A couple of days ago,  I came across the website generated.photos (via the Verge) a new service that offers 100.000 computer generated portrait images and positions them as an alternative to traditional stock photos. The Verge article highlights the fact that the pictures can be used “royalty free” and the generated.photos website claims that “Copyrights … will be a thing of the past”. This made me postulate on twitter that we might very well be witnessing the emergence of an “auto-generative public domain”.

It has since become clear that the creators of generated.photos do not intended to contribute the output of their algorithms (or for that matter the algorithms themselves) to the public domain: By now the website has been updated to note that the images are available for non-commercial use only. A new terms and conditions page states that “Legal usage rights for content produced by artificial intelligence is a new, largely unknown domain” only to go on to list a number of restrictions on the use of the “materials and software” made available on generated.photos.

As noted in the terms of conditions the copyright status of images (and other types of artworks) that are autonomously created by AI-powered software is largely unsettled. As Andres Guadamuz notes in his excellent overview post on the topic, there are generally two schools when it comes to the question if computer generated artworks are (or should be) protected by copyright. One school argues that copyright protection only attaches to works that have been created by humans and as a result computer generated artworks can by definition not be copyrighted. The other school points out that such works are not created without any human intervention (someone needs to start up the software and set basic parameters) and that whoever initiated the generation of these works should be considered the creator and receive at least a minimum level of (copyright) protection as a reward for their investment.

In the case of generated.photos it is evident that the people behind the project have made a considerable investment into the project. The website states that they have shot more than 29.000 photos of 69 models that have subsequently been used as a training set for the software. Judging by notes on their website, the 100.000 images made available on the website have been created using the open source generative adversarial network StyleGAN that is freely available via GitHub. It remains to seen if creating photos (which are copyright protected) that are then used to train a out of the box GAN does indeed mean that the output of the network is (a) protected by copyright and (b) that the copyright belongs to the entity that trained the GAN.

While it seems to be at least possible that the creators of generated.photos do have a legitimate copyright claim in their output, that does not necessarily invalidate the idea that we are witnessing the emergence of an auto-generative public domain, i.e circumstances in which computer algorithms produce a (possibly endless) stream of artworks, that are indistinguishable from human created works and that are free from copyright and can be used by anyone for any purpose.

In terms of quality, the images provided by generated.photos are still far from indistinguishable from human made stock photos, but it is clear that it is only a matter of time before the technology gets good enough to produce high enough quality outputs at scale. Projects like the next Rembrandt illustrate this development is not limited to stock photography but will likely happen across the full width of human creative expression.

Such a development would dramatically upend a large number of creative professions. It seems like it will only be a matter of time before stock photography and other forms of creative work where the primary draw is not the specific style of a particular creator will be replaced by AI-generated output that will cost almost nothing to create. Once AI powered systems will be able to deliver high quality creative output at zero marginal cost the question if these outputs are protected by copyright or not will be largely meaningless (a single system releasing its output into the public domain will render any attempts to enforce copyright futile).

From the perspective of those making a living by creating stock photos, background music and other forms of creative work that is about to be eaten up by AI, the emergence of this “auto-generative public domain” must feel dystopian. Under these conditions the primary question that we must ask ourselves is not how we can fit works created by computer algorithms within the framework of copyright law. Instead we should ask ourselves how we can create the conditions for human creators to leverage these technologies as tools for their own creative expression. Instead of mourning a future in which humans are no longer employed to shoot endless variations of the same stock photos, we should look out for entirely new forms of creative expression enabled by these tools.

While running i listend to a On The Media interview with the autor of the Wired piece on content moderation that was making the rounds this week. After a while the interview addresses the relatively obvious question of why content moderation is still a task that can only be carried out by humans:

Brooke Gladstone: I think that one of the things that struck me is that this work demands human beings clued in to American mores and laws. This has to be done by brute force of eyes and clicking fingers. Is there no alternative to human moderation?

Adam Chen: Well everyone i talked to said that there was no way a robot could do all of this. They can come up with programmes and algorithms that will make it more effective and more streamlined but there is always going to be somebody who has to looks at it. And also the kinds of moderation that si going on is becoming more nuanced and complicated. And so i think you always gonna need people and probably more and more people as time goes on.

What struck me when listening to this is exchange that this is just one instance of a much broader problem, namely the current inability to encode moral judgement in algorithms. Once we have ‘solved’ this issue those poor schmucks who have do do content moderation for the rest of us will be out of job (which sounds as a good thing) but that will also be the moment where have to start dealing with killer drones/robots that do not require human interventions before firing their weapons.

