Economics, Bubbles and Transformations (flowchart)

Peter Hagdahl, 2023.

The site-specific artwork Economics, Bubbles, and Transformations (flowchart) by Peter Hagdahl in the premises of SSE´s House of Innovation, Norrtullsgatan 2, is a dynamic reflection on the social development of our time. The artist explores economic flows, social changes and historical events, which are portrayed through a fusion of painting, drawing and video animation. The various forms of expression create a versatile spatial design that explores the connections, contradictions and conflicts that characterize our times.

The work resembles a comprehensive process map or a complex flowchart. It extends over two floors and is made up of different techniques and materials such as photography on glass, painting on acrylic plastic and video projections. By using various artistic methods – painting, drawing, animation, programming and photography – a diverse expression is achieved. By combining elements from different sources – e.g. historical and socio-economic facts – with the artist's own comments and associations – unexpected coincidences and tensions arise. The images used in the work are simple symbols or pictograms in primary colors carrying references to art history such as Herbin, S. Delaunay or Riley. The static expressions of the paintings and drawings meet the movements of the projections. By including information flows from the internet, a constantly changing image is created.

Economics, Bubbles, and Transformations is a reflection on the constant change and complexity of our world. The work visualizes the tension field of various forces that affect existence. At the same time the work challenges and transforms our way of understanding the world around us.

Peter Hagdahl, born in 1956, is a Swedish painter, installation artist and former professor of liberal arts. He lives and works in Stockholm and Paris, and he studied at Valand Academy of Art in Gothenburg 1983 to 1988 and P.S.1 Contemporary Art Center in New York in the nineties. In 1996 he founded Creative Room For Art and Computing. He has worked as a professor of liberal arts at Konstfack 1997 to 1999 and at the Royal Academy of Arts 1999 to 2009, as well as a curator at the Public Art Agency in Sweden.

The artwork is a donation by Josefsson Foundation and Lars Bane.

All photos: Mikael Olsson

Peter Hagdahl´s homepage

Photo: Mikael Olsson

Text by SSE student Douglas Bengtsson

Do you want the good news or the bad news?

Let’s imagine you participate in an experiment on good news and bad news. This experiment is created by a group of data scientists at an American social media company. In this scenario, we will imagine that I am the one running the show; I am a young computer science student at KTH that will soon graduate with a specialization in data science. You are one of our millions of users.

Goal: to maximize the time you spend on our app.

Method: choose which content is featured, based on a “sentiment analysis”.

The first thing I do is google what "sentiment analysis" is and why I would want to use it. The results show that it is a method to put a numerical value on the sentiment of a text. A positive text includes words like “fantastic” or “win”, and a negative text includes words like “devastating” and “attack”. It provides an objective metric to something that can otherwise be subjective.

I realize that I can predict which news stories you want based on the sentiment of the text. You prefer the good news. You have grown tired of reading about the current state of the world and how everything seems to be getting worse. That’s fine by me, I don’t make the news and I only want you to continue reading them. I won’t show you those news stories.

However, your friends seem to be more open-minded toward reading bad news. I try to show you the things they share on your timeline, but you still don’t seem to care. Fine by me, I’ll just make sure that your friends are prioritized less on your timeline. Instead of showing you posts from people you follow, you will now see a customized feed that I think you will like more.

I won’t show you the bad news, but I think some of your friends prefer to see them. Fine by me, I can separate them into a different group that is shown the bad news. One of them really likes to see the bad news; it’s almost scary how often she clicks on those articles. I wonder if this is affecting her mental health?

After some investigation, I realize that there is an obvious flaw that I have missed. All news stories cannot be objectively measured. Sometimes it is a zero-sum game, where good news to one person is bad news to another.

Lucky for me, I have learned more methods within data science. The world isn’t as easy as classifying something as good or bad. Instead, I can choose a much more complex model that will predict which content you prefer. The only drawback to this model is that it is a black box. I can’t explain in words why it is you prefer some things to another. It would never be my goal to feature unethical content, but it’s such a pity that my algorithm is so good at maximizing our profits.

The experiment that we have imagined is more or less realistic. In Peter Hagdahl’s interactive piece, we see a simple algorithm in action. It scrapes news from the BBC and New York Times, and outputs a “yes” or “no” depending on the sentiment of the text. In this work, the viewer will probably agree with the sentiment of shown enlarged. However, occasionally, you will stop and wonder if you agree and wonder which words made it classify it as either good or bad. Perhaps it is worthwhile to do the same while scrolling social media. Why am I shown this content? Do I want the good news or the bad news?