>> Michael Cohen: I'd like to welcome everybody and wish everybody a happy Valentine's Day.
It's nice of you to come in on Valentine's Day.
>> Jason Salavon: Share the love.
>> Michael Cohen: Share the love with everybody. I'm extremely honored to Jason Salavon
here. I've known Jason for, I don't know how long. We have been trying to figure it out. It's
probably, I think it's more than ten years. I know I've been a fan of his work for close to 20
years that he's been exhibiting it. He's had worked in numerous galleries and museums around
the world. I got attracted to it about the time that we started thinking about computational
photography and what it meant to compute on images. I think you'll see from the talk that
Jason has taken a very different idea. A while ago we started to think about what it meant to
take a whole packet of images and process them and obviously, once you have a whole bunch
of data, thinking of images as data, the obvious thing to do is to begin to average things. I know
this set here that he did was one of the first things that caught my eye. These are real estate
listings that through the magic of what Jason applied to them gives you sort of the gist of the
places, and the thing that pops out for all of us living in Seattle is it's easy even without the
labels to know which one of these is Seattle. We'll let you guess which one of these. We've
lived here long enough to recognize those skies. Anyway, Jason, as I said, it is exhibited in
numerous places around the world. He has worked, has shown in galleries around the world
and museums around the world. Some of his work actually sits in permanent collections at the
Metropolitan Museum in New York, the Whitney in New York, Art Institute in Chicago, the LA
County Museum, if you have ever been down there and in the National Portrait Gallery. I didn't
realize that one at the Smithsonian. Sort of curious as to what ended up in there. And also the
Microsoft Art collection contains I think at least three of his pieces. I don't know when you're
walking around the building you should keep an eye out and see if you see them and you will
know where they came from. Anyway, so it's a great honor to have Jason here to talk to us
about his work a little bit. Thanks Jason.
>> Jason Salavon: Thank you. Is there a way to lower the lights a little bit? It's going to be a
very image intensive.
>>: You say it out loud and then…
>> Jason Salavon: Lights.
[laughter].
>> Jason Salavon: It is really nice to be here. I'm escaping the polar vortex part 2 1/2 in Chicago
right now, so I appreciate that as much as everything else. I'm an artist and I'm going to do sort
of my version of an artist talk, which kind of spans sampling. It kind of spans, I don't know.
Maybe not 20 years, but probably 15 years of work, and I'll sort of sample little bits there and
focus more on more recent work. Since we have sort of not a huge audience, I'm happy to
engage and answer questions and even go with digression, so we don't have to wait for a Q&A
at the end or anything. It sounds like you guys are comfortable piping up, but please don't be
shy about it. I think of myself as a computational artist, basically. I just usually call myself an
artist. My tools are writing software, using data and I've been doing that since I was an
undergraduate. I made a conscious decision to start exploring art making through, directly
through writing software. I do want to show one image, this image first just to kind of frame
the conversation a little bit. This is a painting that hung above my bed when I was like five
years old. It was about that big. It was maybe a little bit smaller than that. And it's acrylic on
panel and it's a painting my dad made in the mid-‘70s. That's the world I grew up in. He still
makes work of all kinds. He's not a painter so much anymore. I grew up around, at this point
he was making lots and lots of really interesting weird paintings and I grew up with that. It was
like a normal fact of life. I think it did have a lot of impact on where I went. One impact it had
was I drew and painted a ton as a kid, but by the time I was in high school I had zero interest in
being an artist. I had seen kind of like a lifelong, at least ten years of sort of struggle. We were
living in Fort Worth Texas and there's no way this has any market in Fort Worth Texas in 1975.