Yesterday we saw 1+8 at the opulent Galata branch of SALT. 1+8 is a dynamic eight-screen video installation about Turkey and her eight neighbours based on the feature film of the same name directed by Cynthia Madansky and Angelika Brudniak. I usually do not have much patience for video installations but 1+8 managed to capture my attention for quite some time. If you are to believe the catalogue text this thanks to an the brilliance of a ‘custom made algorithmic computer program’ powering the display:

“The installation invites the audience to become immersed in the contemplation of life at the eight borders of Turkey. The multi-screen projection lends itself to experience simultaneity and inter-connection on a physical level. The choreography of video’s on the eight screens, is created dynamically with the help of a custom made algorithmic computer program allowing for a unique viewer experience, whereby the projections will never appear the same way twice.”

Not sure in how far the algorithm contributed to my enjoyment here. Being a bit obsessed about maps i was much more delighted by the way the room (a large rectangle) was used as a map of the territory, with the videos projected on those parts of the wall that correspond with the actual borders between Turkey and its eight¹ neighbours (this of course only works with a country like turkey which is an even bigger rectangle):

Also, it appears that the border regions between Turkey and its six Asian neighbours are really fascinating/beautifull which makes me want to travel there at some point in the future

If you ask me one of the more fascinating things going on out there right now is high-frequency trading. High-frequency trading (HFT) occurs when traders program computers to buy and sell stocks (or other financial products) in quick succession under certain, pre-defined circumstances. (a good starting point to learn more about HFT is this planet money episode or this ai500 article by Joe Flood).

Apparently High Frequency trading enables successful trading firms to skim of enormous surplus off these transactions (up to 1 million USD per day according to the planet money episode mentioned above). Not surprisingly this behavior can also act as a destabilizing factor wrecking havoc on stock markets. It has been one of the contributing factor’s to the ‘flash crash‘ which saw the Dow-Jones index plunge nearly 1,000 points in seconds on the 6th of may 2010.

If you believe wikipedia (which of course you should not) High Frequency trading is currently responsible for 70% of the equity trading volume in the US. Needless to say the practice is generating a fair share of controversy among economists.

At the core of this controversy are the merits of HFT: does is make macro-economic sense (because it ensures the liquidity of markets and limits market volatility) or is it detrimental to the economy at large (because it extracts value from markets based on no other fact than that prices tend to move)?

While this debate is going on it appears that there are even stranger things occurring in the field of high frequency trading: in August the Atlantic reported on research undertaken by a market data firm called Nanex that unearthed trading patterns that do not seem to make sense even by the high obfuscation standards of HFT. The article in the Atlantic claims that these strange patterns are the result of ‘mysterious and possibly nefarious trading algorithms’ whose ways and reasons of operation are known to no-one:

Unknown entities for unknown reasons are sending thousands of orders a second through the electronic stock exchanges with no intent to actually trade. Often, the buy or sell prices that they are offering are so far from the market price that there’s no way they’d ever be part of a trade. The bots sketch out odd patterns with their orders, leaving patterns in the data that are largely invisible to market participants.

When you visualize this you get something like this (graphs by Nanex):

According to the Atlantic it is unclear what exactly causes these patterns to emerge. The Nanex researchers have come to the conclusion that these algorithms are most likely an attempt by trading firms to introduce noise into the marketplace in order to realize a competitive advantage:

Other firms have to deal with that noise, but the originating entity can easily filter it out because they know what they did. Perhaps that gives them an advantage of some milliseconds. In the highly competitive and fast HFT world, where even one’s physical proximity to a stock exchange matters, market players could be looking for any advantage.

On the other hand there are much more poetic explanations for the emergence of these patterns, that abandon the idea that these patters serve a purpose all-together:

On the quantitative trading forum, Nuclear Phynance, the consensus on the patterns seemed to be that they simply just emerged. They were the result of “a dynamical system that can enter oscillatory/unstable modes of behaviour,” as one member put it. If so, what you see here really is just the afterscent of robot traders gliding through the green-on-black darkness of the financial system on their way from one real trade to another.

Whatever they are, these patterns are also outright beautiful. The above visualizations remind me on the work of german artist Jorinde Voigt, who’s stunning drawings (pdf) often rely on algorithms as a source:

p.s:Sara says that these stealth trading bots remind her of the tiger in Jonathan Lethem’sChronic City instead. p.p.s: Also just finished reading ‘the Fires‘ by the aforementioned Joe Flood. brilliant book, highly reccomended.