When photography “produces something other than photographs” | Hacker News Reader

When photography “produces something other than photographs”

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92 pointschippy31 comments

This artist's several sentence summary of an ANN and relating it to prejudice is fascinating: "The output of an artificial neural network can be roughly defined as a conclusion obtained by generalising a limited set of observations. Surprisingly prejudice can be defined in the same way. This will always be a problem with systems that generalize information. No matter how large and representative a dataset might be there will always be an eccentric outlier that will break the system." On the one hand this succinctly sums up the challenges we face with AI systems becoming more and more ubiquitous and on the other hand the reality we non-artifical intellegent humans face in living our lives and dealing with day to day encounters.

"The output of an artificial neural network can be roughly defined as a conclusion obtained by generalising a limited set of observations. Surprisingly prejudice can be defined in the same way."

Not really surprising. The first thing they teach in data science is that bias is everywhere. One of the first things taught in programming is garbage in garbage out and that computers do exactly what we tell them. Once you start making decisions with biased data you will start to prejudice some group.

The quest for non-biases systems is a little like a perpetual motion machine. If we all have biases and these machines learn from the same data we do, using systems we write, how could one expect a different outcome?

The

This is why you strive to identify the biases and move them from system 1 to system 2 thinking. AI will help humanity operate in a direct cognitive regime rather than sub-conscious one.

Not all or even most subconscious influence on decision making is bad. There is plenty we can’t yet quantify and fully understand.

This labels all imperfection in reasoning "prejudice".

Seems like a biased premise.

Definition 1 of prejudice in a lazy google search is "preconceived opinion that is not based on reason or actual experience." Certainly that figures into most reasoning, considering that perfect information is impossible.

I guess it depends on what we define reason and reasoning as. Are the rules a “reason” even if not “reasoning”?

That definition seems to cover everything you've learned a textbook, video, lecture, another person, or in any other indirect way, and which you didn't have an opportunity to think through yet.

Which is... most of the thing people know? Including, ironically, this very definition, which I learned about from a HN comment that quoted a Google search result...

It doesn't label. It doesn't do anything to "all" of anything. It doesn't refer to any "imperfection," and it doesn't address "reasoning."

This is a misrepresentation of the parent comment and the article.

It's interesting. Everybody is always talking about creating unbiased machine learning models, but we're still no closer to cracking the code on unbiased humans.

I'm not biased. It's everyone else that is.

In the data sense isn't bias literally just the result of limited/narrow data? So isn't the problem not in how you train models but simply the fact that it's impossible/exceeding difficult to provide omnipotent and universal data?

Bias of a data set is when it doesn't reflect the true underlying distribution of nature.

So a face corpus with only white faces doesn't reflect the diversity of faces one encounters in the world.

With that said, unbiasing data is extremely difficult because the true distribution of things is unknown and sometimes subjective. The visual images you would encounter as a human from birth to death growing up in a first world country would be very different from that of a drone's video camera. Are we really sure that imagenet should be K% animals and not K/2% animals? And if you train a machine learning algorithm on every possible image with every possible pixel, it will just learn noise.

There is a classic thereom from computational learning theory that says, if all hypotheses are equally likely, then no generalization can happen. Ie bias is necessary for learning.

To respond to some sibling comments: Yup, this is prejudice. I'll try to analogize the thereom with an example: Without prejudice, you can't recognize a leaf in a figure, because alternate hypotheses (there are an arbitrary number of things in this universe that look like leaves but in fact are not) are equally likely.

My advisor one told me that machine learning is the study of biases.

"Without the aid of prejudice and custom, I should not be able to find my way across the room." - William Hazlitt

Isn't this more a study of priors and statistics than bias? Bias would be an error between some latent underlying value and an estimate of it.

Interesting article about an extremely thoughtful artist. I liked this quote, "...artwork can be seen as an interface to experience the world. This makes the artwork akin to a scientific experiment, but while the experiment seeks to provide objective and repeatable knowledge, the artwork provides meaning and alternate points of view."

I try to look at modern art with similar lens, that way I can accept and tolerate at least some of them while pondering about their effects on me, and even find beauty in few.

But I have to ignore what giants like Rembrandt achieved, how much effort they put in and how universal those messages are. And sure as hell I can't and don't want to ignore that.

I guess I'll stay in the museums of the old masters (but not too old).

I am somehow drawn to the old Dutch masters and early Impressionists. Previously, I never was much of an art guy, since I took up photography again I look at art differently. Especially the play with light and shadows, composition amd colours.

