Research Commons Guest Lecture: Mimi Onuoha
So Mimi Onouha is a Nigerian-American artist whose work deploys choice moments of seeming absence to question expose the contradictory logics of technological progress. You print code data, video installation and archival media. Onouha offers new orientations for making sense of the gaps that define systems of labor, ecology, and relations. Onouha’s recent solo exhibitions include Bit Forms Gallery and Four City Gallery.
Her work has been featured at the Whitney Museum of Art, the Australian Center for Contemporary Art, Now Geelong Arts Foundation Artillery, Transmedia Ballet Festival in Germany, the Photographers Gallery and Neon, among others. Her public art engagements have been supported by academian Dirk Ernst, the Royal College of Art, the Rockefeller Foundation and Princeton University. With that said, I'm happy to pass off to Mimi and let her give her talk. right.
Hi, everyone. Good to be here. Let me just I have to share screen.
I have the ability to share screen right? Yes, Mimi, you do. Beautiful. Okay. Let me just pull this up. Great and great. Okay.
So all of you can see, I hope a photo of an orange wall with some cables coming down it. Yes. Thank you. Great. Okay, perfect.
Then that that leads us into my caveat, which is that I can't see the chat. So if anything goes wrong, I need somebody to speak up and let me know. So if I'm speaking too fast, if I cut out. Anything happens, please just feel free.
Whoever can just speak up. Tell me. Okay. You're all right. You're free to continue. I'll be monitoring the whole thing.
Beautiful. Thanks, y'all. Okay, so this is.
This is an interesting moment to be presenting to y’all or to all of you here, because literally, as of this week, many of the ideas that I'm showing you here on this presentation have evolved. They've changed a bit. That's what happens.
You know, I have a friend who says that documentation never can keep up with code. So you have to document in your code. Or another way of putting this is that the world is its own best model.
This is just to say that the presentation doesn't always keep up with the work. So I say this because in terms of this presentation, I'm asking for a bit of generosity from you today. Maybe you're less audience and than normal. You're more people.
I'm sort of working these ideas out along with. Okay, That's my that's my main caveat. Those are my two main caveats.
And so now we're going to get to it. We are eventually going to work up to explaining this piece that I have on the screen. We'll get to that at the end of this. This is a presentation in three parts. The third part is where I will explain a bit more about that, About this piece and with all that. I'm just going to go ahead and start.
Part one, it's called What Is Missing is Still There. So to begin with, I want to start this all off by saying that I have always been drawn to absence. I like places that don't show up in maps. I like information, that can't really show up on charts. And I like everything that doesn't fit everything and anything that doesn't fit. And I like missing things.
There might be nothing that exemplifies my obsession with absence more than this piece, which is called The Library of Missing Data Sets. The Library of Missing Datasets is a physical repository of those things that have been excluded in a society where so much is collected missing datasets. This is the term that I have for blank spots that exist in spaces that are otherwise data saturated. My theory is that wherever large amounts of data are being collected, you'll find these empty spaces where you can't find anything at all.
These are things like the number of civilians killed by the police, which used to be a missing data set and isn't anymore. But other examples are the amount of cash that is outside of the US. The number of folks who are illegally placed in detention centers. Miscarriage rates in the US.
For before the 1970s. Number of people living off lease in New York City. Reliable accounts of Romani people worldwide. Total count of the number of Indigenous and First Nations women who have gone missing in Canada. And the list goes on and on and on and on.
This piece is about those things that aren't collected, and it shows this in this way that seems almost plain bureaucratic. Easy, easy to dismiss this white filing cabinet that is filled with these folders. Each folder has this tab, this tab, and the tab has the missing data set on it. And in presenting the work this way, we're trying to mimic the plain and bureaucratic way that certain things are excluded from data.
So I made this piece in 2016, and after I made it, it went on to be shown around the world. It still is being shown right now as we speak. It's shown in a, it’s in a show here in New York City, which is where I am.
But everywhere that it is shown, I changed the datasets that are within it. I changed them so that they match the people who are in the place where it's being shown. So if it's being shown here in New York, A lot of the data datasets have to do with New York City and with the US. If it's shown in the UK or in Brazil, then the data, the missing datasets will have to do with that. I did this because I wanted it to have a sense of specificity and I wanted it to be able to speak to people across different places. I told you this piece was made in 2016.
In the time since, it's gone on to be featured in magazines and TV shows and so on, it has done really wonderfully. But, the whole time, though, I was happy with it and proud of it. I also had the sense that there was something that I was missing, actually. I think I felt like I hadn't quite gone deep enough. Like there was more that the piece was pointing to.
And I don't think this sense had to do with other people. I did have to. I did have to be in conversation with folks who kind of missed the point of the piece, people who wanted to fill the missing datasets or buy the missing datasets. But that wasn't really the issue. I think when you make an artwork, it ceases to be yours entirely, and that's not an entirely bad thing. No.
