Introducing Machine Data Dreams

Earlier this year, I received an Individual Artist Commission grant from the San Francisco Arts Commission for a new project called Machine Data Dreams.

I was notified months ago, but the project was on the back-burner until now — where I’m beginning some initial research and experiments at a residency called Signal Culture. I expect full immersion in the fall.

The project description
Machine Data Dreams will be a large-scale sculptural installation that maps the emerging sentience of machines (laptops, phones, appliances) into physical form. Using the language of machines — software program code  — as linguistic data points, Scott Kildall will write custom algorithms that translate how computers perceive the world into physical representations that humans can experience.

The project’s narrative proposition is that machines are currently prosthetic extensions of ourselves, and in the future, they will transcend into something sentient. Computer chips not only run our laptops and phones, but increasingly our automobiles, our houses, our appliances and more. They are ubiquitous and yet, often silent. The key to understanding their perspective of the world is to envision how machines view the world, in an act of synthetic synesthesia.

Scott will write software code that will perform linguistic analysis on machine syntax from embedded systems — human-programmable machines that range from complex, general purpose devices (laptops and phones) to specific-use machines (refrigerators, elevators, etc) . Scott’s code will generate virtual 3D geometric monumental sculptures. More complex structures will reflect the higher-level machines and simpler structures will be generated from lower-level devices. We are intrigued by the experimental nature of what the form will take — this is something that he will not be able to plan.

kildall_5

Machine Data Dreams will utilize 3D printing and laser-cutting techniques, which are digital fabrication techniques that are changing how sculpture can be created — entirely from software algorithms. Simple and hidden electronics will control LED lights to imbue a sense of consciousness to the artwork. Plastic joints will be connected via aluminum dowels to form an armature of irregular polygons. The exterior panels will be clad by a semi-translucent acrylic, which will be adhered magnetically to the large-sized structures. Various installations can easily be disassembled and reassembled.

The project will build on my experiments with the Polycon Construction Kit by Michael Ang, where I’m doing some source-code collaboration. This will heat up the fall.

PCK-small-mountain-768x1024

At Signal Culture, I have 1 week of residency time. It’s short and sweet. I get to play with devices such as the Wobbulator, originally built by Nam June Paik and video engineer Shuya Abe.

The folks at Signal Culture built their own from the original designs.

What am I doing here, with analog synths and other devices? Well, I’m working with a home-built Arduino data logger that captures raw analog video signals (I will later modify it for audio).

20150730_200511I’ve optimized the code to capture about 3600 signals/second. The idea is to get a raw data feed of what a machine might be “saying”, or the electronic signature of a machine.

20150730_150950

Does it work? Well, I hooked it up to a Commodore Amiga (yes, they have one).

I captured about 30 seconds of video and I ran it through a crude version of my custom 3D data-generation software, which makes models and here is what I got. Whoa…

It is definitely capturing something.

Screen Shot 2015-07-30 at 10.08.49 PM

Its early research. The forms are flat 3D cube-plots. But also very promising.

People I Want To Punch in the Face

“People I Want to Punch in the Face” is a book sold at the Whitney (and apparently on Etsy as well) with blank pages.

In one of them, unbeknownst to the bookstore staff, assorted visitors filled in their choices.

11222053_10153612163059274_906440019349147799_n

11058240_10153612163614274_2887715013415183768_n 11145561_10153612163409274_2681781276863721911_n 11214197_10153612163304274_2279591990549537961_n 11220458_10153612163539274_7186057447222198758_n 11220879_10153612163809274_422588321701773217_n  11223531_10153612163859274_8381130295349143957_n 11224733_10153612163924274_8767296298503521774_n 11702794_10153612163894274_5660821899910988506_n 11796299_10153612163389274_5730743001320813356_n 11800074_10153612163124274_3322783156749186006_n 11800312_10153612163149274_169491647891715725_n 11811389_10153612163489274_7267997940101690339_n 11811500_10153612163334274_2498593643581833620_n 11811505_10153612163654274_978369019232892087_n 11816853_10153612163719274_5747074713365788879_n 11825711_10153612163984274_5919445799299516647_n 11828615_10153612163759274_6926645940978707847_n

Bad Data: SF Evictions and Airbnb

The inevitable conversation about evictions at San Francisco every party…art organizations closing, friends getting evicted…the city is changing. It has become a boring topic, yet it is absolutely, completely 100% real.

