Artist Writing


Over the past year or so I have been reading more writings by artists. This includes correspondences, journals, and art reviews of other artists/artworks.

For example: Philip Guston, Adrian Piper, Van Gogh, Carroll Dunham. Why have I been doing this? Sometimes I read journals, and this is the pleasure of biography. This is the sense of understanding the trials and tribulations of an artists life and how an artists deals with personal struggling. However, more than that, I am interested in how artists are reflecting on their personal art practice and other art works (what inspires them). I have a voracious appetite for this, Why?

I have no idea.

That is why I am writing this blog post.

I made a number of false starts in my analysis. I started writing about the changing nature of art, the artist, the interdisciplinary/multidisciplinary nature of art today, art and commerce, art and propaganda (advertisement), aesthetics, craft…. naw.

Then I started thinking about creation in general:

Why create anything? What do people find interesting in other people’s creations? What motivates people to create in the first place?

But I am not interested in all creative function. A business person can be creative, and this is different than the creative activity of a painter. I am more interested these days in the creative activity of the painter. How to keep working in a medium that seems almost exhausted? What is the impulse? Because there is something that draws me to this kind of work as well, but I do not know what it is.

To create means to create something new. This is not some sort of capitalist fetsh. How to create something when it seems that everything has already been created?  How to create something with the burden of history and information?

To that end, if anyone has any good recommendations on artists writing about their work and art that they like… please let me know.


AI & Art Met

AI and Art

art, machine learning

I am reflecting on the AI and Art event put on by the met. Most of the people there were MSFT, Google, MIT, and Cornell. From a cynical point of view, there is a great interest in ML/MI (Machine Learning/ Machine Intelligence) from the industrial-educational complex because it will eventually drive more sales of more powerful computers and software, and because it will increase the need for more education.

From a less cynical perspective, here are my reflections. But first a recap. The Metropolitan Museum of Art is in the process of putting its images (and eventually objects via 3d renderings) on line via wikimedia and wikidata through its open access initiative.  The next question then is how to use this data – ie justify the cost of putting all this stuff online. What is the OKR/KPM/the METRICS? Which is why we enlist google, hackathons, et al.

Now, let me reflect!

Getting it wrong

Two of the panelists: Eva Kozanecka and Serge Belongie, mentioned that they entered the field because they were concerned that the conclusions of ML/MI were incorrect. In particular, as a curator, Eva saw historical connections deduced by ML/MI that were not accurate. This is a powerful driver. The fears with ML I experience bias (ML/MI not recognizing faces with darker pigmentation), or and delusion such as deep fakes (imitating a real person and then putting them in a false situation that appears real).

So, question 1, how does opening up ML/MI to artists or to the public at large mitigate the fear of getting it wrong? Is it merely an example of demystifying the tools. If that is the case, is this the most effective way measure?

Computational Space

The artist Matthew Ritchie gave, what I found to be, the most compelling reason for wanting to work in ML/MI. It allows “computational space to become legible”. There is something to notice here. We are talking about computational space, not digital space or information space. If we imagine the pictorial plane perhaps allows the unconscious to become legible, and the writing plane to allow time/history to become legible, and video/film/production, or interface design  in general that allows the digital space to become legible. Digital is what can be endlessly recontextualized, and infact must be contextualized (ie produced) in order to become meaningful.  The question Ritchie asks (or answers) is what allows the computational space to be legible? What is the computational space. By rendering the relationship between different pieces of data Ritchie is rendering this legible. But, machine Learning is one type of computation.

Ritchie also introduced me to the word Semasiographic: communication by signs. And one of his projects was an ML analysis of diagrams to look for underlying or perhaps the ur-language of graphical communication.

The computational space is made of up many spaces and typologies in a concrete way, and I recommend (as I have before on this blog) reading Quantum Computing Since Democritus by Scott Aaronson to learn what this means. Is ML/MI the only way to make this legible. What does making this legible entail? What does computational space enable that other forms of thought and representation do not?

Tools Vs Work and Transparency

Eva made the comment that the artist Ana Ridler considers different machine learning algorithms as different lenses. And her machine learning project at google is intended to explore this. This is fascinating. But I wonder in what sense are we fetishizing the tools over the work. Like how tube paint allowed impressionists to go paint in the country side. I suspect this question is irrelevant, and it is made irrelevant by the age and modes of expression in the contemporary world. That one of the things the technical image did (Flusser), was remove the distinction between tool and object, and that perhaps the final erasure is between tool, object, observer and creator. This again is another topic worth further exploration.

One participant made a fascinating comment: these works do not make any clearer what ML is actually doing. She didd not have an immediate experience of the ML/MI. And this is absolutely true. In some respects, one of the goals of The Met and open access is pedagogical. And perhaps we should not distinguish between pedagogy and art, or communication and art (propaganda and art).  But it was only until I became a filmmaker that I became aware of the mechanics of different film lenses, what they were doing in a film and why they were being used to communicate something or elicit certain responses. So, I wonder if it is impossible to reveal this information without engaging the observer in the creation process. This also refers to a comment about how sometimes it becomes obvious which Gan is used. As people become more used to, and aware of this technology then people will recognize these techniques more (like autotune or reverb – which was actually a comment linking to Gans to guitar pedals).