So my issue wasn't that. My issue was that I felt like there was something that I was missing and I was the one who had made it. So what I did is the same thing I normally do in situations like this, which is I made a new version of the piece. In my work, I have a lot of different versions of pieces, and I make them when I feel like there's more patterns in a work that I still have yet to uncover myself.
So in 2018, I made a new version of this piece, which is called The Library of Missing Data Sets Version 2.0. The second version of the piece is very similar to the first one. It's the same size cabinet, exact same type. It's still a filing cabinet filled with files.
But what is different is that it focuses on a different type of information. This one focuses a lot on blackness and data about black people in a very Pan-African sense, Data that is disproportionately out of our hands. And that also is the reason for the other way that this piece is different, which is that it's gold colored. I was trying to tease out here this idea of wealth, abstraction, wealth extraction of what happens when you don't have control over the information that's about you, which is information that can go on to be used for commerce or control or for wealth generation. I have to say I really loved this piece and I, I liked how it brought out a different note from The Library of Missing Datasets because it got it, this idea of power and ownership and control. This fact that data collection often happens on someone else's terms.
But I still have that sense that I hadn't quite scratched the itch, that there was still more to the topic. So a few years later, I made a third version, and this one, the Library of Missing Data Sets version This one was, well, not complete. It was still a filing cabinet, but it was a different type of filing cabinet. And this one had the the the very important difference of it being locked. So there were still files and information in it, but the information and it was intentionally private.
And the reason for that was because making it public could be harmful to those whose information was contained within that. So this piece, as I said, it was locked. No one could access it, not even the gallery. And with this work, what I was learning about was when it makes sense to withhold information for the sake of protection. And when I was done, I had this trilogy of artworks, and I thought that together they were even more powerful than they had been individually Put together, they teased out these themes of access and of power and of busyness. They had been made over the course of six years.
So they had they involved so many different parts of my of my life and also the landscape of data collection, which had changed in that time. And I liked this trilogy of pieces quite a lot, so much so that I did not want to admit to myself that I still felt that squirming feeling, like I hadn't quite managed to get to the other level of it. But that was a feeling I could ignore. So I did.
And I made other pieces that were interesting and beautiful. And I got a job and I packed the feeling away and I moved on. At least until the summer of 2020. I'm sure all of you remember this time It was the height of the pandemic, days of absolute confusion. It was a time of clarity, but also a time of just complete chaos.
I was living in New York, and amidst all the COVID wildness, there were these widespread protests that were happening against police brutality, For George Floyd, For Breonna Taylor, for so many others. And in the middle of all of that, I wrote this essay that ended up being published in FiveThirtyEight, which is an online publication about data. And the essay was called When Proof Is Not Enough. So here was the idea behind it. During the protests that have taken place across the US, people had the idea that it was technology that had really sparked them, that had made everything possible. And the way that that whole story went was that technology and specifically cell phones, had made it possible to view things that otherwise people would not have been able to see specifically the brutality of these killings of unarmed black people and presented with clear evidence, through technology.
The the what logically followed was that it was the presence of this evidence that had been enough to pull people out to the streets. That was the story. That was the way it went.
And I didn't believe that at all. I didn't believe it was true. I didn't buy it.
I didn't buy it because I knew it was wrong. Throughout the US history, there have been countless forms of evidence that have been presented as proof of structural racism and of police brutality. And in the article that I wrote, I listed some examples.
One of them, just one, was this; it came from 1951 when the Civil Rights Congress wrote an entire petition exposing US racism to international audiences and connecting it with the U.S. strategies of foreign policy and the rest of the world. The CRC created a list of all of these examples of violence and of racism that had happened in the US, but specifically of police brutality. Like I said, they presented it to the UN. They had there were tons of examples and in the article that I presented to the U.N. and nothing happened, I should say.
So this was just one of many examples of the moments when constant proof of violence had historically not been able to change anything. And in the article, I really I just dove into this and I teased it out as much as I could. My main point being that I didn't want anyone to confuse the most legible artifact, cell phones and technology with being the most significant for these protests. Usually when I publish something, I leave it alone. It's stressful enough to get something written and published that I actually don't read it for a while. But this piece was different.
In the time after I published it, I reread this essay over and over again. I put longer and longer gaps in between each of those readings, And each time that I reread this piece I had written, I found that new lines would jump out to me. And slowly over time, I finally began to understand why I had had so much discomfort with the limits of The Library of Missing Datasets.
So there are missing things, missing data blank spots that exist in these spaces, things that have been excluded, information that's been excluded in a society where so much is collected. But then there are unknowable things, these collectively, unknowable things that are information or reality that can't be known, but not because they're wrong or false, but because they're too true. And to know them would challenge the foundations of the society that you live in. Classic example is Galileo, who so we have pictured here the 16th and 17th century Italian astronomer who worked across science and technology and many other fields.