[laughter]. There's just a lot of this stuff around the house, basically. I loved it. I was really
appreciative of it. I sensed the passion and all of that, but it did not set a good example for -- I
could feel the struggle. That's what I'm sort of saying. And I had, it gave me a different
impression of what being an artist was that was maybe a little less romanticized. When I
started undergrad at the University of Texas, I took a drawing class in my first semester just on
a whim and I just really fell in love with it. Being separated from, having an environment that
was my own, I really, really started to sort of attack making art with a lot of vigor, but also I
ended up being a CS minor and I was taking technical classes the whole time and I was almost a
major, but I didn't have enough hours. But that combination, you know, by my junior year I was
thinking I think there's really interesting part two be made through writing software through
this sort of thing. This was the early ‘90s and no support from faculty. Faculty kind of
begrudgingly went along with my ideas. Just to show kind of some of the things that I did in
undergrad. I don't know if it's that useful, but this was like eight 380 page cotton paper book of
tile repeating forms that I called carpet maker, and dot matrix printer, 1991, in an apartment in
Austin and I just had this kind of old -- I'm a software operating system agnostic. I use all
operating systems, so whatever references, you'll see works that are made in all different
environments, but this piece was made on a little 9 inch Macintosh. It's simple, but for me the
magic of it was that I would write this little bit of code, press go, go to bed, wake up and have
30 new friends that held surprises that I couldn't anticipate, like I didn't anticipate that this
form would happen. That experience, the surprise of what kind of autonomous software
processes can do, shaped, you know, random processes that are kind of shaped, that surprise
stays with me today. That's a really, combining data and having sort of slightly counterintuitive,
really counterintuitive results is still super important and meaningful to me. I ended up going
to the School of Artistry in Chicago for graduate school. In 1994 they had an art and technology
program and was one of the few art schools, kind of formal high-quality art schools, that
actually was sort of thinking, had forward thinking ideas about technology, the relationship
between -- they had a strong robotics area. They had strong 3-D graphics, and I'd kind of made
up my mind that it was sort of the area I wanted to work in. This is a project that was part of
my MFE thesis in 1996 that's called The Grand Unification Theory, and these are photographic
prints. A lot of times I make my prints through photography rather than printed in ink jet or
another form. Partially that was because it was really the only way to make really good largescale prints in the ‘90s. This is, every frame of Star Wars, or every second of Star Wars, one
frame per second, so one 30th of Star Wars. It's arranged, not by order, but by luminosity,
right, so it's not narrative that's driving this shape. This was at a point when there wasn't a lot
of like, people weren't working with cells of film. That sort of stuff was around. I had taken a
job, during graduate school I had taken a job at Viacom New-Media which was Viacom’s new
soon to fail videogame company. I worked on the Beavis & Butthead game and I worked on a
failed snow crash and your interactive pet dinosaur. One of the teams was basically folded into
Fungee [phonetic] and ended up here. The point of all of that is I was using, at night I was using
Silicon Graphics machines to sort of capture and build these images. There was nothing at my
school that could handle the amount of data. We had, do you guys remember Silicon Graphics?
I think some of you guys do. Yeah. We had an Onyx, four processor Onyx. It was the size of a
refrigerator that is less powerful than my phone. Maybe. Used to hate that. Anyway, so that's
every second of Star Wars. This is every second of Snow White.
>>: Do you have a lot of lawyers calling you about that?
>> Jason Salavon: Yeah. [laughter]. So we can talk about fair use, yeah. That's an interesting
problem. This is every second of, it's a wonderful life. And this is every second of the throat.
My interest in sort of performing these operations almost clinically was some expectation of
the kind of variability, the kind of variance between really different kinds of genre films, sort of
archetypes of genre film and the kinds of results. You get this really beautiful gradient. The
histogram is like really distributed, right, versus this is a little bit of this, but mostly it's just
inside two rooms, the same lighting. That combination of abstraction and sort of known
recognizable content I think is an important thing to me. I think it's an important thing -- if
you're thinking about -- Michael said something about stacks of photographs as data. That's
completely how I think about it too. And if you think about all of these frames as data, the
choice of the content is really kind of key for me. It's really the specificity of these films is what
makes or breaks a project like this. At that moment, again, there weren't many people making
sort of computational prints with this sort of feeling and I was fortunate to start working with a
gallery. I ended up leaving Viacom. I went to Midway and worked on the blitz football games
for Nintendo 64 and other things. I was an artist programmer, kind of hybrid, so I would work
on the engine little bit and then do modeling and talk to artists about, you know, kind of the
specific needs of the engine. It was a cool job. I enjoyed working at Midway. But I'll go while
I'm continuing to make work. I'm having exhibitions and so to talk a little bit more about the
piece that Michael started with. For me it was kind of an intuitive switch. I've got this grid of
images and I'm sort of arranging by luminosity. It's not too big a stretch to start to think about
those images, those fields of images in other ways, so kind of stacking average, take a mean or
take a median was not too far from my thinking. But again, it's like the content for me is what
kind of makes or breaks it. So they're all like homes in the median price range. They're all
realtor photographs and the only alteration would be that they're cropped to the same size
from center. There's no other alteration. The southern ones have sort of blue skies. L.A.,
Orange County even has a street, because you've got all these ranch houses so the
photographer always has to get far enough out to get the bit of street in here. New York and
the five boroughs, you get more of a peaked roof and you have like gangways between
buildings from the boroughs.