I guess the closer paintings are to reality, the more I can take from them, and thus I am drawn more to them. For more abstract works I need time. Strangely, I develop a fondness for some of Dali's work... That being said, when visiting the van Gogh museum, I much preferred his earlier work more resembling the old Dutch masters. Still do.

You bring up an interesting point, not all modern art is directed at anyone other than the artist themselves. Its less likely in that framework that a particular artist just happens to create art that most people would also like and create a name for themselves and there are fewer trying to show off an absurd quantity of craftsmanship in a single work.

>I guess I'll stay in the museums of the old masters (but not too old).

On the other hand, I really enjoy the medieval art where there is absolutely no perspective and everything is the wrong size. I'd go to an exhibit just for that.

I like the site in general for its dedication to Hard Art. I used to visit at least weekly some ten years ago just to inhale a little bit of that European-tinged creativity. I'm happy to see it make the front page of HN. I should return to visiting more often.

That's a different lensless camera art project than yesterday's (https://news.ycombinator.com/item?id=36139729). Related list of lists:

https://github.com/golanlevin/ExperimentalCapture/blob/maste...

https://www.fotomuseum.ch/en/situations-post/vernetzte-kamer...

https://unthinking.photography/imgexhaust/three-new-cameras

  "Don't tell me you're going to use that smartphone for night photography."

  "My camera is augmented."

How does this AI sound camera thing detect color? I can see such a device seeing shapes and movements, but not color.

Maybe because he trained it on Mexico City videos and as an example in the subway for those particular sounds the ANN best matched the subway, the subway where in the training set the trains were that color.

That was a great question BTW!

How do you know the leaves bustling in the wind are green?

They might not be. They might be brown. But apart from that, how would this device know the color of a train?

Artists (specifically conceptual artists) are generally poor philosophers. You can expect a sort of a hodge-podge of presently fashionable ideas combined with some colloquial observations, banality, and inscrutable turns of phrase.

Take the distinction between the natural and the artificial. A colloquial distinction is not especially sensible. It's some kind of conflation between "man-made", not occurring in "nature" and "fake" which confuses a few notions that are not mutually dependent on one another.

In the first case, that something is man-made merely means that human beings made it. Water can be synthesized, but there is no difference between the water we find around us and the water we can synthesize. Human production involves the use of reason to modify or transform existing things to produce something else. But transformation of things is very much universal. Our cells transform things. Non-human animals and plants transform things. Stars transform things. The universe is in a constant flux of transformation. While only human beings are known to produce plastic (as far as I know), there is no reason in principle why other life forms or physical processes might not effect plastic.

In the second case, the notion of "nature" is a vague, largely romantic idea that doesn't seem to mean anything more than everything that isn't Man or man-made. Distinguishing Man from the rest of the universe is not unreasonable for certain metaphysical reasons (for example, the capacity for reason and thus moral responsibility; artifact as a product of deliberately and directly rational activity). But whence the sense of alienation? Perhaps this has to do with human moral failure. Traditionally, in the Jewish and Christian traditions, men were understood to be stewards of creation (pagan cultures tended toward pantheism which incidentally stifled their scientific development; modernism tends to denigrate the world by adopting a desiccated and reductive metaphysics which, while perhaps practical in some cases, is false). Stewardship is a responsibility and thus a failure in this regard can create a sense of rift.

In the third case, "artificial" can mean "fake", something presented as something it is not. But the mere fact that something is man-made doesn't mean it is "fake", and artifactual identity is dependent in part on the cultural conventions it is embedded in.

"Nature", in a traditional metaphysical sense, is merely the nature of a thing. There is human nature, the nature of plastic, the nature of water or trees or whatever. These are all real things and their nature is what makes them what they are. Thus, the "unnatural" is that which is opposed to the nature of a thing doing it. We say that a desire to eat glass or Styrofoam is unnatural because the consumption of it has no nutritive value, and the desire to eat is per se ordered toward nutrition. Thus we say that the desire to eat glass or Styrofoam is disordered, even intrinsically disordered. Wishing to cut your arm off is unnatural because human nature is ordered toward self-preservation. "Nature" is very teleological, in other words, but it is the basis for normativity.

I think artists are compelled to produce "artist statements" about their work, and in tune with current intellectual fashions too. This is a little like complaining that Ariana Grande wears stupid clothes.

So I take it you're a conceptual artist?

So... sounds like this artist statement on the distinction between the natural and the engineered has caused you to think about yourself, which is kind of the point?

I like the effort that the artist put into designing objects that we might consider to be strictly functional. For example, his data collection device and even the suit he worse to do data collection.

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