Project by Seth Price
Published June 2015

Written in Ruby 2.2.2 using Sinatra 1.4.6
Hosted on an Amazon EC2 instance running Ubuntu 14.04
Web server: Apache 2 with Phusion Passenger
MySQL database for user comments and auction data
View templates written in ERB
Styles written in SASS

WRONG SEEING, ODD THINKING, STRANGE ACTION
Organic Software: An Interview with Seth Price

Thanks to MS and the LS crew, Synthetic Piracy LLC, Galidium Synthetic Futures Posse, Seasteading GmbH, Nutwerk Foolzy



Original About Page:

ORGANIC SOFTWARE


1. What is the site?
A demonstration of a proprietary algorithmic perception tool.

2. Who are these people?
Art investors/collectors.

3. Why art collectors?
The art world is not important; the tool may address any data set, but art investors are a good demo of the tool because art investor data intersections [finance/culture/power/media presence/taste] are an ideal pool to demo the algorithmic perception tool. This is because art market data pools are both visible and invisible:

A. VISIBLE
* The data pool “art investors” = a good set size to see/understand [not too big, not too small];
* The data pool “art investors” = a good social footprint for data scrapes:
     (presence at parties/social events = image record;
     wealth/social prominence in career = public data trail;
     public obsession with art market = media footprint)
* Art market/auctions = Western, so the art investor from a country w/o data transparency goes West, which gives public records access. For example Russian/Chinese investors with New York apartments means NYC real estate records, etc)

B. INVISIBLE
* Invisibility of art investment (no gov. regulation, contracts, public auction records, etc) = ideal to show the algorithmic perception tool’s power.
* Obscurity of art investment worth = media/public obsession (The West is obsessed with finance/culture/art/power/taste/digital: everything that is Invisible but The Spirit)

4. How does this algorithmic perception tool work?
Profiling:
Group data-aggregation/correlation (bulk data scrape)
Simple AI; open source analytics tools with machine learning
Example: Which portrait to use for a record? The algorithm correlates demographic data across multiple points: address/GPS metadata, social media trail, keyword match [refer to social role/occupation], host site, proximate images, posting date, caption analysis, etc

5. Where is all data sourced?
The Internet.

6. Why not show investor addresses?
This is not necessary for now.

7. Is this to make money?
At this point in time no.

8. Why are you doing this?
To be a demo of the algorithmic perception tool.

9. What is next?
Further development & application of other data sets.

10. Who are you?
Tool developers.

11. Why anonymous?
Focus should go to the algorithms for now. Anonymous work is difficult for the West (except trolling, flames, pranks, etc.) but in the old days coders were not big stars, for example all the first wave videogame developers, Xerox PARC, Wozniak, etc.
Silicon Valley/startup culture has been the big culture in tech for a long time, and is now based on monetizing and fame. Yes, Western tech is focused on a money/fame/IPO system now, but the next wave of coding will be anonymous.

Contact: