Category Archives: science

You Don't Know Jack

Love Jack? Turns out to be an icon at the university where I work: University of Texas at Dallas. To be perfectly honest, none of us really knew Jack before the start of the Spring 2016 Creative Automata class, however, because of my students' admirable diversity, we can really know more about Jack. This is the biggest project to date, and the Jack adventure began with a challenge to the students to explore the sculpture (which is located in the courtyard of the ATEC building) from different perspectives. What perspectives could be better than those that are natural to the students' interests and backgrounds?  The class contains computer scientists, artists, and designers--often with students crossing over among areas and interests. A smartphone app accompanies the main Jack web page, so that when one is near the Jack, the perspectives can be browsed. Interested in the artist's history, how Jack relates to computer science and mathematics, modeling & simulation,  graphic design, digital fabrication, the connection of art to science? It's all there. A beacon is next to the sculpture to facilitate object-based learning discovery across STEAM (Science, Technology, Engineering, Art, and Mathematics). You can also start with STEAM and browse based on interest.

Why the STEAM Argument is One-Sided


Full steam ahead. Or should I say STEAM ahead? STEM stands for Science, Technology, Engineering, and Mathematics and has been a driving force initiated by the National Science Foundation to focus education policy within technical areas and their associated disciplines. More recently, the letter "A" has been added to create a new movement called STEAM. The "A" stands for the arts, and according to a leading site devoted to STEAM, STEM + Art = STEAM. Since I spend much of my time thinking about the interconnections between STEM and the Arts, I welcome the STEAM movement. And yet, I have deep concerns about the movement's three published policy goals stated on the STEAM site:  (1) transform research policy to place Art + Design at the center of STEM; (2)  encourage integration of Art + Design in K–20 education; and (3) influence employers to hire artists and designers to drive innovation.  These are worthwhile goals, but notice how all three goals seem to be about getting STEM-oriented folks to hire artists and designers, and placing art & design at the middle of STEM? Let's flip this. What about having STEM at the center of Art and Design? I am not suggesting doing away with the three STEAM goals, but I am recommending some sort of balance by extending or broadening these goals; the current ones are lopsided. I strongly advocate new ways of starting with design and the arts, and then surfacing STEM concepts from within art and design. For the STEM subset of computing, this advocacy resulted in the aesthetic computing movement. Recently, this approach has taken root in learning systems thinking in the art museum.  I am not the first to suggest this if we consider the larger literature base of  blending STEM with the Arts. Take Martin Kemp's book The Science of Art where he explores mathematics and optics via art. Also, the MIT Press Leonardo journals edited by Roger Malina has extensive historical coverage of intersections of STEM and the arts.  Leonardo was founded in 1968, and so its publications contain a treasure trove of knowledge, suggesting new ways to get to the heart of STEAM.  To advocates of STEAM, my suggestion is to rethink of STEAM as two-way traffic: two steam locomotives, two tracks, perhaps with some switches here and there.

The Beauty of Small Data


I started playing chess at a young age when my uncle in England sent me a tiny plastic chess set for Christmas. What were these strange pieces? How did they move? Before long, I learned that they could make interesting patterns on the checkered board. I followed Fischer vs. Spassky with an almost religious fervor. Over time, I became interested in computer science and followed those who made chess machines and software. And then came the inevitable day when the machine beat the reigning world champion (Kasparov).  What were we to do now? I guess there goes chess out the window. But no. Humans continued to play chess, and the game is as popular, or more, than ever. There a lesson here. Just because we teach machines to excel at artificial intelligence and at machine learning doesn't mean we stop our quest for life-long learning and enjoyment. Big data is hot. The machine can run through an array of sophisticated algorithms so that, for instance, your search engine experience is more meaningful. I am grateful for this capability and the research that goes into it. Think of the massively complex data networks and automated inferences and patterns generated from them. And yet, I find myself interested in teaching students to draw small networks for things that they see around them. By doing this, students learn something about semantic networks and concept maps (ideas developed by artificial intelligence researchers in the 1970s). The learning that occurs is personal and in this case, does not require the big. It requires an attention to detail and a never-ending fascination with discovery.

Engineering the Humanities


When I landed my first academic job at the University of Florida in the mid-80s, I began a slow and steady life journey of knowledge enrichment, which included making friends and colleagues in different schools. One of the things that confused me then, and continues to be a puzzle now, is the schism existing between and among areas such as arts, humanities, science, and engineering. Here is one example of a schism, or perhaps more of a deep canyon.  Recall that the humanities are traditionally very old subjects--been around a while and dominated by reading and writing: Scholarly production. Then, consider the arts, and by "arts," I am referring to the arts of the senses such as fine art, ceramics, sculpture, and performing arts such as theatre and dance. Tasks that involve making live in the art building. People are making things--paintings, kinetic sculptures, cinema. Tasks that involve writing are somewhere else on campus--in the humanities building. There is a deep schizophrenia where the people who "make" and the people who "write" don't talk much with each other. As an engineer, I find this peculiar because in engineering, not only are writing and making in the same place, they are also in the same person. All engineers are expected to form carefully worded arguments about what they contribute to knowledge through making; engineering has a high degree of scholarship as do most areas within the university. All of this causes me to wonder whether what is going on in "digital humanities" is actually a leaking of engineering culture into the humanities. Is that a bad thing? I don't think so, and let's not muddy the waters in the digital humanities with misleading phrases like "using a tool"  or "using technology." These have nothing to do with what is occurring at a fundamental, philosophical level within the humanities. At the core, the transitions are about a social and cultural osmosis from science and engineering. Similarly, there are big shifts--rooted in the arts and humanities--occurring in science and engineering, but that is the subject of another post.

It's About Time


A long time ago, I told a friend that I was starting to move more deeply into the field of modeling and simulation. The friend said to me "It's about time." How true. For no particular reason other than it being January 1st, I thought it appropriate to celebrate the 555 timer integrated circuit (IC), which was designed in 1971 by Hans Camenzind. This is one heavily-used IC, and it can be purchased well under one US dollar depending on the source. The above picture is called a block diagram -- which is a high level design description of how the IC functions. If you looked inside, you'd find mostly transistors with resistors and a couple of diodes. Think of the 555 as something that can create a well-timed oscillating square wave, or just a "one shot" pulse of a given width. An egg timer, but more precise. Having just sung the praises of this IC, we also need to put this technology into context with regard to time management. The most accurate time is kept by atomic clocks, such as those employing cesium. In the semiconductor world, there is also a tug of war, sort of, between MEMS-based oscillators (oscillators built into the silicon) and quartz (which you may have seen on an Arduino or other similar micro controller). All of these technologies are "about time." With the Internet of Things (IoT), computers built around micro controller chips are getting much smaller, more powerful, and are cheaper (although not yet at the < $1 level). For example, you can make your own bare bones Arduino for about $4. You can program a 555's behavior in software rather than through voltage dividers and a capacitor. What will 2015 bring us? There is no time like the present.

We Are All Technologists


I was struck by text that I recently saw when browsing online information about art-science collaborations and upcoming conferences. There was a phrase in one of them promoting connecting "artists with technologists." What the heck is a technologist? Everyone is a technologist. A "technologist" is someone who uses (modern, recent) technology. One might think that a computer scientist or electrical engineer is a technologist, but think again. People in these fields have their own research and agendas; they do not think of themselves as technology gurus out to serve the public at large.  They use technology like everyone else. I have to backtrack a little bit because it so happens that these fields just so happen to produce the most sophisticated technologies (as end products) around. But to a computer scientist, a digital artist might be a "media technologist." The message here is: let's penetrate the broad term of "technology" and get to what is really important to individual practitioners of art, computer science, and engineering. Technology, and the "digital", are simply tools for all of us to do that which drives our passions.

Gender, Computing, and Modeling


Computer science and engineering as a field doesn't have that great of a track record when it comes to gender balance. While I was Director of Digital Arts & Sciences (DAS) at the University of Florida in 2012, I published a piece in Leonardo demonstrating that a core computer science degree can indeed achieve a better balance. The DAS program encompasses an undergraduate (BS) and graduate (MS) degree in computer science with a strong shell of human-centered computing (HCC) surrounding the CS/Math/Science core. The paper represented a 10-year comprehensive summary of what worked, and what didn't, along with statistics. There are others around the country that have tried similar programs involving media and the arts. At the University of Texas at Dallas, we have computer scientists, engineers, designers, and artists working in the same building (Arts and Technology). The gender situation is complex and it isn't clear what works and what doesn't work in every situation. However, there appears to be hope on the horizon in the form of programs that have a strong social/human-centered approach to computing.