>>: I got a question. Did you do anything in particular to achieve the almost pastel feel of it?
>> Jason Salavon: I did no, minor adjustment for photography. I'm not color adjusting.
>>: [indiscernible] the texture [indiscernible]
>> Jason Salavon: Yeah, that’s all in the architecture. One thing I found was if you get over the
low 100s with these sorts of really tight sets of -- and it's funny because the way I speak to an
art audience is really different than the way I speak to you guys. I'm enjoying an ability to speak
in a slightly different language than I usually do. But these are really constraint sets of things
and if you put that number up past sort of 150 the thing goes to mush and if you are under 75
you really can't make out distinct features. I kind of found naturally a kind of sweet spot where
you have the kinds of little striations that are indicative of individual pieces of architecture but
they're not recognizable. It's hard to pull anything out. That's really important too. I want to
hit a kind of sweet spot of abstraction that still sort of hints at meaning and recognizability. If
you want to 200 I think you'd still have the same kind of palettes, the color palettes would still
remain, but things would just get mushier and mushier.
>>: So if you take 75 pictures out of thousands was there some curation about I want to get
some of these [indiscernible] or was it just random?
>> Jason Salavon: It's random and it's to the point where, not in this project, but, and I've only
done -- I think people know me for these works. I'm strongly identified with these works, but I
probably have only done eight of these kinds of projects. But in later ones I would have
assistants pick out images for me. I wanted to distance myself from that process to the degree
that I would just describe, pick, I'll skip around just to -- in this project, which is commemorative
photographs on the internet, I would tell an assistant, pick a hundred photographs of a wedding
couple with her on the left. I want a hundred photographs of the Little Leaguer on one knee.
I'd probably show some archetypes and show, pick these guys. This is what we're looking for. I
just want the classic versions of these things. And it's amazing how easy it was to find these
things. I really am jumping around, but this might be interesting. This is like one of them. It
kind of makes a little bit of my point about what happens as you go through, you know, five -you start to -- what's interesting about these projects to me is even with five you have like the
vector of where it's going is already fairly, purely defined. It's already, it already tells you what
it's going to be and then as you shoot over that amount it sort of just becomes more, the
mushier and mushier version.
>>: [indiscernible] dropping the faces?
>> Jason Salavon: What's that?
>>: [indiscernible] cropping you get?
>> Jason Salavon: This one has a little alignment, but that's it and it's just manual. I prefer as
little of that kind of stuff as I can. This project was one of the first ones. These are the high
school graduation photographs of my mother and my high school’s that are both in Fort Worth
in 1967 and 1988. This required no alignment, no anything. You've got, you have this sort of
standard size. And I want to lean on the photographer's definition of what the set is. That's
kind of an important part of it, that I am not seeking to make things happen. The set sort of
really expresses itself. You get little anthropological things. Fort Worth was very conservative
and 1967, but some of the women are starting to get a little hippie here, you know, like things
are starting to happen. I do commissions occasionally. I did a commission for a couple some
years ago and they were the class of 1972 and they were in like Springfield Missouri or
something. By 1972 both the man and woman have hair going past the shoulders. And then by
the time I'm in the Reagan era, it's full on preppy. Although you can tell the demographics of
the area have changed. We were in different high schools but they were sort of similar, and
this is really a sort of complex demographic. Also, we still wear the same tux tops and the same
sort of scooped, which I think is funny 20 years later. The other thing I'm interested in in these
kinds of things is how for me, I've been around these images for a long time, these have really
individual identities. This is a meta person has a real identity for me which I think is spooky and
weird. I'm in there to with 120 other high school seniors, but this is, he has a strong guy. I
don't know if his name is Doug or what his name is, but he has that quality. I printed these in
two sizes. One print size is this big basically, so this sort of really massive, fun than the 24 x 36
wallet size version.
