Challenges, opportunities, future

There a lot of questions to be answered. To what extent will algorithms replace designers? When will designers learn to work with algorithms? How will artificial intelligence change the design practice? When will a new area of data-driven design emerge?

Data pose many challenges for designers. Gathering data can be stressful: Shall I delete this file? Should I keep it? The more data we have, the more difficult it is to organize them and search. The omnipresence of data increasingly affects our attention span and time management. “You can get addicted to data,” says Piotr Migdał, Data Scientist. We hear increasingly often that algorithms are biased. Is it really so, or rather the results of algorithms reflects human behavior and decisions? According to Andrew Ng, Professor at Stanford University, in practice it is easier to reduce bias in AI than in people. 

Professor Piotr Płoszajski (Warsaw School of Economics) draws attention to the spectacular effects of using artificial intelligence in diagnostics. A database and the description of particular symptoms allow algorithms to detect autism in infants. The symptoms that can be observed by people will develop in children aged about 4. AI is also extremely effective in imaging diagnostics, as well as genetic and space research. The most fascinating thing about data analysis is that in large pools of various data there are interdependencies which cannot be found without artificial intelligence algorithms, which in turn may lead to groundbreaking phenomena.

Designers are faced with the challenge of going beyond the context of human-centred and human-oriented design. Perhaps we will design together with machines and data—“Technology can be not only the material, but also a participant in the design process”. (Giaccardi & Redström, 2020). Designers will both use and cooperate with data in the design process. Perhaps, we are currently on the verge of exhausting the current design framework and structures.

Data analysis is a creative process, just like design. According to Ewa Bugajska, Senior Data Analyst at Brainly, “an analyst is a data guide who protects the designer from over-interpretation”. A good analyst is a narrator. Designers also use narratives, for example when they create scenarios for using designed solutions, generate ideas or present concepts. Stories and narratives can become a bridge between the world of designers and data analysts. The clash of such narratives may contribute to a breakthrough in design.

In her Nobel Prize lecture, Olga Tokarczuk wrote: “It has turned out that we are not capable of bearing this enormity of information, which instead of uniting, generalizing and freeing, has differentiated, divided, enclosed in individual little bubbles, creating a multitude of stories that are incompatible with one another or even openly hostile toward each other, mutually antagonizing.” Will designers be able to change that?

2020

Optical brain

Jakub Mielczarek, Poland


Designers’ work has always consisted in extracting key observations from data, ordering complexity, finding meaning in the maze of information, combining seemingly distant phenomena. Designers visualize information, prioritize it. Similar words can be used to describe operation of many algorithms and systems based on artificial intelligence methods and techniques.

Will the design process become automated? Will designers specializing in problem solving replace algorithms? Michał Witkowski (Lead Game Economy Designer at Rage Quit Games) shows an interesting trend: “Analytics is becoming another support system for design.” But will people ever learn to work with algorithms which achieve unimaginable performance levels?

The installation of Jakub Mielczarek presents a prototype of an optical artificial neural network based on optical fiber. Such a simple optical neural network can be built by each of us, using commonly available elements for fiber-optic Internet networks. If we could simulate the operation of biological neural networks with light, they could process information about 2.5 million times faster than the human brain. One day of our lives would therefore correspond to about four hundredths of a second of the optical brain. One earthly year would take about 13 seconds in the optical simulation. In turn, in the optical world, a simulation of our entire life would take no longer than twenty minutes! Artificial intelligence can become more powerful than human intelligence in terms of both quantity and the speed of information processing. Is it possible that such super-fast artificial intelligence will remain in contact with humans?


AI is not going to kill us; it might make us more human”said Holly Herndon, American composer, graduate of Stanford University. Herndon has created a special Artificial Intelligence system that collaborates with her in composing music.

Data can become a source of expression and inspiration. They help to predict user behavior and create personalized solutions that are developed in real time in a continuous learning process. Designers have skills that allow them to cope with new challenges and understand the complexities that arise in human-data interactions. They can contribute to habituating people to data that often seem confusing and hostile.
Data are often demonized, dreaded, and may seem terrifying. And yet, texts and numbers are a symbolic record of human stories and behaviors, experiences, reflections and desires. However, data do not speak for themselves. In order to give them meaning, it is necessary to distance oneself from technology and create a narrative about data, which will be embedded in everyday life. We are at the heart of the digital revolution and still do not see all the possible consequences. It is not the first time this has happened. It is worth remembering what happened during the industrial revolution—to draw conclusions and try not to make the same mistakes.

Numbers can dehumanize and data is often a matter of numbers. When we reduce people to numbers, we risk abstracting human pain, even human rights. I’m thinking of immigration reports. The importance of designing data is not to be underestimated. Like our own speech and body language, the communicative power is in how we speak and move even more perhaps that what we say or in this case, what the numbers say.

Susan Yelavich, Professor Emerita, Design Studies, Parsons School of Design, The New School in New York

Artificial intelligence methods and techniques are the tool, and data are  the material. When designers have mastered this new tool and new material, then we can expect rapid progress in data humanization, rediscovery of data and the emergence of solutions that we have not thought about before. Designers can support the world of new technologies in changing the perspective by shifting the focus from data to people.