As machines develop, information work decreases, and education should provide skills for new kinds of design work, write Matti Tedre and Peter J. Denning.

THE information technology revolution is advancing at a rapid pace.

Customized smartphones for individual needs have the power of supercomputers from the turn of the millennium and keep us online almost everywhere. Self-driving cars are already on the roads. Companies like Uber and Airbnb challenge old business models. Computers monitor health and diagnose diseases. Many traditional jobs and professions have disappeared.

The ability to represent and process any information as bits has continuously improved. First, computer simulation became a central tool in science and engineering, opening new possibilities in almost every field. Then personal computers made everyone a potential computer user.

The Internet and especially its www services made global communication everyday. Computers became communication devices. Billions of computers have been connected to the Internet. Now fast data connections are part of societies' infrastructure, and new services based on them are constantly being created.

The artificial intelligence revolution has made image recognition, speech recognition, machine translation, and diagnostics easily available. Through machine learning, computers perform specific tasks faster, tirelessly, more cheaply, and often better than humans.

THE DEPTH OF THE TRANSFORMATION is comparable to the Industrial Revolution. Then machines replaced a vast amount of manual work, for example in the textile industry and agriculture. The changes shook the foundations of society and caused instability.

An entirely new sector emerged in the 20th century: information work. It was long believed to require an intuition that machines do not possess. Universities became training institutions for information workers. A university degree became a ticket to a career.

Now machine learning questions these old truths. Any task that can be learned by studying how that same task has been done the previous hundred thousand times is a likely candidate for automation. Task outsourcing and crowdsourcing are harbingers of its future automation.

Information work decreases as machines develop, but new types of work closely related to it – for example, design work that creates something new – increase. In information technology, the emphasis shifts from coding skills to understanding and skills in communities, language, mentoring, innovation, culture, values, added value, and social change. In Silicon Valley, it is precisely these design workers who master such skills that are behind information work automation and new services.

FOR THE EDUCATION SYSTEM, this change is a major challenge. It is easy to get stuck discussing the tools for transmitting and acquiring knowledge instead of preparing for information work automation, even though it has already changed and will continue to change the roles of computers and humans at work.

Although the amount of design work is growing and will offer new careers and jobs in the future, our education system provides little preparation for it.

As information work becomes automated, it is important to understand information itself. Education should add tools for analyzing and structuring problems that allow solutions to be presented in a form that computers can process.

Key competencies for design work include understanding communities and their backgrounds, awareness of social networks and interaction, and understanding human behavior and practices. These competencies help understand the needs of people and communities and avoid excessive technological faith.

RETRAINING BASED ON PREVIOUS knowledge can help those who become unemployed due to robotics and information work automation build a new professional identity. A constantly changing and unpredictable working life also requires the ability to combine old and new skills.

Successful education preparing for design work combines technical, communal, and human understanding skills. We should not teach how to compete with robots. Instead, people should be trained – using automation – to solve problems that robots cannot yet handle.

Matti Tedre and Peter J. Denning

Tedre is a computer science researcher at Stockholm University and Denning is a computer science professor at Naval Postgraduate School in California.

https://www.hs.fi/paakirjoitukset/art-2000002927745.html