>>: I have a question. I love the fuzziness, the pastel quality these things, but have you ever
experimented with trying to morph a bunch of images together as well so you actually have
eyes, ears, bone chin…
>> Jason Salavon: Yeah. In different projects that are I think distinct, but it would be fun to talk
about how they are similar. I'll show in a second. The one thing, I want to move on from this
sort of average stuff. Maybe I'll show another one, but the interesting point to me from like an
art history point of view, so lots of people say things like they look impressionistic. You guys are
saying pastels; I think that's anonymous, I think that usage is about Impressionism and Turner
and other kinds of -- so painters at a certain point, especially when photography started,
painters really started moving away from sort of accurately representing things to sort of
abstracting things. So Monet painted this cathedral over and over again so he could sort of kind
of take it from specificity, to some kind of attractive generic. And I wonder what it is about, I
don't have an answer for this, but I keep wondering what it is about a kind of simple
mathematical relatively simple process applied to some set of common images that starts to
naturally harken back to painters sort of exploring abstraction. What's the relationship
between that kind of exploration in abstraction from an individual human versus a kind of
algorithmic mechanized exploration of abstraction, and why is it that they look similar? What is
it that, is it something isomorphic or something related between the two processes? I don't
have an answer, but I do think that it's an interesting problem, interesting thing to consider that
these two kinds of abstractions are so, do sort of look alike.
>>: I have a question about that. There's a variance between like 100 and 124. Are you
curating the numbers to get to a final sort of composite that sort of feels right to you, or what's
the difference?
>> Jason Salavon: It's weird because I'll do things in some project and then I'll completely
contradict that thinking in another project. I think at that moment I thought it was boring to
have them all be like exactly 110. I wanted kind of a natural variety. I was able to find more
here. I like sort of that looseness of the sizes of the sets. I don't think I did much curation. I
think I dumped images that were sort of so -- again, this is, we're in, I think we were in the ‘90s
when I did these. I think I did three and I did three more, so right around 2000. People forget
how crappy photography was on the internet in 2000. Everything was 644 x 80 or smaller, so I
think I dumped super low-quality stuff, but the guiding vibe was basically a kind of looseness.
I'm looking at them. I think I was also kind of bracketing them by population. I don't think it's a
coincidence that New York and L.A. are the two biggest numbers. Seattle has the smallest. I
think that, I'm vaguely remembering that, but that's in contrast to the hundred special
moments which is called the hundred special moments, newlyweds, kids with Santa, where I
wanted exactly a hundred for each one. I had just gone a different way where then I wanted all
of the sets to be sort of identical and use that sort of 100. You asked about morphing. I really
am jumping around, but that's fine. There's a whole, more recently in the last five years I
occasionally do these projects that are essentially, this is an industrial monitor, so it's meant to
sort of feel like a light box. It's actually a four-hour animation that's moving so slowly that it's
literally outside of perception. The speed is not trackable, but what it's doing -- this is like a
super sped up version. And it's a literal morph of mesh geometry. This is all rendered. And
there's basically four biological key points, like baboons, like I really went through great
expense to model a baboon skull, a human skull, a boar skull and a bear skull and then sort of -we even set up a rig so that you could put any proportion of the four schools. They're
topologically identical, so they can be morphed into any, you can just pull the, and then there
was just as beautiful design project of just doing like a how much, at this point in the animation
how much boar, how much whatever. They do hit each key point at some point, but mostly
you're in sort of fictional biological space, which again if I said that in an art talk people would
be like what are you talking about. So you are in the sorts, you are traversing -- I think like for
me a lot of my work is about dealing with sets as space and how to traverse or collapse or
whatever different kinds of sets. All these different frames they could, or I actually did average
a big chunk of these just to see what that looked like. It looked kind of like what you would
expect, so instead of overlaying the set, I kind of generated it and then I just did a walk-through.
But also, I'm really concerned with traditional art issues. This is a still life. It's a classical Vonnie
Toss still life. It's sort of meant to look like a Dutch still life. It's still. Also people are like, what?