In 1633, Galileo wrote publicly about the validity of the theory of Heliocentrism. This was a theory that had been advanced by Copernicus almost 100 years before. It’s the idea that the Earth and planets revolve around the sun, which is at the center of the universe, rather than outside the sun, being the one that moves around the earth. And when Galileo wrote about this, the Catholic Church convicted him of heresy and they put him on house arrest.
Today, we know that this is true. Why? Why was he put on house arrest when he was just saying the truth and he wasn't even the one who would come up with it in the first place. Well, the answer to that is that regardless of whether the fact of Heliocentrism was right or wrong, it invalidated the order of knowledge at the time. At the time that the the order of knowledge of that time that the Catholic Church was deeply invested in protecting.
And when I say this, I'm not drawing any conclusions or doing any fancy research, putting things together. The church said it themselves at the time. If the Earth moves, it would vitiate our entire plan of salvation Vitiate means destroy or spoil.
There's also the example of X-rays. X-rays, when they were first created, were thought to be some kind of elaborate, I said created, X-rays, when they were first discovered, were thought to be some type of elaborate hoax. They were discovered in 1895, and at the time they shocked the scientific community. And the reason for this was not because they were new, but because they had been unnoticed by the cathode ray equipment being used at the time by scientists at the time. The very equipment that scientists were using to make sense of the world was this cathode ray equipment. And these this was the same equipment that actually emitted the X-rays, which meant scientists have been looking at them the whole time, but just hadn't been able to see what they were.
It also meant that if the scientists themselves had been wrong, then they might have to redo experiments from the past that they had already completed. So they would have to reopen to questioning ideas that they believe they had laid to rest through the scientific process. So this is what the unknowable does. It comes into conflict with the deeply entrenched expectations, usually expectations that are advanced by those who have a great deal of power or regard in society. And it's the nature of this conflict and the power of those expectations that really makes these things still remain unknowable. And of course, final example, police brutality, which is tied to structural racism.
This is what my article had been saying from the beginning. The extent of structural racism has still really an unknowable fact that is inconsistent with the US's understanding and presentation of itself. And that's one that it is heavily invested in protecting. So nearly any system of knowledge creates its own unknowable things, and those who breach it can expect to feel like Sylvia Wynter. She says in this quote here: “If they are right, then everything I'm saying is wrong.
But if I'm right, I cannot accept them. Expect them to accept it easily.” And this is about the point when I realize that I am not just interested in missing things. I'm also interested in the collective realities that are locked away from a groups, shared understandings. Because to understand them would be to rock the core of who that group presumes itself to be. So I'm interested in the unknowable.
And most importantly, I'm interested in what it takes to make it known. Part Two: Make True Things Known. Here's what I think.
The unknowable hides in plain sight. But it's protected. It's locked behind walls that have been built up over time to block it. So in order to make it known, you have to break through that protection. You have to make visible the very road that you've been traveling on to take something that is familiar. And you have to render it strange anew.
And this is about when I started to get into archival footage. I like archival footage because it says the subtext out loud. I think, any system of values, knowledge, hierarchy or relations, it lays the foundation for its own unknowable things. And media created in that system is encoded with all of that context of unknowability. So when you have archival media, it's like you have a time capsule, time capsule of all the assumptions of the day. And then because the current moment you're in is a different one.
You have the space. The archival media introduces just enough distance to produce a sense of dissonance, which then makes it possible to see your own world differently. It's easier to see this with an example. An example I'm going to use is one that affects everyone, no matter who or what we're talking about, which is an example that is around food specifically the production of food. What I have here on the screen are three quotes from Earl Butz, who was Secretary of Agriculture from 1971 to 76. The first quote says, “Food is a weapon.”
The second one, “Get big or get out.” And the third,”Plant fence row to fence row.” These are the three quotes. The Earl Butz is probably the most famous for. The first one is referring to the global power and being able to produce huge amounts of food. It's pretty straightforward.
He moved. Earl Butz said, This is a weapon. The ability to be able to produce food at scale is a weapon.
The second quote is kind of your standard encouragement of the growth. You know what is maybe a little different? The second quote says, Get big or get out. And this is this is really Earl Butz’s mission. He wanted to encourage the growth of big corporate farms over smaller, smaller enterprises. And then the third one, plant fence row to fence row. This one is a bit more like standard maximization of space.
So really, also maximization of capital spawns a production. So the background to all of this is that around the 1970s there were these fears of food scarcity that that really reached their height. In this time, though, they began earlier through the so-called Green Revolution that began in the 1950s and 60s. They were fueled by this idea that population growth was going to be a huge issue that would need to be dealt “At present population growth rates world food production will have to double by the end of the century just to maintain the present inadequate level.” This quote from John Hannah really synthesizes those fears, those fears around population growth and the amount of food that it would take to feed everyone that's really rampant through the 60s to 70s. So this was the fear that the political administration and agencies at the time were worried about: The threat of there not being enough food available in the world.
