While we were appropriating

While we were appropriating

While we were appropriating, the machine was learning. What we were appropriating and what the machine was learning may have run parallel for some time, yet the machine was more studious (trained by studious people) and concentrated on a large volume of structured data. Machine learning is massive; in comparison, humans can access only a small part of the existing and potentially learning material. However, an equally important difference is that humans attribute a concept to the product of their appropriation, while machines generate content on a given concept with the use of pre-existing content (appropriation). At both ends of the line is ‘the concept’ which for the moment derives from and stays with humans.

What is appropriating: To incorporate elements from existing works, like texts and images, into one’s own work without much transformation and without the permission of the creator. 

In the arts, appropriation has always been a practice, as in ‘Dali Mona Lisa’ or the African masks in the paintings of Picasso and in the artworks of the dadaists. Where in art limits are vague, in textual works there is more control. The academic world has sorted this out: In your writings you must mark every bit of text, phrase, or idea that is not strictly yours and put the reference in the foot/end-notes. In any other case appropriation is called plagiarism. In the art world, boundaries are loose and the issue is addressed case by case, usually attached to a legal process. However, an effort is made to draw some rules in image appropriation, such as the Appropriation Art Guideline, a policy drawn by Pictoright, the author’s rights organisation for visual creators in the Netherlands.

The recent release (November 2022) of generative artificial intelligence bots by OpenAI, along with increased media attention, has sparked once more the discussion about the relationship between humans and machines, the issue of property and copyright of the used and the generated material, and the eventual job loss as a result of increased automation. 

The talk is about generation of texts and images, including artworks, with the use of algorithms that analyze and recreate content and form/style. The AI uses text to generate text and prompts (commands) to generate images. The image generating AI also creates image variations based on a generated or an uploaded image. On text generative AI bot ChatDPT you can have a smooth conversation with the machine. You ask a question and the machine generates an answer. When asked about the impact of text and image generative AI on employment, the machine answers:

“As an AI language model, I do not have personal opinions or feelings. However, I can provide information and context on the topic of the potential impact of AI on employment.”

It also states that its training stopped in 2021, so information after that year is not in its set of knowledge. The generated texts seem quite general; they can be used as a basis for further editing and creating a specific text, for example for marketing purposes, (micro)blogging, reports, etc. For shorter advertising texts, the Ai-generated text suffices. 

While the generation of text seems to go smoothly, the generation of images is more of a struggle. For example, when experimenting with DALL-E, which is described as “capable of creating images from natural language descriptions” (such as ‘a red kitten with back light on ears’), it soon becomes obvious that one has to learn to ‘talk’ to the machine in order to get something other than a smudge or a caricature out of it. That means that there is a need for usable prompts (commands, string of text) in order to have generated something close to the desired image. Entering easy ideas for a start, numerous examples are images of kittens and puppies, or zombies and cartoon heroes. When moving a bit further, the generated images are less interesting, ranging from illustrative clichés to incoherent smudges or too close to the source image (without the flair) to be considered a new creation.

The machine still has a lot to learn about art and words alone will not do the job. That aside, and despite the fact that there has been AI experimentation in the art world for a few years already, visual artists start having dark thoughts about their role in the future, or the near future for what concerns illustrators and graphic designers. At present, it is good to note that DALL-E is still in research (beta) mode; the generated images do not fall under copyright law because they are not human creations; when you upload your own images, these are considered ‘feed’ and are taken into the database and anyone can use them.

DALL-E generated image ‘Van Gogh style painting Cat with bandaged ear’ [off topic]

Thinking backwards, a number of points line up: the question of quality of the generated images; the question of property and copyright of the appropriated material and of the generated as well; the question of prompts; the question of quality of the generated text; the question of quality and extent of the fed & learnt material; the question of impact on creative professions. 

In experimental and open mode these text and image generating tools are fun and fine. It is the extent and speed, as well as the natural-like language use of ChatGPT, that make these tools a mega-appropriation project. This will bring changes in laws, jobs, ethics and aesthetics. It is a game changer, worth checking. Try it and enjoy it before the serious questions, like ‘why’ and ‘what for’, will pop-up. There might be a little traffic jam on ChatGPT.

“We’re experiencing exceptionally high demand. Please hang tight as we work on scaling our systems.” [Sincerely yours, ChatGPT]

P.S. 1 The non-digitally-documented artifacts (and texts) are not part of this game.

P.S. 2 This is an interesting article; an interview with ChatGPT (read the comments too): Thoughts on AI’s Impact on Scholarly Communications? An Interview with ChatGPT

The authority of the button

The authority of the button


Introduction no 1

Being, or not, a person who doesn’t like to be told what to do is of no importance; we all succumbed at some point to the button. Being aware, or not, of when the delirium started is of no importance either. At present, the button is triumphing.

The authority of the button in practice: you do when you press it. Yet, this authority goes beyond the physical action on to the power exercised on thought and will of each one of us.

The following text was a brief comment, expressed rather as a question, that was published in a closed wiki last year (2016) as assignment in the course ‘Media Philosophy’.  It refers to text as this was the subject of the study; but the visual and the arts are in the same stream.

The comment: the authority of the button

[…] in text-related technologies, we can take as example the structure of the digital text with its multilevel linking; all with the use of the button and the necessary user’s action of clicking.

The button is a technological device that entails simultaneously the option (free choice) and the command (authoritarian behavior). In these two contradictory traits, the first lays the foundation for the second to establish itself. A technology with innate capacity for organizing power and authority seems the only option in a democratic society; seemingly, the authority is diffused to the people that use this technology.