And they walk away, and they come back five minutes later and maybe they get there mind a
little bit blown by the fact that it's something different. I think people like to have these around
because they can, they live with them and they are surprised by them. I think for me it's like
that kind of piece is a similar approach to these pieces. So while we're talking about old
masters, this is the last one. I'm not sure I'm going to do any more of these sorts of basic
averaging pieces. This feels like the last one. Never, say never, but. And this is entire portrait
ooves [phonetic]. In this case I sought to find every Frans Hals portrait I could find. This is all
the Frans Hals portraits and these are all painters painting around the same, within 50 years,
VanDyke, who is the only artist who at the time is doing three-quarter portraits, but half of his
portraits are Prince Edward and he always wants to show off his fancy clothes. This is
Velasquez. This is Rembrandt. Rembrandt really distinct in his use of black in the sort of
punching the glow. I think that my work is sort of having some branches and tendrils. One of
the branches that has been with me for a long time, this is an early 2000's work, is clinical
graphs of data whose intentions aren't necessarily about teaching. This one, and that becomes
complicated. This is shoe production in the U.S. These are, this is all one three-dimensional
graph of shoe production the U.S. from the ‘60s until the late ‘90s, I guess. There are four
photographic prints that are again printed photographically. They are 4 x 4 foot. I also did,
there's a video that goes with them. This is just a little fly through of the data set. This was all
sort of scripted. This was rendered in Maya, so it's using Maya’s scripting language which is
now Python, but at the time they had their own scripting language. The thing I was interested
in is I want to take a banal data set, something that I think was just having kind of no kind of
effect, like shoe production was whatever reason I was thinking of. Take all the sort of census
data and tried to make it like psychedelic, like I wanted it to be -- I didn't want it to learn about
shoe production. I want it to learn about squeezing data into different kinds of shapes and
forms clinically, so if you have a key it's readable. This is actually the past. This is the present.
So the timeline is kind of a vertical. Distance from center is basically number of shoes produced
and there are 31 categories. Women's heels, children's play, and men's work and all these
different, the census tracks all of these different categories of shoe production. The weird
interesting thing that came out of it, well a couple of things like many people, especially the
ladies tell me that shoes are not banal or Monday. [laughter]. I get that a lot here I'm like, got
it, point taken, so maybe it's not a mundane data set. But the other thing is that the shape is
sort of like volcanoy. This is the peak of it and the base is down here. That shape, that strong
peak is because we don't make shoes in the U.S. anymore. That big wide base that's us making
shoes in the ‘60s and this is us not making shoes anymore, which I had zero, I did not predict
that at all; I did not expect that at all and it was a weird lesson in a kind of relationship between
data where if the data is telling a story and you're kind of consistent about the way you treat it,
no matter how you treat it, you could think of like an infinite number of ways of trying to graph
that particular data set. Some kind of strong sort of slope will show up in that slow will
demonstrate sort of outsourcing of shoe production. I was thinking I wanted to make this
really, I wouldn't say cynical, but I was making a piece that was about sort of twisting of data for
visual effect and then I still got a kind of social political thing happening without even intending
it. It's got me to thinking about data. Historically artists paint trees. Not so much the second
half of the 20th century, but historically before that especially in Western art, we find these sort
of formal things, people, trees, mountains, different kinds of things, still lifes and you explore
that form over and over again. So you have the history of the still life all the way to today. As
an experiment in different kinds of representations of a form, my feeling about data, which is
like what is data? Data is really just sort of numerical sort of assignment of things happening in
the real world, right? At some point there's something, they are grounded to reality. These
data sets are formal entities. They are, I wouldn't call them real, but in some sense they are like
the tree, representing the tree. I guess that's what I'm trying to say. I'm really interested
artistically in thinking about data sets as these swords of fungible things that still have a kind of
form that always has to be kind of negotiated with and dealt with. I'll kind of follow that up
with talking about this piece. This is a piece that was installed recently. This is a 40 foot light
box in the lobby of the U.S. Census Bureau headquarters, and this image is the U.S. population,
similar to the shoe piece, that the US population from 1790 to the present in these sorts of
sheets. More recently, we installed this thing which uses Microsoft Touch which I enjoyed
working with a lot, actually, which is a kind of haptic interface to the data set itself. I want to
talk a little bit about how the data was, how I sort of made this image, this pure abstraction.