So the US threw itself into increased mechanized industrial food production, which was made possible by applying new technological methods to the growing harvesting and packaging of food. And in that moment, no one really questioned this assumption of population growth, which would prove to be correct. And no one question that the assumption that increased production through technology and big, big agriculture methods was the only solution to that problem. The clips that you can see here in the background are from a recent work of mine. They are gathered from archival footage that is taken from the U.S. Department of Agriculture, the USDA, which is the same department that Earl Butz worked for.
And what they show is how is this myth of the U.S. of survival residing and its ability to increase industrial agriculture technology, and how this myth conveniently allowed for reproductions of some of the same labor dynamics as had existed in earlier times, Even though these same labor dynamics were wrapped in the veneer of new technology. So if we were in person, I would show you a little clip of a clip of this piece that also played the sound, as it is, I'm not going to. But I'm going to tell you that what happens in this clip, this is actually an interactive. I'm going explain the piece to you.
This is an interactive piece. People interact with it on the website. You change the clip, the clips by clicking on the website or by advancing on it.
And then in the background there is this kind of laid back soundtrack, this groove that really lulls you in and that gets you into the sort of rhythm as that groove is there. Then you start to hear these voiceovers that ring out over the track and the voiceover overs are taken from other archival footage that I gathered. So programmatically grabbed and assembled all of this.
And really what I'm trying to do in it is to make the myth the parent. I'm trying to make it visible and make it so that you can feel it, so that you can see this this dichotomy in the way that we're using these new technologies, but reproducing some of the same dynamics. And which when you hear the voiceovers for the track, which promise these, just fantastical things, which today we can we really can tell have led to some of the same issues that we face with industrial agriculture.
I'm trying to make it so, look, it doesn't feel academic. It feels like something that you can feel. I'm trying to make it possible to know right now what was hard to know then, which is the kind of work that myths perform when it comes to the technological. The title of this piece, by the way, is “40% of food in the US is Wasted.” And that is a that's a present statistic. Well, the full title is “40% of food in the US is wasted (How the hell is that progress, man?)”.
And that last bit is taken from one of the voiceovers. But that first part, the statistic that is a present statistic, and it is also taken from the USDA, which is the same department that was one of the largest proponent proponent proponents of this industrial agriculture revolution. In all accuracy, the full statistic is that 30-40% of all food produced in the US is wasted each year.
And the absolute irony of this is that in the 1970s people were trying to double the production of food and that has been done, been able to actually increase food production. But we've done it just to arrive at a place where nearly half of that food, almost So there's an unknowable fact here, which is that in our vastly unequal world, feeding more people is not just about production of new food, it's about the distribution of existing food. But to know that would invalidate is the power of the story of unbridled technological development, which is attached to just global and market dominance. I say all this to say that there's always a myth, a narrative, a story that I think works to block unknowable things. It's a story that's comforting to believe.
One that serves multiple interests and therefore feels very firmly locked in place. And in some ways, that agricultural truth is beginning to be able to be known. It takes a long time to build up the walls of that, protect unknowability, and it takes just as long to tear them down. But years of efforts from organizers and food laborers and farmers and NGOs and even the U.N. have caused a kind of opening. But this is an uneven process.
And even as those walls are being torn down, they're also being rebuilt. And here's the proof. Here's a present quote from the largest insurance companies just tied to these food companies as well, which says “By 2050, the global population is expected to hit That means that to feed everyone, it will take than it has produced in the world today, according to the UN's environmental program. We reproduce the exact same, exact, same logic.
So this process of making true things known, it's not easy. It's not obvious or straightforward. How do you convince someone that a narrative isn't isn't the full story that isn't just what they might like it to be, especially if there's no incentive to listen or especially if to believe that could could just destabilize the world as they know it. I'm asking this this genuinely, I told you at the beginning that I'm very much in progress on a number of different things right now.
And one of the things I'm working on is a project which has stalled in some ways precisely because of this question of the unknowable. In my project Ground Truth, I'm working with a team to create a machine learning model that can predict which counties in the U.S. hold hidden graves from the practice of convicts leasing Convicts leasing, for any of you who don't know, was a period of forced labor forced labor that took place in the 19th and early 20th century. It took over after the end of slavery, but it encoded a lot of the same, really. It encoded even worse racialized forced labor dynamics.