The use of the imperative form, either friendly as in “join, share, like, etc.” or service oriented as  in “listen now, download now, go there now, etc.”, and of course more directly commanding as in “buy now”, would not be accepted otherwise; not in politics, nor in social life. Instead, because of being essential to the structure of the specific technology, and through its material carrier, the button, the command has been accepted as normal. In its turn, the authoritarian behavior exercised on individual level, shifts the limits of acceptable authority that can be imposed centrally.

The question arises: is the authoritarian tendency innate to humans so that the central power contains it as much as the technology that they produce?

Introduction no 2

The button has been a peculiar element of modern times. It has been the focus of awe and of mockery since the moment that its use left the industrial terrain and spread in to everyday life. Between Chaplin’s uncontrollable machines in his movie Modern Times (1936) and The Matrix (Wachowski brothers, 1999), buttons became an accessory in the hands of literally everyone.

One push further, the statement ‘Never send a human to do a machine’s job’ (The Matrix) moved from the sphere of the joke to the common belief.

P.S. 1 I had a hard time in the Univ when omitting the conclusion/closure bit, faithful to the inconclusiveness of art. Cause, apart from believing in this as the only possible free area, I considered all my writings as being part of my artistic practice (no conclusions, only open space). That is why this blog post has two introductions; one to start and one to finish, with the question in the middle.

P.S. 2 The front image is a detail from a textile work of mine titled ‘The memory of a nebula’; embroidery with some padded parts.

‘Do not press’ – acrylic on canvas, 1998


Digital analysis of a blog

Digital analysis of a blog

What can distant reading say about a blog, when we know its theme and we follow it either from the author’s side or that of the reader? What is expected from a digital analysis of a non-commercial blog?

There are numbers and ratios retrieved, and lists of words (the most commonly used) as well as links between them. There is a web revealed and a mapping done. The analysis is both quantitative and qualitative, the two tightly correlated.

A good number of digital analysis tools for texts have been developed and are in use the last 10-15 years. Those who have more understanding of such tools set themselves the terms of the analysis, to some extent; for ex. which common words (a, the, and, etc.) to exclude when composing the word frequency lists. This is not an impossible task, it takes however a lot of work and a brave brain squeeze. Though I find something intriguing to it, I don’t feel that brave to meddle with commands, expressions, and you name it. I have done it, and even got some result. But, the ratio (!) of success towards failure is a negative figure. A simple job can be done with the ready-to-use free online tools, like the Voyant tools, and such (with thanks).

Summary of the five most recent posts (here seen as a ‘corpus’):
This corpus has 1 document with 5,077 total words and 1,541 unique word formsVocabulary Density (ratio found by dividing the Total Words by the Unique Words): 3,30 (not too bad) [see literary examples: Vocabulary Analysis of Project Gutenberg].
Average Words Per Sentence: 22.3
Most frequent words in the corpus: art (49); artists (33); artist (23); like (22); work (20); blog (15); authority (13); time (13); words (13); life (10); sea (10); book (9); march (9); music (9); way (9); world (9); april (8); arts (8); comment (8); january (8); p.s (8); people (8); read (8); status (8); books (7); don’t (7); end (7); essay (7); facebook(7); film (7); google (7); irony (7); kapnissi (7); kind (7); leave (7); linkedin (7); loading (7); market (7); order (7); pinterest (7); poetry (7); posts (7); reddit (7); september (7); share (7)

By this, the theme of the blog is already set, with a little surprise in the mention of the ‘sea’. The social media presence was inevitable, as they make part of each blog post (that is why I did not remove these words/ names) even though not in the actual text. While here we see about 50 words, in the visualization with the name cirrus we can view many more words in one look; I set it up to retrieve 150, so this is what this cloud-like word list shows:


Quite interestingly but not a real surprise, the word ‘depression’ pops-up as a prominent one, yet not as prominent as the ‘sea’, or ‘music’. And it is possible to go even further and expand the viewing of the words used in this part of the blog, in this beautiful arch, which works itself linking word for word in a rhythmical progression:


As artists, we find and we make links between whatever lies in this world of ours. Words are more specific in this, that is why they are regarded as more appropriate for conveying meaning and for transferring knowledge (make a note for another post, though just one will not be enough for this topic). Digital analysis tools also find links between words in the analysed text. The result of such a search can be presented for ex. like this:


In a very quick viewing of this visualization, the word ‘status’ is linked to the word ‘artists’, the ‘artist’ is linked to ‘authority’, and ‘art’ is linked to the ‘artists’, to ‘history’, and to the ‘market’.

Reversing the findings, what is not there also says something about the analysed text. In this case, what is absent are the names of people, and specifically of (famous) artists.

Text analysis tools give a variety of options for breaking down the text into its components and re-composing it in an untangled form. The new forms, rather in plural, are untangled from whatever we have in our mind regarding the text(s). However, these tools also entail to some extent the choice for manipulation (of input and result). This makes the analysis a game, which seriousness lies upon you. A lot of responsibility again; here is a knot representing the vicinity or correlation (not clear) of the words ‘art’, ‘artists’, ‘work’, ‘authority’, and ‘time’:


I must say, that the first time I saw a visualization of a data set (or of a text, not sure) I was so impressed that since then I look for such things, mostly with the artist’s hat on. There are sophisticated people out there that can make real use of the analysis tools, systems, methods, etc. I am happy I managed to take a glimpse (and, I have some fun ideas…).

P.S. Text analysis and visualization are not necessarily connected. They can also live apart. Visualization lives in science and in art, and relevant studies can be done in either field. Here is someone who combines both; have a look, there are interesting things in here: http://manovich.net/