Archives May 2018

Programming As Art: How Blockchain Can Help Artists (And Save Art)

Programming As Art: How Blockchain Can Help Artists (And Save Art)

Published on INC Magazine
Link to publication

Can blockchain save art?

Last month I spent a week in Moscow where I spoke at the Skolkova Robotics Forum on Smart Matter: 4 Things That Are Making Every “Thing” Smart. While there, I happened to visit a very unique gallery in the heart of Russia’s top cybernetics institute, the National University of Science and Technology, or MISiS.

There, I met Anna Karganova, the director of the Russian Abstract Art Foundation, and Olga Uskova, its president. (Olga is also a scientist, CEO, and self driving car technologist.)

After viewing some of the art, our conversation surprisingly turned to blockchain.

To put it mildly, that’s not what I expected from an art historian.

But as the conversation developed, it became clear that artists and curators are looking to blockchain as a possible solution to three problems in art. Provenance, or where an artwork came from, is always a challenge. Fraud will be an issue as long as people are paying millions of dollars for famous paintings. And knowledge about the art is something that curators are always hoping to share.

Here’s a summary of our conversation:

Koetsier: How can blockchain help artists and the art world?

Karganova: In the future, within just 5-7 years, blockchain technology will significantly increase the safety level for all participants of the art process. There are issues that blockchain can already solve now and some issues for which the technology still needs to “grow up.”

For us collectors, the most attractive and important thing this technology can give is the potential transparency of all the processes. In the open decentralized database which we can already build with the use of blockchain, we can store information and learn about the origin of the artwork … we can get info [such as] who’s the owner of it and who owns the copyrights. This technology also makes it possible to monitor all the transactions with the particular piece of art and maintain the provenance (exhibitions participation, publications in the catalogs, etc.).

If we have such a database, all the painters and their heirs will be able to track all the movements and relocations of their artworks. This will protect them from illegal sales and situations when after the exhibition the works are not returned to the owners for long time. It’s worth mentioning that the technology will be really useful and important for acceptance of artist’s resale royalties. So in long term perspective, painters and collectors will be more willing to participate and give their works for various temporary exhibitions.

The most interesting feature that can be developed with the help of blockchain technology is the possibility to purchase a piece/a share of an artwork. But for this one – the necessary legislative base is not yet available in the world.

Uskova: In this regard, in my opinion, we can implement such an advanced thing as a special cryptocurrency that will be used to evaluate artworks. Accumulation of the art’s capital/net worth can depend exclusively on demand: for example – on the total number of views or on the number of acquisitions.

Koetsier: Where would it be the most useful?

Karganova: First of all, blockchain technology can significantly help us increase and control circulation of the artworks. If we link all the originals to a single open database – this will ensure the number of copies of the paintings/photos/videos is fixed and guaranteed. In general, for all the new multimedia in art – blockchain is a perfect breakthrough system. And it will be especially interesting for those potential buyers who are attracted by innovations and high-tech in arts, but who are often stopped from a real purchase because of the particular insecurity of the art segment.

Koetsier: Honestly, I was really shocked to hear you talk about blockchain. Maybe I had an internal prejudice … art is creative, and blockchain is technology. How did you get interested in technology?

Karganova: Art and Technology have been linked for a long time already and we just can’t ignore this fact. Some time ago there were doubts about online auctions, but now this method of bidding has successfully and organically merged into the art environment that is historically quite conservative.

The convergence of arts and technology is a process that comes from several directions.

Artists who work with audiovisual and VR technologies often build their works on the basis of rethinking classic art and ideas embedded in it. More and more traditional museums include media artworks in their expositions. And of course all museums are trying to make their expositions digital to store them in worldwide web. One of the important reasons for this is the necessity to attract young audience. There are steps towards art from the developers of artificial intelligence too.

Uskova: Blockchain is a technology that is based on a new revolutionary ideology. For the artist it’s not only about the safety of the artworks’ storage and an easy access to virtual galleries, but it is an opportunity and a tool for creation of a new type of digital art. For example it may be an object that consists of many decentered, infinitely embedded worlds that are linked to and united by a single idea.