What prompted this whole project was the discovery of one of these mass graves in my hometown in Sugarland, Texas, back in 2018. And when this grave was discovered, everyone in my hometown, myself included, was shocked with I think there was a sense that in this sleepy little town called Sugar Land that such that this kind of gruesome thing, how could this be possible? But the strange thing is that actually we had no reason to be shocked because it was obvious. Our town is littered with the history of this period, from the physical infrastructure to the names of the streets and landmarks. The names that they bear are the names of the same people who were behind these these exact systems.
And even even with all of that passive evidence, even before the grave was discovered, there were people who had publicly spoken up to say that it existed. This is one of them, Reginald Moore, who constantly would show up at these school district meetings to say, there is a grave here, there's a grave here. We should do something about this land. People are buried here. He was not listened to. When I learned about this, I thought to myself that the only reason what happened was that the school or I should rewind that, I should say that Reginald Moore was not believed until the local school district started breaking ground on that same place and discovered this grave.
And what they discovered was the evidence. They discovered the remains of people who who had been buried there. And once they did, that became a sufficient enough form of evidence for for people to realize, oh, there's something there's something here. We should do something.
And what I guess what there were many things about this incident that that struck me, but one of the ones was that they just happened. The school happened to have been able to dig and see this grave. But what would it have looked like if you hadn't been able to? Well then, no one would have believed it at all. And so I came up with this project as a way to leverage the seeming precision of machine learning. I figured I could make this model, given that you can't dig all over all over the U.S., but
it is very likely that these sorts of mass graves are all over the U.S.. I can use this model to try to predict the likelihood that they were in different counties, and it was, I should say, an impossible model. It would be what it is and would be mathematically sound. But at the end of the day, it could only gesture to the fuller story. All it could do was say the counties that were likely to contain them.
It couldn't. It was no map. It wouldn't be able to point to where where to dig, and it would only be able to talk in terms of likelihoods and percentages.
It could not contain the full story. But I thought that it could be like the remains of the Sugarland 95. Those people discovered in the grave. It could be a form of evidence that could be trusted, could be from evidence that could be listened to. But very foolishly, I didn't consider that the very same forces that made those graves hidden in the first place would be reflected in the data that we needed for the model. It is hard to find the data that can be used for this model because this is a topic that was long overlooked academic literature, histories of U.S.
institutions that just simply remove any mention to the practice because the local historians whose interests lie in positive arcs about their town rather than the grizzlier violence these stories, or because of the long time lack of incentives for discussing such information in public, It's not not very fun. It's not very sexy. In short, what is imperative? The progress of the project project are the same structures that blocked my original knowledge of the Sugarland 95 in the first place. Unknowability cuts across so many different spheres. I don't know why. After having done a whole series of work on missing data that I had to learn that unknowability would creep into affecting this very dataset as well.
This is a video of me calling, calling different counties, trying to ask them, trying to get this information. So we're blocked by the same wall. And I shouldn't have been surprised. You know, all those folks I mentioned, all of whom tried to make unknowable things known. Most of those stories are colored by failure.
I talked about Galileo, he eventually apologized and revoked what he had said about Heliocentrism. Even though it is true. Structural racism continues to exist in the US. It's gotten better, of course, continues to exist and to be denied. And as for the X-rays, well, one of the story of the x rays comes from the structure of scientific revolutions written by Thomas Kuhn, and he talks about this fact that what really made people believe it in the end was not necessarily that other scientists were convinced, but because of the opponents who held a different worldview basically dying out.
So they are the odds are not good when it comes to making unknowable things. So I guess the question is what is the path forward for this? Part Three: Attuning. Now, this is the part that I think I might be the most uncertain about, but this is also the part where we can begin to talk about that photo I showed you at the very beginning, not quite yet though. This is a photo a friend of mine, Okwui Okpokwasili and in during the open is a fantastic performer, a choreographer artist many things and Oakwood for a long time has done these things that she calls soundings. and soundings are kind of exactly what they sound like.
It's people coming together and making sounds, just making sound together. It's not like singing. I mean, it has something in common and that people are making sound together.
But it's not really like singing because in singing. The point, of course, is to sound good. You're trying to to create this pleasing harmonic sound. And that is not the point of soundings.
Soundings are about just connecting. They're about coming together in this strange and intimate space, and they're about just finding each other through sound. So for a long time Okwui had done these soundings. She had done them on her own and she had done them with others. She had done them in person.
And during the pandemic, Okwui came to me because she wanted to do them online. And so she talked to me because she wanted to see if there was a way we could talk about what it meant to do. These soundings, which were so dependent on people sharing space together, to do them together, to do them in online space. And so we came together and we led these sounding workshops online. They were they went well.
But what we found is that in order to get them to work, what we needed to do was not really introduce people to sounding so much as we needed to get people to let go. We needed to get people to clear away. We needed to get them to let go of their judgment, to make space beyond it, to let go of the sense that they were doing something completely weird, something so strange, something that made them uncomfortable. We had to we had to clear something away more than we had to bring something there. And lately, I have been thinking that when it comes to the unknowable and to making true things known, that perhaps it is, it's a bit similar that perhaps it isn't so much about convincing people of the thing as it is about breaking down what gets in the way of the knowing. So I want to I want to show you a piece that I have up right now.