Putting a large sort of data viz in the Census Bureau, I knew, I had lots of meetings with their
social scientists and their statisticians and I was really impressed by their real deep comfort
with and awareness of their data and I thought presumptuous to try to teach them something
about their data, so my interest was in exploring that fungible anesthetic quality of data. I also
wanted to show how it's built. This little bit is in the interface. This is the population of Cook
County, where I'm from. The past, now, so we kind of leveled out. This is the ‘60s. These are
all 3171 US counties, so lots of small counties just making it black. Color-coded by the state
they belong to and we sort of build the form. I basically sort of build this three-dimensional
form and then act as a photographer and pick out a view that I was really interested in for the
static version. The whole thing is really meant as a dynamic piece. That's why the touchscreen
piece is so important, but it's literally like a series of transformations to build a thing, like a -- I
really like working in 3-D with data but in an abstract way so you can have this freedom to sort
of build sculptures essentially out of, you know, this is the births and deaths of people or the
movement of people around the country and that sort of transferred into this abstraction and
it's really interesting to me. Let's talk about a couple of more pieces that explore similar ideas
from different perspectives maybe. These are little photo pieces. I had done these sort of cell
photo pieces since the movie piece thing and I come back to it a little bit. I'm not sure how long
I'll do it, but this is called good and evil 12, so it's just a year and a half old. It leans on, I know
some people here are working on some of this a little bit and I was really interested in that. A
paper that Peter Dodds, whose at Vermont wrote two or three years ago where he had Amazon
Turk, hired people through Amazon Turk to rank the 10,000 most frequently used words in the
English language by positivity. That's the only sort of attribute, so the most positive word to the
most negative word in the top list. And this is that list. So laughter is the highest rank in
positivity and terrorist, right now, is the lowest-ranked of popularly use words. I did do Bing
image searches for all of these words. I used Bing because you guys, or not you guys, but this
company is much more generous than Google is with its images. You can use a lot more before
you have to start paying for it there that API allows you a lot more freedom. Google starts
charging you a fair amount much quicker. Anyway, these were arranged, each of these panels
is essentially a pie chart and these little rays are the image searches of each of those words in
order, so starting with laughter at this point. You can see that here. So this is the good panel
and this is the evil panel. It's darker; it's less saturated. I was actually anticipating, this is like a
fun surprise, I was anticipating it actually being more starkly different. In person, they are really
noticeable, but the other thing I did was these little monitors played, there's 25,000 images and
these monitors play each, all of the 25,000, so it will show the word it's mapped to and it will
just sort of go through it. And of course I had Safe Search turned off and this little screen which
shows the evil panel shows some of the most distasteful, tough imagery that I can imagine. I've
never, you seem. I'm not shy about exploring certain kinds of things, like the Playboy pieces,
other things I've talked about, but we had to actually post a parental warning. What's
interesting is I just wrote software to grab images based on words, like cancer and based on
whatever. I had Safe Search turned off, but I like, I shouldn't say like. I'm really interested in
that kind of agnostic, not agnostic, amoral quality of like search. The algorithm returned, I
mean there's an image of like someone defecating in someone else's mouth while they are
being like found in bondage and like it's just over the top. It's really interesting in a conceptual
way. It's pretty difficult. They go by real fast, but it was really important to me actually to sort
of, that quality that, you know, this -- and then this is obviously like kind of compliance to
expectations. It's like puppies and ice cream and sunshine. So that sort of, that quality of what
search does with our requests is echoed here up to the last piece I'll talk about. This was done
at the same time basically. It's a Roy G Biv color wheel and I noticed that downstairs the artist
who is here did a little bit of stuff with color as well in search. This is a Roy G Biv color wheel in
tertiary colors, so you've got your standard Roy G Biv and then you have the tertiary colors
which are, you know, red, orange et cetera. It kind of conforms to expectation except for this
chunk here is for blue violet and Violet Blue is an adult actress. Changes that little wedge into
just flesh tone, because whenever anybody searches for blue violet, I guess they are always
searching for this actress, not for the color blue violet. So again, you get this -- and I'm really
interested in those accidents and mistakes, or are they mistakes, right? Like I don't know if
they are mistakes, but that semantic sort of confusion between myself and software. If, you
know, I was super excited by that result. To be honest, I think made the piece for me. There's
more work here, but I'm happy to sort of answer some questions generally or I think we are at a
good spot. I appreciate you guys coming. Thank you. [applause].
>>: Do you have a little bit of a video of the touch interaction on the synthesis?
>> Jason Salavon: I don't have it edited. I have it. I have some, there's something old maybe
on here. No. Try one more time. Yeah. I actually thought I would really like to have that ready
for you guys, but I'm pleased with the way it turned out and apparently the census people are
really happy with it, so I think we had fun. That was new to me, that kind of, that project was
new. I had like some experienced programmers on the team and it was a year-long project. It
was a really fun one. Yeah?
>>: On that piece, just looking at it, it looks great. It's great like wall art, but like how much
does it play into your thinking that it's hard to interpret? Like if you told me, you explain to us
what it was. Now even though I know what it is, if I look at that perspective I look at that, I
can't glean much information from that.