In the collection of our foundation we have works of a unique artist, Vladislav Zubarev. Back in 1977, when the world hadn’t yet suspected the existence of String Theory and before the discovery of the Higgs Boson particle, Zubarev introduced to the contemporary art world his Concept of Temporality.

He said that in a current time, with its dynamics and pace of change, it’s impossible to be a truly modern creator without putting time into a single coordinate system. He began to draw in four dimensions and his paintings got really magical dynamics, secrets of which are still not solved up to date by experts from around the Globe. Zubarev’s Theory of Temporal Art (1977) included so many correct guesses about the nature of space and time that in 2000s delegations of physicists visited him trying to understand how could an artist in the 1970s visualize what has later been discovered in 2000s.

So this is what can happen with blockchain technology too. Decentralized blockchain is a system of the different connected worlds of ever-changing information … a great basis for art objects of a new type.

Koetsier: How big an issue is fraud in the art world? Any idea of the scope of the problem?

Uskova: The problem of buying fakes is not that big at the moment as it was 10-15 years ago. There are several explanations for this.

Firstly, buyers’ interest has shifted towards the post-WWII and contemporary art, where there are a lot of options to track the origin of the artwork and its provenance. Secondly, methods of technological analysis have really improved. As for those who prefer to buy antique and classic art – these people do this for many years already and they are experts themselves. It’s more correct to call them not collectors but connoisseurs.

For Russian art, the most frequently falsified period is Russian avant garde of the beginning of the 20th century. It may now seem to everyone that the most famous fraud cases are left in 2000s, but nearly several months ago the Museum of Fine Arts in Ghent was involved in one huge scandal. Russian and international experts doubted the authenticity of some avant garde paintings from one private collection on show in the museum. This led to a large-scale investigation and early closure of the exhibition. It turned out that the provenance of paintings was unclear and consisted of different fake legends, and even the mentioned publications in exhibition catalogs were forged.

So what should we prepare for? I think that in a short term perspective the art of the middle 20th century will be in focus of fake makers. In Russian Abstract Art Foundation we have already started creating the database of samples for our artists and completing the catalogues raisonnés for internal use.

Koetsier: Defending against fraud is one thing blockchain can help the art world with. Anything else?

Karganova: Before buying an artwork, you should check as many details and facts as possible.

There are two main types of expertise: technological research and the one provided by art historians. Technological expertise studies pigments & binders and defines whether the painting fits the period that is claimed. But this type of study doesn’t prove or identify the artwork’s authorship. To confirm or to disprove the authorship, during the technological expertise, experts take X-rays. This study case helps to see the structure of the painting and compare it to the museum samples. In some cases ultraviolet light may be implemented. It identifies the signatures applied over the old varnish and shows the preparatory drawings that are individual for each artist.

If we talk about the expertise by art historians, they usually do some kind of a scholarly research. If you are about to close a deal, it makes sense to ask for an opinion of several experts, and better from different countries. Usually for a certain time period or an author – there is a limited number of experts. If two or three experts say that the work is genuine, then in the case of suspicion there will be no one to make an objection. The given certificates themselves should also be checked for authenticity. Nowadays to do that, specialists from auction houses ask the organization, that provided the expertise, to confirm has it issued the submitted papers or not.

All these processes are very time-consuming. And just imagine if all the data could be uploaded to one open database!

A clear provenance is a very strong reason to buy an artwork. The ideal and rare situation is when the whole history of the artwork can be traced from the artist’s studio to all the exhibitions and all owners. If any time periods are missing – then the provenance research is required.

Koetsier: Anything else that I’m missing?

Uskova: Nowadays we can witness just the beginning of the blockchain technology formation process; it is now still on the early stage. But the first deals begin to appear. There are still very few of them, but they set a precedent and allow us to identify all the possible downsides and limitations.

I think that the attractiveness of blockchain will grow with the generation that develops it. The great role of the current art world is played by people who are used to some certain rules and entourage. Pre-auction exhibitions, electrified atmosphere in the auction houses, discoveries of various unexpected data, positive art experts’ feedback – all of these provides emotions that are so important to the collectors of the old formation. This emotional experience, that is integral from the process of artwork purchase, is one of the most important parts of arts collecting. When people for whom speed and results are more important will get the necessary resources — then the introduction of the blockchain will no longer be an issue.