Beyond Skin Deep


What is "art science" anyway? An artistic approach to doing, or representing, science? Let's say that the science is biology or astronomy. An artistic approach might be to create new media, or highly creative, representations of dividing cells or nebula. But I'd like to go beyond the surface, beyond being "skin deep." Most science is formalized in mathematical structure. Even formerly descriptive sciences such as biology are increasingly mathematical (e.g., systems biology, bioengineering). Can the mathematics, or the computing behind these formal structures, be constructed and sensed in an artistic way while preserving the core internal mathematical relationships? Can the abstract ideas of accumulation, difference, or iteration be felt, be heard, be seen? In an artistic way--with multiple representations, sensing the mental abstraction in personal ways? A bunch of us got together in 2002 in the beautiful hills of southwestern Germany with this in mind and created a one page Aesthetic Computing manifesto. [Credit for image: Metal Skin by Rómulo Royo, 2008].

The Sands of Calculus

LargeCircleFilling 2

Physics sandbox programs such as PowderToy create an entertaining environment for playing with mechanics. Sometimes, the physics is a bit surreal, as with MineCraft, but that is fine as long as the rules are uniform, repeatable, and easy to understand. I worked on a design with Scott Easum here in our lab, and he produced a nice sand integrator inside of Powdertoy using a digital counter thats someone else had developed within the Powdertoy community. The learning theory is simple: if a student likes PowderToy, then deliver content such as calculus to that student through PowderToy. The goal of this machine is to measure the area of the circle. Note the digital counter with some very small multi-colored pixels beneath it. These pixels form a structure that represents a digital circuit required to make the counter work. The count begins once the sand starts pouring into the circle. The circle's area can then be measured mechanically using a feedback mechanism so that when the container is full, the overflow sand triggers the digital display to stop counting. The final count is read off to yield the area (an adjustment coefficient is required to obtain the area in common metric units). The operating principle is similar to the hourglass. Unlike the hourglass, though, we can quickly create any geometry we like in PowderToy and use our sand calculus machine to determine the area of an arbitrary shape.

Inter-Species Dynamics


The Lotka-Volterra model representation challenge was discussed earlier as a goal for our lab in preparation for Engineering Week, culminating in a set of demonstrations to be given on February 22, 2014. The image shown is a partial screen shot of a simulation created by Karen Doore, a PhD student in Computer Science, also working in the Creative Automata Lab. The time-based dynamics of predator-prey are seen on the right hand side and may look familiar to most modelers of ecological systems where predators and prey interact, causing the population levels to oscillate. The diagram on the left differs from the representational norm--it is an interactive Javascript sketch of an analog water computer. The water computer stems from an underlying modeling language formalism called System Dynamics. Water levels depict the predator and prey populations rising and falling. Input and output valve settings are a function of population levels sensed with water floats. The equations are also represented in a way that the coefficients change inside the equation text, but not shown in this figure due to lack of space. Here are the implemented equations:

\frac{dP}{dt} = -Pm + bHP ; \frac{dH}{dt} = Hr - aHP

Beyond Tool



Hammers are pretty useful objects around the house. This is a photograph of a claw hammer - it can be used to bang nails in things like sheets of wood and plastic, and then remove the nails later. A hammer is a tool. But the hammer pushes back because by using it, I now have to think about what certain materials are made of and what it means to layer objects on top of one another. Computers, and the mathematics that drives them, are like hammers--you cannot use a computer without being fundamentally changed. You think differently when you interact with computers and add numbers together when paying the bill at a restaurant. And since almost everything has a computer in it these days, that means that your philosophy, well-being, and way of knowing the world are all rapidly evolving. It doesn't seem like that should be so. Why can't we just use something that interfaces with a computer and treat the computer tool as, essentially, invisible? Because using a tool is a two-way street. Now that I know my hammer is talking back to me, I am a little worried.

Organum Hydraulicum


Athanasius Kircher was a 17th century German jesuit scholar who produced many publications on machinery. One of them, Musurgia Universalis, was written in 1650 and described ways of creating automatic music. The machine shown above, a water organ, is from Book 9 of that work. Water and air are introduced at the right side into a vessel termed a camera aeolis. The rate of water flow introduces a displacement of air which exits into the vertical pipes comprising the musical organ. The control of which notes are produced, and when, is achieved through barrel rotation.  The water not only displaces air for the organ, but also drives the barrel. The barrel has protrusions that interact with the keys as the levers interact with the protrusions. There is a separate mechanism shown in the upper left of the illustration.