>> Jason Salavon: I don't know what this is doing. That's why this thing is essential. I have a lot
of mixed feelings about my software. I have a lot of mixed feelings about how much to reveal.
It's a question I have. In that particular piece for that audience, like a lot of this depends on
who you're communicating with, so it's people who live with the piece, lived in the building
who work on various -- it's 6000 employees at the Census Bureau. It's a big organization. I was
really happy with the aesthetics of that object and I'm also, but I'm more interested in the kinds
of store that yielded that object. So you literally, there are dials where you can literally unfold
and re-fold it. You can go from the, there's a graph mode where you can select individual
counties and then switch from that county into the graph mode. There's all kinds of different
ways I'm explicitly showing how the form was generated. And it was a really important
problem for me to solve in that case. In other cases, I've done pieces where I can tell someone
walked off without -- I didn't talk about. I don't know if this is going to work. The Titanic piece.
I've never had this thing breakdown and of course it would happen here. [laughter].
>>: What's [indiscernible]
>> Jason Salavon: It's a website, but I use this old, it's actually really old browser that the fullscreen works really well, but it's a local website basically. Like a piece like this, which I usually
talk about and haven't yet, it's called the top grossing film of all time one by one. It's a print
that's this big if not a little bit bigger, so a really large photographic print. Each of these little
sort of specs, you can see they are squares, are actually one frame from the film Titanic. Sort of
taking the mean across the entire image to a solid colors so it's the average color for the frame.
>>: [indiscernible].
>> Jason Salavon: Right. No longer the top grossing film, that's true.
>>: [indiscernible]. [laughter].
>> Jason Salavon: This is the ship going down. This is bad times. This is I'm king of the world up
here.
>>: [indiscernible] [laughter].
>> Jason Salavon: That's them like running through the ship with like, there's all this electrical
popping like they are in the bowels of the ship and there are like loose wires and all this sort of
electrical popping and it's literally like some of it is per frame. The film is called the top grossing
film of all time; I mean the piece is called the top grossing film of all time. But for years I've
seen people walk up to it, look at it, walk away and not know what the piece was. I don't know
what to do. It is part of the identity of these things that sometimes there's more back story and
the thing is truly what it purports to be, but how to communicate that, or should I? Maybe, you
know, the identity of this thing is okay as it is. You know, it's kind of an open question. This
piece was in a Whitney exhibition and all kinds of cool stuff happened, but the weirdest part of
it and this is early a big Hollywood production studio wanted to license the software to use on
dailies like they're going to run it on things. It was interesting and flattering and it was the first
realization that this work I was doing had an interest to sort of commerce. It had, there were
people who wanted to try to apply these things. I met this purely as an artistic sort of
exploration and that Hollywood would -- it fell through and it didn't happen but that Hollywood
was we want to do that on our movies, I always thought that was hilarious because does that
mean that they are going to need to add more red here? I always wondered what they would
do with that information. We've got to go back and re-shoot some purple scenes? But it was
kind of a moment where I realized no. The place I'm operating has this strong interest in lots of
fields and now we are, 12 years later, 13 years later and it's just sort of this idea of visualization
of the data as sort of this ubiquitous thing and, you know, my 12-year-old niece knows what
DataViz is and my grandmother knows what DataViz is, right?
>> Michael Cohen: The one thing I didn't mention about Jason is he teaches at the University of
Chicago. Actually he's got tenure there, so I was wondering kind of what you teach to your
students and do your students have a tendency to produce pieces of like [indiscernible] pieces
and how you kind of get around the art is that good or bad?
>> Jason Salavon: I have a dual appointment at the University of Chicago in the computation
Institute which is like a research entity that is partnered with part of Argon Labs. It's high
performance computing oriented and I think of myself as one of the token sort of humanists
there. We really have done some interesting collaborations with other faculty in the kind of
universe of DataViz and other things. And by teaching appointment is in the art department, so
I teach computation for art types of classes, imaging classes that integrate kind of programming
ideas. University of Chicago had no theoretical University and had no maker space of any kind,
so I build out a maker space and I'm teaching some classes and there. I never show my work to
my classes. They find it, and I can tell, but I, sometimes you see stuff that's like oh I know
where you got that idea. But I show a lot of artwork. There's lots of, we are in a really nice
moment for the collision of art and computation. It's finally here. We have bandwidth than we
have power and we have relatively inexpensive machines where a small team or individual can
put together really amazing things. That's really gratifying, so there's lots of stuff to show, but I
am interested in, like I'll teach some sort of basic stuff like Photoshopy stuff, but I'm always
trying to push them toward process, algorithm. We were talking about processing. I love
showing, teaching kids processing. It's a really like low barrier entry into software. There's tons
of interesting examples for them to sort of kick the wheels on. And I advise graduate students
who, since my background I think helps with this. I advise painters and I'm interested in art
kind of at large even if my own practice is really rooted in computation and what I did in sort of
reorganization of information maybe.