It's an installation. It's called This is up right now in it's called It's two pieces, actually. It's called “The Cloth and the Cable, And These Networks In Our Skin and in this piece, which figures. It features this installation. It has these cables. It has that have cloth wrapped around them.
And then it has a video. And in the video there are these women and they are working together to cut open these cables, to take things out of them and to put new things into them. These cables are meant to stand for the Internet. The whole thing is meant to be this sort of allegory for thinking about the very technological infrastructure that is around all of us and circles the globe. Like great veins, like a great circulatory system. And to think about what it means to to, to, to refigure it, to change it, to clear out, to put in new things.
And in the piece, what I'm and what I'm doing is putting in spices and cloth and hair and things that have to do with my own my own tradition as from where am I, where I'm from. But the idea is not that that is the only way of doing it. It's just what I bring to it. It is that maybe there is something to that, that there is something in this prefiguring and there's moving things around and taking and taking out and putting in that can actually get us to knowing things in a different way.
I have the sense that when something is rendered unknowable by a paradigm, then you need more than just the tools offered by that paradigm to get out of it. And this is why I speak of pulling things from my own culture. But I say that it's not the only way that maybe there are many other ways of doing this. And so now what I'm trying to do is to think about the unknowable in this way in terms of what are the other things we can bring it that will help us see it differently.
And when I say see it differently, maybe what I mean is just be able to see it and to hold it. And I think I think really this is this maybe is what I'm searching for with all of this. When I was drawn to missing datasets, in the beginning, it was never just about the data. It was about what the data said about that thing, the systems underneath, what they said about what it what it meant to be in a world where data had this kind of power. And I think when it comes to unknowable things, perhaps it's quite similar that maybe making sense of these becomes a way to see actually the system that we are in a bit differently and to be able to intervene in it and change it and remake it in ways that are that are open to more of us.
So all of us are two different, different fluidity and flexibilities and ways of knowing. I don't know. Like I said, there's a bit of uncertainty here, but this is what I'm building towards and really more than just the installations or the workshops and the talks from building this is openness to all different things, all the things that are challenging, and then that flexibility and fluidity of knowing when to switch between different ways of knowing and different ways of being. And while I don't know where that's going to lead, I think it might be okay to start from a point. I think my whole what I, what I keep learning is that it's okay to start from a to know the point that you're starting from but not know the point that you're going towards. All right.
I'm going to leave it at that. Thank you all. I’m going to stop there. And I'm going to show the slide because I just wanna make sure I show some credits. Right.
Thank you for that performance there, Mimi. Kristen, are you still around? Let's see. So what we're going to do now is moving to Q&A. I don't know if Kristen had any comments to add about it, but if she does get a book for now. Brian, you can hear me? Yes, I can hear you, Mimi.
Yes, yes. Can you hear us? We're going to hear it for Q&A now. Oh, no. Hello? Can you hear me okay now I can now even hear you. Oh, my goodness. I was like, Wait.
Oh, my God. Has no one heard me? This holds all your. Wow. Okay. Thank you so much. We are going to open it up for Q&A now.
Yeah. So if there are any questions for our presenter, we have the Q&A at the bottom of the screen. Feel free to put those questions in there.
For some reason, if you prefer chat, we can also. That is also open to you send as long as you think of them and we will respond. Thank you.
And if you don't have any questions, that's fine too. Best Absolutely. Cool. Yet at 4:00 on a Friday, it's you know, it's a little rough. We do have a question, Mimi, from Kelly.
So what inspires you most today? What inspires me most today? Hmm. It's funny, the hard part, Kelly The hard part of that is but today, like I did a lot of work on a Friday right now. Yeah, at 4:00 on a Friday. But it's Thursday. Thinking it up. Yeah, I think that's what it's a you know, I like the question because.
I don't know. I don't know. Okay. I would say there are two answers. One is the kind of simple one I feel very inspired by. Really anybody is creating work that is about creating work that seems a bit impossible, cutting work that is against the odds, creating work that feels like you are you are trying to bring about something new, even though that's a very challenging task.
So this this kind of willingness to fight a challenging battle, I think I'm always really inspired by and I think so many of course, there are a lot of artists I can think of that do this, but I think that actually unfolds across so many spaces, across organizing and policy and research and so on. So I always I find that that in general to be very inspiring as well as I find specificity, a kind of honesty and connection to to the specific to the specifics of a situation or context. I'm always inspired by people who dive deep. Yeah, I'll leave it at that, actually. Well, great, because we just got a second question in for you. So this one's from RO.