For the Bad Data series — 12 data-visualizations depicting socially-polarized, scientifically dubious and morally ambiguous dataset, each etched onto an aluminum honeycomb panel — I am featuring two works: 18 Years of Evictions in San Francisco and 2015 AirBnb Listings for exactly this reason. These two etchings are the centerpieces of the show.

evictions_airbnb

This is the reality of San Francisco, it is changing and the data is ‘bad’ — not in the sense of inaccurate, but rather in the deeper sense of cultural malaise.

By the way, the reception for the “Bad Data” show is this Friday (July 24, 2015) at A Simple Collective, and the show runs through August 1st.

The Anti-Eviction Mapping Project has done a great job of aggregating data on this discouraging topic, hand-cleaning it and producing interactive maps that animate over time. They’re even using the Stamen map tiles, which are the same ones that I used for my Water Works project.

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When I embarked on the Bad Data series, I reached out to the organization and they assisted me with their data sets. My art colleagues may not know this, but I’m an old-time activist in San Francisco. This helped me with getting the datasets, for I know that the story of evictions is not new and certainly not on this scale.

In 2001, I worked in a now-defunct video activist group called Sleeping Giant, which worked on short videos in the era when Final Cut Pro made video-editing affordable and when anyone with a DV camera could make their own videos. We edited our work, sold DVDs and had local screenings, stirring up the activist community and telling stories from the point-of-view of people on the ground. Sure, now we have Twitter and social media, but at the time, this was a huge deal in breaking apart the top-down structures of media dissemination.

Here is No Nos Vamos a hastily-edited video about evictions in San Francisco. Yes, this was 14 years ago.

I’ve since moved away from video documentary work and towards making artwork: sculpture, performance, video and more. The video-activist work and documentary video in general felt overly confining as a creative tool.

My current artistic focus is to transform datasets using custom software code into physical objects. I’ve been working with the amazing fabrication machines at Autodesk’s Pier 9 facility to make work that was not previously possible.

Ths dataset (also provided through the SF Rent Board) includes all the no-fault evictions in San Francisco, I got my computer geek on…well, I do try to use my programming powers for non-profit work and artwork.

I mapped the data into vector shapes using the C++ open source toolkit, called OpenFrameworks and wrote code which transformed the ~9300 data points into plotable shapes, which I could open in Illustrator. I did some work tweaking the strokes and styles.

sf_evictions_20x20

This is what the etching looks like from above, once I ran int through the water jet. There were a lot of settings and tests to get to this point, but the final results were beautiful.

waterjet-overhead

The material is a 3/4″ honeycomb aluminum. I tuned the high-pressure from the water-jet to pierce through the top layer, but not the bottom layer. However, the water has to go somewhere. The collisions against the honeycomb produce unpredictable results.

…just like the evictions themselves. We don’t know the full effect of displacement, but can only guess as the city is rapidly becoming less diverse. The result is below, a 20″ x 20″ etching.

Bad Data: 18 Years of San Francisco Evictions

baddata_sfevictions

The Airbnb debate is a little less clear-cut. Yes, I do use Airbnb. It is incredibly convenient. I save money while traveling and also see neighborhoods I’d otherwise miss. However, the organization and its effect on city economies is a contentious one.

For example, there is the hotel tax in San Francisco, which after 3 years, they finally consented to paying — 14% to the city of San Francisco. Note: this is after they had a successful business.

There also seems to be a long-term effect on rent. Folks, and I’ve met several who do this, are renting out places as tenants on Airbnb. Some don’t actually live in their apartments any longer. The effect is to take a unit off the rental market and mark it as a vacation rental. Some argue that this also skirts the law rent-control in the first place, which was designed as a compromise solution between landlords and tenants.

There are potential zoning issues, as well…a myriad of issues around Airbnb.

BAD DATA: 2015 AIRBNB LISTINGS, etching file

airbnb_sf

In any case, the location of the Airbnb rentals (self-reported, not a complete list) certainly fit the premise of the Bad Data series. It’s an amazing dataset. Thanks to darkanddifficult.com for this data source.

BAD DATA: 2015 Airbnb Listings

baddata_airbnb

Selling Bad Data

The reception for my solo show “Bad Data”, featuring the Bad Data series is this Friday (July 24, 2015) at A Simple Collective.

Date: July 24th, 2015
Time: 7-9pm
Where: ASC Projects, 2830 20th Street (btw Bryant and York), Suite 105, San Francisco

The question I had, when pricing these works was how do you sell Bad Data? The material costs were relatively low. The labor time was high. And the data sets were (mostly) public.

We came up with this price list, subject to change.