>>: Are your students mostly are students or are they computer science students?
>> Jason Salavon: My students are art students. I work with a lot of CS undergrads in my
classes. I find myself teaching these classes that are like literally half physics and CS students
and half our students which is super fun, and I will like curate teams to do a sort of installations.
That's been really gratifying. And, you know, the undergrads there are generally speaking really
good and really up for like challenges enough to sort of stretch themselves in different
directions from both sides of the aisle, I guess. My graduate students are art students, although
there is talk of me advising some sort of PhD students too.
>>: Were your students like from art to programming and from programming to art, how hard
is it to teach them? Like programmers, how do you teach them like color theory, blah, blah and
artists algorithms for loops, what's your…
>> Jason Salavon: Yeah. Those are both hard. My mechanism tends to be through example, so
she'll lots of stuff, like turn them on to things I think are interesting combinations of these
things and stretch their minds sort of visually first. Sort of show them the space of possibilities
and then start to talk about principles and things like that. That especially, both directions that
works for. There are other people who teach sort of more fundamental things like color theory
and stuff like that. I do talk a lot about composition and those sorts of things. Most of my
classes are maker oriented, like you are making stuff. They are studio classes, so we do a lot of
critique which is sort of, you know, everybody making stuff, putting it up and talking about it.
>>: How do you grade them?
>> Jason Salavon: Roughly. [laughter]. I'm not too hard on them. Our grading has always been
a complicated thing. I try to establish some criteria that are sort of standardized, but effort
means a lot. Art is a thing where there's, I believe, something about innate talent that's
involved, so, you know, someone who tries really hard, there's a lot of credit for that in my
mind. And, you know, you see kids are great; I love them, but complaining about an A- is the
most annoying thing in the world. [laughter]. Oh God!
>> Michael Cohen: Maybe one more question.
>> Jason Salavon: Yeah.
>>: Do you so far [indiscernible] come from a science background. Do you see kind of
[indiscernible] for them [indiscernible] so they have more [indiscernible] use it for art by
[indiscernible] specifics [indiscernible] produce it, a different kind of approach?
>> Jason Salavon: Yeah. It is a different approach. In my own work I tend to be a whatever
works kind of guy. I tend to be interested in the phenomenon that you are going to experience
and the black boxes that one puts together to get there, while I am interested in them, I'm
interested, and I talked about this. I'm interested in the nitty-gritty, but I don't privilege it over
getting the job done. I do try to put that across for art making that when a person comes up to
a thing you've made, most of the time they don't give a shit about like all of the details of its
construction, right? That's something you have joy of in your own world, and to me it's the
same with software design, right? Nobody cares what's under the hood, if it works, as a user.
But that doesn't take away from the joy of it. I said something about being interested in the
final product. Actually, I love programming. I love working on problems. I really like disappear
for like 12 hours. Where did the time go? I've been like beating on this problem. That joy is a
personal kind of joy that is about generating these things, but I'm not expecting my audience to
sort of get in there and have that joy with me. That's a thing I do that is somewhat separate
from their experience of it. Anyway, I try to relate those kinds of ideas, and again, the thing
that I found that works the best is show them lots of cool stuff and get their minds thinking oh.
And then they can problem solve their specific thing. What is great about like undergrads, you
know, they never touched Arduino and they are making robots in like 36 hours. That's like a
super joy from working with sort of tech and science oriented kids is they go and take care of all
of that by themselves. I don't have to do much. They, so I'm more about ideas and what it is
that they are going to make and that sort of thing. Then from the art side I have to do a lot
more sort of handholding about, you know, loops and conditionals and, you know, just sort of
basic stuff. But putting them in teams, they help each other a lot too. That's been really
gratifying. I've enjoyed, there's a particular class that I'm really pushing that direction. It's been
my most enjoyable class to teach lately.
>> Michael Cohen: Thanks a lot Jason.
>> Jason Salavon: Thank you guys for coming. Appreciate it. [applause].