So as there are more of us who want to put novel things into the cable, perhaps that there must be others who want to control, who can and cannot do or want to maintain the cables as they are now. How should we view this issue? I can't tell you how you should do it, but I can tell you how I view it. I think a lot about structures and systems. I think a lot about the incentives of a system.
And what I think about is how a lot of the systems that we have have having there's a lack, I think, about a system I think not just how does it work, but what maintains the way that it works. So when you say that there are people who are against that, that is 100% true. But then I like to go deeper and say, Well, why? What is it that they are protecting? What is it that they're actually maintaining? And then what does it look like to pull away at that? I think that it what the reason why I say this, why I say that this is helpful for me is because I think that allows me to think allows me to feel like I'm more at the source because it's not it's easy to be it's easy to fall into being like they're the heroes or the villains or this and that. But also there are there are the ways to kind of guide how people behave. And if you can change the ways that guide, if you can change the incentives of a system actually that can do far more than trying to convince individual people or having to feel like you're fighting individual people. Now, don't ask me how it is that you change the incentives of a system.
That is that is the bigger question that I can't tell you that I feel. And I'm often grappling with that myself. Brian, Did you see, there's a question in the chat as well. No, I didn’t but think I can read that one. It says, I'm amazed how differently you think, Wow, you're a genius.
What did you want to grow up to be when you were a child? My gosh, what a question. Oh, wow. You've been you think it's a simple question, but the truth is, I as a kid, I really could never figure out what I wanted to be. And I really only very recently have have have let go of my the like, the way that makes me feel, I would say I think as a kid, I never knew what I wanted to be, but I knew what I wanted to do. And what I wanted to do was to try to make sense of the world around me so that it could be different. And I think that the way I never really I didn't actually when I was a kid, I spent I wrote a lot and I was very I wrote a lot of like, fiction and poetry and had a lot of friends online who I would share it with.
But I never thought I would be an author or a you know, I didn't think I would be an artist. I think what drew me to the space of art is that I think of so many of the fields. It's just has the most latitude as an artist. You can you can do so much, you can make a film, you can write a text, you can do things that are with people. You can it's you just can do everything. And people, nobody really blinks.
People or nobody bats an eye, people will allow you to do it. And so I think that's how I ended up in the arts, is that I felt like it was the place where I could take all of the things I was interested in and I could slot it into something that was more culturally legible. But even now I can't. I'm an I am an artist there and I have no issue saying that. But I do think that in some ways I'm a bit of a different artist in and even when I have to explain to people what it means that I'm an artist now, do you paint? I say, No, I don't.
I like it, but I don't do it. That's not what I mean. There's still that bit of friction. And so that that friction that I feel like from when I was a kid and I'm like, I don't know what I want to be, I still feel a little sense of it.
I think I've just come. I’ve come to peace with it. Thank you for that meaning. So now we have a two part question.
So the question one, I guess it's just two questions. Could you elaborate on the relationship between the fluidity of humanity and the structured nature of industrialized society and how the detention informs your creative expression? Great. Can you read that one more time, Right? Yes. It's a bit of a doozy. Could you elaborate on the relationship between the fluidity of humanity and the structured nation, the structured nature of industrial industrialized societies? Yes.
And then how this tension informs your creative expression? Yes, I think this tension is kind of at the center of a lot of the creative expression, because I think what would be you know, I think whoever is asked you already know about that. You talked about the structured nature of industrialized societies. I think you already know about that.
I suppose the relationship between the two is a difficult one because I told you, I think a lot about structures and I think a lot about categories and I think a lot about classification. These these tools of structuring the tools that structure, the tools that standardize, the tools that make things so that they are neat and able to be easily grasped, easily reproduced, easily abstracted from, etc.. And the thing about this is that I don't necessarily think that it is all bad. That is not the word.
What I mean is that I think it is a task or it is an approach that is very well suited to a certain type of work. The problem is that I think it's an approach that has been over applied in very in too many other spaces and it has been also held up as the only approach that matters. It's like this piece, the work I was telling you about, the project with the graves, how how we have to we have to think about what works, to think about what are the forms of knowing that are that can count as evidence. That was a thing we used to think a lot about and making the project.
And part of it is because there is this form, this sort of structured nature of industrialized societies and of much more. I would say that nature is so powerful. It is the form of evidence. It is you have to put something into that form. So as I think why I was also so interested in data, you have to go into that form for it to carry weight and because of that it almost erases the fact that there are things that is, that there are things where it's very helpful to put into that form.
So now the fluidity part, to me, the fluidity is not necessarily just another approach that is left, that is that refuses the top down bureaucratic imposed grid for a more like loose structure. That that is one approach. But the real fluidity is knowing when to switch between these different approaches is knowing when actually we should use this more structured, more precise way of of approaching the world. And then when we should switch and say, no, there's something here that cannot be grasped and that is the point. There is a different way we need to enter this through a more sensorial form or we need to we need a different way of approaching it.