But now, when mathematicians and software developers work with AI projects, they also can no longer work without Contemporary Art. For example the Cognitive Pilot project team, that is now developing neural networks for self-driving cars, has recently moved to a new level – developers are now creating emotions for artificial intelligence.

This kind of work requires a fundamentally different approach: not mathematics, but arts … in order to understand and project emotions. So in order to understand different emotions, neural networks specialists participate in master classes about Arts that are conducted by the unique method of Ely Belyutin.

Modern programming is a form of a modern art. It has ceased to be a purely logical apparatus. With the advent of heuristic methods of programming and the creation of AI-objects, software products have a new theme of emotion that is so inherent to contemporary art.

Top Russian Cybernetics Experts On AI, Robot Morals, Human Extinction ... And Self-Driving Cars

Top Russian Cybernetics Experts On AI, Robot Morals, Human Extinction … And Self-Driving Cars

Published on FORBES.COM
Link to publication

Elon Musk has stated his opinion that AI could lead to the extinction of humanity, and it’s one of the reasons he’s working hard to make us a multi-planetary species. Stephen Hawking was incredibly clear as well: true AI could be the “worst thing” for humanity.

And yet, every country and major company is racing to build AI systems.

Small wonder: Russian president Vladimir Putin has said that the nation that leads in AI will be the ruler of the world. And China is investing heavily in winning the race.

I was in Moscow recently to speak at Skolkovo Robotics Forum. One of the highlights: a visit to Russia’s top cybernetics institute, the National University of Science and Technology, or MISiS.

I asked two of its leaders about AI, its dangers, and — of course — one of the tasks we might use AI for: self-driving cars.

Koetsier: There’s a lot of noise about AI today. We have machine learning and neural networks … but what is true AI?

Olga Uskova (Head of the Department of Engineering Cybernetics): From my experience I can say that under ‘artificial intelligence’ people understand the state of an object when it actually becomes the subject and begins to have an independent abstract thinking.

Koetsier: You’ve been working on AI for decades, and the MISIS Cybernetics department just celebrated its 50th birthday. How far have we come in that time?

Konstantin Bakulev (Deputy Head of the Department of Engineering Cybernetics): 50 years ago, when MISiS Department of Engineering Cybernetics was created, and it was created by a group of very young scientists from the Institute of Theoretical Physics under the leadership of Alexander Kronrod, the AI theme was represented by methods of Heuristic Programming. And literally in the first year of the department’s existence, young scientists together with students created the first heuristic algorithms for playing cards.

The computer complex at that time occupied two rooms — an area of about 80 square meters. The code of the program was entered by perforated cards. Each response of the machine to the cards took several minutes.

In 2018 the students of the department, as a course work, created a system for semantic analysis and analysis of news feeds to create analytical reports on changing of purchasing power of Russians during the holidays. Now gigabytes of information are processed in just a few seconds and this work was done by two fourth-year students just within a month.

Koetsier: For achieving AI, do we need more speed/processors/memory? Or do we need different thinking/algorithms?

Olga Uskova: We need all of these.

On one hand some leading developers, including us, are following the path of building an anthropomorphic model. When we started studying the decision-making process of the person behind the wheel [note: Uskova also leads a self-driving startup, Cognitive Pilot] we discovered that the logical intelligence is not the only one participating in this process. A significant part is occupied by emotional intelligence, the data for which doesn’t go through sequential processing by standard methods. The final solutions are achieved by connecting some types of neural networks.

By the same principle, we are now building neural networks for our automotive AI. There may not be many pictures, but they must be correctly marked and they must give a new knowledge to the neural network.

So we came to the theme of programming of intuition. In particular, the analysis of the behavior of small objects on the road as a material for predicting the change in the road scene in the next few seconds (for example it may be the change in the angle of the car driving next to you or the ball that rolls out onto the road). Thus in many cases it’s necessary to have not ‘more’ data/information, but ‘smarter’ data/information. This is a bit like teaching people how to read fast.

