Books
Lev Manovich

AI Aesthetics

Ivanhas quoted2 years ago
1) Selecting content from larger collections: search, discovery, curation, recommendations and filtering.
Anastasia Marochkinahas quoted7 months ago
We can say that AI, implemented in this way, acts as a cinema (or art, video game, fashion, etc.) theorist and historian. These researchers also study many works created in particular places and historical periods to find common patterns. Their findings become part of the history and theory of this area.
Anastasia Marochkinahas quoted7 months ago
archi-tecture (often called “parametric design”)
Anastasia Marochkinahas quoted7 months ago
DeepDream neural net (2015-)
Anastasia Marochkinahas quoted7 months ago
abstract geometric images by
Anastasia Marochkinahas quoted7 months ago
Manfred Mohr (1969-1973)
Anastasia Marochkinahas quoted7 months ago
Google Clips video
Anastasia Marochkinahas quoted7 months ago
Assistance in creation/editing of new content. (If we are to think of AI as intelligent in the biological sense, we can cal this “participation” in content creation.)
Anastasia Marochkinahas quoted7 months ago
https://www.eyeem.com/eyeem-vision,
Anastasia Marochkinahas quoted7 months ago
https://www.eyeem.com/eyeem-vision
Ada Gogohas quoted9 months ago
AI now plays an equally important role in our cultural lives and behaviors, increasingly automating the processes of aesthetic creation and aesthetic choices.
Svyatoslav Yushinhas quoted10 months ago
Let’s look at computer science publications that quantitatively analyze Instagram as an example. To locate only quantitative papers, I usually add the word “dataset” to the name of the social network I want to find research about, and then search for this combination of words on Google Scholar. The search for “Instagram dataset” conducted on July 15, 2017 returned 9,210 journal articles and conference papers.
Svyatoslav Yushinhas quoted10 months ago
This is one of the key issues surrounding cultural uses of AI. Are the results of machine learning interpretable, or are they only a black box which is efficient in production but useless for human understanding of the domain? Will the expanding use of machine learning to create new cultural objects make explicit the patterns in many existing cultural fields that we may not be aware of? And if it does, will it be in a form that will be understandable for people without degrees in computer science? Will the companies deploying machine learning to generate movies, ads, designs, images, music, urban designs, etc. expose what their systems have learned?
Svyatoslav Yushinhas quoted10 months ago
Today AI gives us the option to automate our aesthetic choices (via recommendation engines), assists in certain areas of aesthetic production such as consumer photography, and automates other cultural experiences (for example, automatically selecting ads we see online). But in the future, it will play a larger part in professional cultural production. Its use of helping to design fashion items, logos, music, TV commercials, and works in other areas of culture is already growing. But currently, human experts usually make the final decisions or do actual production based on ideas and media generated by AI.
The well-known example of Game of Thrones (American fantasy television drama series that premiered in 2011) is a case in point. The computer suggested plot ideas, but the actual writing and the show’s development was done by humans. We can only talk about fully AI-driven culture where AI will be allowed to create the finished design and media from beginning to end. In this future, humans will not be deciding if these products should be shown to audiences; they will just trust that AI systems know best — the way AI is already fully entrusted to choose when and where to show particular ads, as well as who should see them.
Svyatoslav Yushinhas quoted10 months ago
the role played by cultural AI is probably not the most significant yet — but it is likely to grow in the future for at least two reasons. First, billions of people who still don’t have access to internet and smartphones will get this access and start using the same AI-driven recommendation engines, automated aesthetic editing of captured media, selfie-beautifying apps, and so on. Second, the automation of aesthetic decisions we have seen so far is still at an early stage, with many more things to come. For example, right now people take photos themselves, cameras apply some aesthetic adjustments at the time of capture, and then a person may use editing software to do further adjustments. But it is easy to imagine a future scenario where cameras will themselves choose what and when to capture to give us the most satisfying photos that fit certain concepts and aesthetic ideals. In fact, the Google Clips video camera released in January 2018 is already doing this. The camera is fully AI-based. It uses computer vision to recognize people and pets and certain emotional expressions, and was trained by professional photographers to make “good” videos with proper composition, interesting actions, etc. (Lovejoy, 2018).
Svyatoslav Yushinhas quoted10 months ago
Of course, a number of other trends also influence aesthetic diversity in contemporary culture besides computational technologies. The rise of the world wide web and social networks, growth of international travel, globalization of consumer economies and advertising, zero cost telecommunication, growth of foreign student enrollment, growth of remote work, and the rise of Japan, followed by Korea and then China, as exporters of cultural products and images are just some examples among many other developments all playing a role. On the one hand, they are making the world into a single global village — or if you like, a single cultural marketplace, where certain im-ages, ideas, values, narratives, products, and styles are marketed to everybody and available everywhere, and this may decrease diversity. On the other hand, the same trends may also be increasing diversity because local cultural DNAs become available globally.
b3993807707has quoted10 months ago
ural production may use AI based on a system of ex
b3993807707has quoted10 months ago
w compare these abstract algorithmic classics with current attempts to automatically synthesi
b3993807707has quoted10 months ago
We are not there yet. For example, in 2016 IBM Watson created the first “AI-made movie trailer” for the feature film Morgan (Mix, 2016). However, AI only chose various shots from the completed movie that it “thought” were suitable to include in the trailer, and a human editor did the final selection and editing. In another example, to create a system that would automatically suggest suitable answers to the emails users receive, Google workers first created a dataset of all such answers manually. AI chooses what answers to suggest in each possible case, but it does not generate them. (The head of Google’s AI in New York explained that even one bad mistake in such a scenario could generate bad press for the company, so Google could not risk having AI come up with suggested answer sentences and phrases on its own.)
b3993807707has quoted10 months ago
We can only talk about fully AI-driven culture where AI will be allowed to create the finished design and media from beginning to end. In this future, humans will not be deciding if these products should be shown to audiences; they will just trust that AI systems know best — the way AI is already fully entrusted to choose when and where to show particular ads, as well as who should see them.
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