In terms of user interaction, I wanted to make a brief mention of tagging. That is user tagging images like blue jay. And in fact there was a tagging party at the Met to tag images. But this a point that Serge Belongie spoke passionately about. That none of this would be possible with out the unpaid labor of millions of people tagging things, either in general, or in their specific area of interest. And although this does sometimes result in bad data, it is by and large incredibly helpful. And we should perhaps talk about the ethics, economics, and what not of tagging. Also he made the comment that tagging is long tail, that most people tag the same sets of images that leave the majority of individual images untagged or perhaps tagged by one person.  This will have its own ramifications for machine learning.  I am sort of interesting in thinking about tagging in analogy with other similar activities in history should any exist (maybe translation – but not really,  The notion of pilgrammiges just popped into my head- I am not sure why)

Final Thoughts

What is the salient thing that ML/MI art would address? If such a question can even be asked.

Some thoughts that crossed my mind, was that it turned interpretations (e.g., ideologies), such as history, into the stuff of creative expression (ie art). That is interpretations NOT processes. One of the panelist said, what does the history of art look like, and how do we turn this into art (I thought of Ezra Pound’s Cantos and other written work that quotes from other work)?  What does it mean to talk about history as the source of artistic expression? For me it means interpretation or ideology – a new type of conceptual art.

Let us imagine that ML is one degree beyond the techno image, that it relies on the techno image but is not the techno image. Flusser wrote that the techno images is about contextualization. The artists is now producer, rather than a painter, or writer.  She puts different pixels in different combinations or different interfaces and recontextualize them. They are recombined, sometimes algorithmically, so these techno images can also be explorations of computational space (algorithmic space). I imagine video to be a techno image. So we can imagine a video to be another form of a techno image.

What does ML/MI do to the techno image? It interprets it. ML/MI is the consequence of outsourcing decision making (thanks Nitzan). It is not number crunching or data analysis. Different ML/MI represent different modes of decision making. We can call this interpretation or ideologies or perhaps something else. The space of the techno image, or computation in general, is the space of context, of bracketed models – e.g,  given gravity is 9,8 and there is no friction the baseball will travel x far in y time. The space of ML is the space of ideology. and value systems, it is the space of all models or meta models.  In machine learning we say: this is the data of chemistry, this is the data of astrophysics, we say this is what fitness looks like, this is what a blue jay is. What is a film made with one GAN vs another. What are the world views of each, the ideologies?  We are still in the grips of the techno image when we express this, how do we break out of this?





Guston on Painting


A few years ago a friend mentioned the artist Philip Guston.  Go check out his images on google.  I personally like his black and white line drawings or markings like this one.

Philip Guston - 1966 Faith hope and impossibility

Philip Guston – 1966 Faith hope and impossibility

But lets not talk about like or not like. I read a book of his collected writings and interviews about art. What is art these days? Who is entitled to make art? Why make a painting?  I was drawn to a few of Guston’s ideas (and then of course rejected others).

  1. The plane – the plane is not the plane of the canvas but the imaginary plane. This is where you create an illusion. You put two lines together or two colors, and something happens. It is like alchemy (my analogy not his).  I love this idea that the plane of the canvas is the imaginary plane, or maybe like Jung, the imaginal plane… the starting off point for active imagining.
  2. The first civilized man – or the first civilized man in eden. This is related to the idea in the image at the top of this blog post. That the artist is at the vanguard. Art is tied with a transformation of consciousness, or spirit.  The artist is the next step in the evolution, she is creating the next ‘reality’ or maybe we should call it the environment or milieu. I used to think that the artist was creating a new way of perceiving the world. But this is reductive. In the above quotation, the artist is re-enchanting the world. The artist is worlding within the world. Not creating an adjacent world but rebirthing the world.  (Also what would it be like to be the first painter, how do you paint without knowing what a painting is, what is painting from first principles).
  3. Diagram vs life- Lets move beyond a diagram (representation) to something that is vitally alive – that has its own life.
  4. I disagree with the critique of Duchamp and Cage. These figures to me are the star children of art. What is the artist when she moves beyond mediums or through mediums? This is the digitization of everything that brings in the recombination or fluidity of representation. Otherwise we fetishize a particular medium, becoming locked in it rather than transforming ourselves. (Again this leads to Guston’s meditation on Kafka and superconsciousness, the ability for the eye to see itself, for consciousness to observe itself. How can painting paint itself? How can art art itself?

I have been painting this winter at the art students league. I general procedure is that I sketch the sitter, sometimes with charcoal, sometimes with a blue acrylic wash. Then I will over draw a diagram, or glyph or sigil. Finally I will color in with solid (or as solid as I can get) colors. I have stuck with monochrome or one color in some instances. I try not to think, I try to surprise myself with my paintings,  They are not precious. I paint them on newsprint with cheap student acrylic and sometimes the paintings stick together if I am hasty and they have not finished drying.  Am I getting beyond myself? Am I super conscious? Am I creating something that is alive? Am I creating something that is between human and divine, beyond both or a child of both?

Requests for Dances! Art of Python! April 17 in Pittsburgh


I am down here in Dallas getting ready to teach another amazing CI/CD Dojo! I just binge read two management books on the airplane and feel up on the latest terminology. I might post something later. I was fascinated by a section on culture while reading Accelerate. There is a discussion of how to measure culture and how this feeds into productivity. I am interested in the construction of culture at the moment, however this seems slightly nefarious. But that is nothing new. Plato also wanted to manufacture culture — and keep the poets out of The Republic

In any case, I would love to see a dance piece at art of python. I have been meditating on this.  I would love to see a dance pieces that interpret CI/CD pipelines, build processes, Make files, even Docker containers. Art of Python is April 17th. There is still time! I think this is beautiful, how to perform a DAG.  We could even expand this to be dances inspired by different types of computational processes / theory of complexity/computation. I am thinking here of Scott Aaronson’s book Quantum Computing Since Democritus.

I know there are inspired dancers and choreographers out there that want to bring humanity to computation.