Koetsier: The kind of AI everyone is waiting for is a kind of Star Trek intelligence that you can talk to, get answers from, and have human-like conversations with. We’re seeing the beginnings of this, maybe, with Siri, Alexa, Cortana, and the Google Assistant. How far away are we from near-human-like intelligence from these assistants?

Konstantin Bakulev: This is a multi-layered question.

Technologically we have already come to the possibility of programming emotional intelligence, and this is extremely important for communication. But when a person is brought up, he/she genetically or historically has a number of restrictions – moral, religious, social. In different value systems, the basic moral values can differ diametrically.

If you are engaged in the development/formation of AI, especially the formation of its emotional part without limitations, then the result can arise with a set of some aggressive characteristics. Because aggression is one of the strongest emotions in social networks and it is dangerous to feed such data to AI.

Koetsier: Super-human intelligence, of course, is what some people worry about from AI. Do you see that as inevitable? And, will it come quickly when real breakthroughs in near-human AI are made?

Olga Uskova: I share Steven Hawking’s opinion with whom we had a short talk on this topic a few years ago. And now I’m totally convinced that he really foresaw many things.

Continuing the anthropomorphic analogy: when a person grows up and learns, besides the recognition of images and meanings of surrounding objects, the self-awareness of himself/herself as a person arises. The same way the AI at the stage of recognizing meanings at some point will definitely come to the process of self-awareness as a separate entity.

And if by this time we don’t bring into the training system any moral limitations – the consequences for humanity can be instant and terrible.

Even now for a lot of people it’s not always obvious that they are useful for an existing ecosystem. People destroy ecology, litter a lot, kill rare species of animals, so the logically thinking AI will quickly come to a conclusion about the uselessness of mankind.

Koetsier: Should we worry about super-intelligent AIs? Will they be dangerous?

Konstantin Bakulev: I think that it’s necessary to solve two problems in parallel: we need to adjust our own behavior towards good and love and impose some moral restraints on the whole territory of the planet when programming AI on the principles of Isaac Asimov.

The principles of AI development and management should be similar to the principles of working with weapons of mass destruction.

Koetsier: When will we get there?

Olga Uskova: Well, here I want to be extremely honest. When programming neural networks, we clearly understand what is the input (what happens at the entrance), we understand what is the output (what is the result), but we do not always understand what is done inside.

While some of the tests at the testing facility there were cases when a multi-ton vehicle suddenly made its own independent decision to improve the situation, which, we think, we haven’t programmed. And then after several months of analysis of what has happened – we’ve got new knowledge about the behavior of deep neural networks.

So it’s not only that we develop and teach the artificial brain, but it’s also teaching us.

And neurophysiologists that consult our team use the results of Cognitive Pilot’s work to restore some of their patients after serious accidents. We all live in a mixed society already, where both biological and silicon organisms are present. And while we are fighting to make silicon organisms smoother and smarter, it’s very important to make sure that we don’t totally ‘mute’ the biological ones.

Koetsier: Talking about self-driving cars … how close are we, in your opinion?

Olga Uskova: Our approach is that for industrial use on autonomous transport we should use only systems with an accuracy of recognition very close to 100%. It’s difficult to achieve this accuracy, but the latest technologies allow it.

Cognitive Low Level Data Fusion is an approach that allows you to increase the accuracy of autonomous systems up to 99.99%. It combines raw data from all sensors of the machine and processes it with a neural network.

This tech will allow you to drive the car better than a person does.

In some sense, in August 2017 a new era of autonomous vehicles began. It brought the use of fully autonomous vehicles on the roads of the world much closer. Of course, in addition to technological, there are serious legal, social and moral limitations that require special development and attention of the whole humanity without division into national and state borders. This is a very important issue, just as the use of nuclear energy for peaceful purposes.

Therefore, a complete transition to self-driving cars in the world will require a minimum of 10-12 years to develop new traffic rules, moral restrictions and legislative norms for mixed car flows. The United States has the most developed practice in this sphere and undoubtedly the experience that America receives allowing the use of driverless cars on public roads is very important for all AI developers around the world.

Koetsier: Thank you both for your time!