And that's to me, when I think about fluidity, that is, it is how do you switch between different forms of approaching and making sense of the world? Because all of them are ways of making sense of it, and we do need to do that. But it is how we do it and which ones we use and whether we have a hierarchy with them or we allow them to be in really in this more beautiful relation, that that's the thing that I, that I want more. Thank you, Mimi. That was awesome. So next question.
So looking forward, what future projects or themes are you excited to explore in your art? Are there new mediums or technologies do you plan to incorporate into your practice? Thank you. Yes, thank you for these questions, everyone. I am, the talk I've given you now. I told you, you know the ground so the model doesn't always the map doesn't always fit the territory or the model doesn't always fit the world. The talk I've given you now is actually, in a way, an earlier version of I'm really now, I think I'm one of the things I'm doing is diving a bit deeper into this question of unknowability, and we're finding it a little bit more so that it can actually result in a whole body of work.
So there's a lot of work I'm doing around that. Another thing that I'm doing has to do with the piece I showed that machine learning piece with the graves. I don't know if that piece will be able to be done in the way I had originally intended it to, but already it's led to too many more interesting places. So I have a lot of work that will come from that. And then I'm in residence right now at Cornell Tech and I will be working on them. I'm working on also this third sort of it's like, I don't want to it's really almost like I'm creating more of like a magical realism world.
But that also involves using a lot of AI specific models too. And I'm working with a lot of the tech folks there. I will be working with them this year to create that. Thank you. And now from Nurse Longmire, you provided several examples that point to evolution of projects over time. How do you know when a project is finished? Yes, I would say that in the long term I never really know.
But in the short term it is just a feeling. I think of it not unlike my partner as a journalist. And one of the things that we have to talk about is how to be a good journalist.
You have to build the sense of knowing when when something is a story is to be able to sift through all of the world in front of you. Then you hear something or you stumble upon something and you say that actually, that's story. And I think there's something really similar with arts where knowing a hunch for me, it's always a hunch that leads me towards a piece. But then sometimes there is a sense of I feel like I've wrung all that I can look. I've squeezed out all I can from this for right now.
So I need to set that away. And so in the short term, like this is this needs to be closed. I don't know why, but it needs to be. I can it's really more a sensation.
I feel this way with some of the work that I've talked about today. Actually, some of them are coming to a point where something is closing, but there's a longer narrative, you know, there's a longer arc and along that arc, actually when I close something, it's not because it's done, but it's because it's going to be re the some of the ideas, the things I learned from it will be remixed into something new or will be advanced upon or played with or re reorganized. So that's a long answer for really what is a very short answer, which is that I don't know. I don't know other than just feeling it. Yeah, Yeah.
Projects are hard. Yeah. You know, I think we could ask the air there. So that was the last one we had in queue. If anyone has any additional questions, any more thoughts in their minds or comments to make, feel free to post them in chat or Q&A.
Yeah, we'll take, we'll take them. Or if we're all done, we can wrap up and have a nice end, a nice Friday workday workday. Right. In the meantime, while people are thinking about that, I am posting a Facebook Copy pasta survey. So if anyone has any recommendation for future events, things they'd like to see input on this event, you can read all of that.
Oh, except when I posted wrong through the link. We also have information about the research comments of your on campus and you'd like to keep up with us. We have events available through our public site, Twitter and LinkedIn, so feel free to connect with us and we look forward to hearing from you on the future. You also get a follow up email from us. I think that was in the copy pasta basically with any resources that maybe you would like to share with us to share out to everyone who attended.
Maybe that website you mentioned sounded interesting, the interactive one. So I might I might pick your brain on that one after the session. Yeah.
Other than that. And then also just want to note as well that this was in partnership with the steam factory. So Michael, if you want to put any links in the chat as well for the steam factory, feel free to do that for our panel or for our guests who might not be familiar with the steam factory.
So this is again, a presentation that was in partnership between the Research Commons and the Steam factory. And we are so thankful for you being here with us today and presenting. This was a fantastic presentation and I think everybody really enjoyed it.
So thank you. Thank you all. Thank you for taking time on a Friday. I don't take it lightly and thank you for agreeing to a Friday.
We appreciate it. And with that, will go ahead. And I don't see any more questions popping in chat. Let me just give one more check. I don't believe so.
So we can feel free to wrap up the event. So thank you everyone for coming and look forward to that email coming from us in the future. And Michael, I'll make sure that the Steam Factory's link is also included in that.
Yeah, thank you. And thanks again. This was a fantastic talk. We loved it over here. Thank you very much. Thank you, Michael.
All right. You all enjoy the nice Friday and the hopefully beautiful weekend.