///  Water-jet etched aluminum honeycomb:

baddata_sfevictions
18 Years of San Francisco Evictions, 2015 | 20 x 20 inches | $1,200
Data source: The Anti-Eviction Mapping Project and the SF Rent Board


baddata_airbnb
2015 AirBnB Listings in San Francisco, 2015 | 20 x 20 inches | $1,200
Data source: darkanddifficult.com


baddata_hauntedlocations
Worldwide Haunted Locations, 2015 | 24 x 12 inches | $650
Data source: Wikipedia


baddata_ufosightings

Worldwide UFO Sightings, 2015 | 24 x 12 inches | $650
Data source: National UFO Reporting Center (NUFORC)


baddata_missouriabortionalternatives

Missouri Abortion Alternatives, 2015 | 12 x 12 inches
Data source: data.gov (U.S. Government) | $150


baddata_socalstarbucks

Southern California Starbucks, 2015 | 12 x 8 inches | $80
Data source: https://github.com/ali-ce


baddata_usprisons

U.S. Prisons, 2015 | 18 x 10 inches | $475
Data source: Prison Policy Initiative prisonpolicy.org (via Josh Begley’s GitHub page)


///  Water-jet etched aluminum honeycomb with anodization:

baddata_denvermarijuana

Albuquerque Meth Labs, 2015 | 18 x 12 inches | $475
Data source: http://www.metromapper.org


baddata_usmassshootings

U.S. Mass Shootings (1982-2012), 2015 | 18 x 10 inches | $475
Data source: Mother Jones


baddata_blacklistedips-banner

Blacklisted IPs, 2015 | 20 x 8 ½  inches | $360
Data source: Suricata SSL Blacklist


baddata_databreaches

Internet Data Breaches, 2015 | 20 x 8 ½ inches | $360
Data source: http://www.informationisbeautiful.net

Bad Data, Internet Breaches, Blacklisted IPs

In 1989, I read Neuromancer for the first time. The thing that fascinated me the most was not the concept of “cyberspace” that Gibson introduced. Rather it was the physical description of virtual data. The oft-quoted line is:

“The matrix has its roots in primitive arcade games. … Cyberspace. A consensual hallucination experienced daily by billions of legitimate operators, in every nation, by children being taught mathematical concepts. … A graphic representation of data abstracted from banks of every computer in the human system. Unthinkable complexity. Lines of light ranged in the nonspace of the mind, clusters and constellations of data. Like city lights, receding.”

What was this graphic representation of data that struck me at first and has stuck with be ever since. I could only imagine what this could be. This concept of physicalizing virtual data later led to my Data Crystals project. Thank you, Mr. Gibson.

dc_sfart_v1

In Neuromancer, the protagonist Case is a freelance “hacker”. The book was published well-before Anonymous, back in the days when KILOBAUD was the equivalent of Spectre for the BBS world.

At the time, I thought that there would be no way that corporations would put their data in a central place that anyone with a computer and a dial-up connection (and, later T1, DSL, etc) could access. This would be incredibly stupid.

And then, the Internet happened, albeit more slowly than people remember. Now hacking and data breaches are commonplace.

My “Bad Data” series — waterjet etchings of ‘bad’ datasets onto aluminum honeycomb panels — capture two aspects of internet hacking: Internet data breaches and Blacklisted IPs.

In these examples, ‘bad’ has a two-layered meaning. The abrogations of accepted treatises of Internet behavior is widely considered a legal, though always not a moral crime. The data is also ‘bad’ in the sense that it is incomplete. Data breaches are usually not advertised by the entities that get breached. That would be poor publicity.

For the Bad Data series, I worked with no necessarily the data wanted, but rather the data that I could get. From Information Is Beautiful, I found this dataset of Internet data breaches.

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What did I discover? …that Washington DC is the leader of breached information. I suspect it’s mostly because the U.S. government is the biggest target rather than lax government security. The runner-up is New York City, the center of American finance. Other notable cities are San Francisco, Tehran and Seoul. San Francisco makes sense — the city is home to many internet companies. And Tehran, which is the target of Western internet attacks, government or otherwise. But Seoul? They claim to be targeted by North Korea. However, as we have found out, with the Sony Pictures Entertainment Hack, North Korea is an easy scapegoat.

BAD DATA: INTERNET DATA BREACHES (BELOW)

baddata_databreaches

Conversely, there are many lists of banned IPs. The one I worked with is the Suricata SSL Blacklist. This may not be the best source, as there are thousands of IP Blacklists, but it is one that is publicly available and reasonably complete. As I’ve learned, you have to work with the data you can get, not necessarily the data you want.

I ran these two etched panels both through an anodization process, which further created a filmy residue on the surface. I’m especially pleased with how the Banned IPs panel came out.

Bad Data: BLACKLISTED IPs (below)

baddata_blacklistedips