps. And remember, tell someone about With Intent. Our theme music comes from ID alum, Adithya Ravi. Be sure to get our next season delivered. Subscribe now.