This post was written for Molly Steenson’s Seminar I: Interaction & Service Design Concepts 2016, CMU School of Design.

Go is an ancient Chinese game, where two players take turns placing stones on a 19-by-19 grid. Whoever takes control of most of the territory, wins. This centuries-old game, that is considered much more challenging than chess, had its first non-human master player in 2016. Google’s DeepMind artificial intelligence, won four out of five matches, defeating world master player Lee Se-dol. Dr. Noel Sharkey, AI expert explained that to beat one of the world’s top players, Deep Mind used a mixture of clever strategies (1). At the end of the game, Lee Se-dol was congratulated on the fact that he was able to make at least one win against the intelligent system. Notice the term intelligent. What do we really mean by it? Intelligence can be defined as the ability to learn, adapt to an environment and situation, and solve problems that require analytical thinking. But that’s just one aspect of intelligence. There is a huge part of intelligence visible in humans that comes from their consciousness. Emotional Intelligence. After the game of Go, DeepMind did not celebrate the joyous victory. It probably did not even care that it played against one of the world’s best master players. Or that it played at all. It just understood the game of Go, built strategies that would let is win, and it won. That was the function directed into it, and it achieved its goal. We see technology advancing at a phenomenal rate. We know that the future of technology is beyond great. In fact, we expect it to be. But when AI scientist like Raymond Kurzweil predict that the future is one where humans will be essentially eradicated in favor of intelligent machines, I have difficulty digesting that thought.

Even Stephan Hawking, the greatest scientific mind of today’s world, believes in this version of our future. He said, ”I believe there is no deep difference between what can be achieved by a biological brain and what can be achieved by a computer. It, therefore, follows that computers can, in theory, emulate human intelligence — and exceed it.”. (2)

We as humans are still pushing the boundaries to understand the true extent of human intelligence and what it means to be living with consciousness. To predict that we will create machines that are beyond our intelligence matrix seems a bit far off. In fact, till date we haven’t been able to create an AI machine that is able to pass the Turing test. It was in the 1950’s, the beginning of the computing age, that Alan Turing first grappled with the question “Can machines think?”. He hoped that by the year 2000, humans would have created machines that would think on their own. The term Artificial intelligence had not even been coined at that point of time. John McCarthy came up with the term in 1956. Artificial intelligence is a very broad term. It has been divided into critical categories, known as AI caliber (3).

There are three major AI caliber categories:

Artificial Narrow Intelligence (ANI): Referred to as Weak AI, Artificial Narrow Intelligence is AI that specializes in one area. Google’s DeepMind falls into this category. It can beat the world players at their games but ask it to solve criminal injustice and it will probably not respond. Artificial General Intelligence (AGI): Referred to as Strong AI, or Human-Level AI, Artificial General Intelligence refers to a computer that is as smart as a human across the board — a machine that can perform any intellectual task that a human being can. Artificial Superintelligence (ASI): Oxford philosopher and leading AI thinker Nick Bostrom defines superintelligence as “an intellect that is much smarter than the best human brains in practically every field, including scientific creativity, general wisdom, and social skills.” Artificial Superintelligence ranges from a computer that’s just a little smarter than a human to one that’s trillions of times smarter — across the board.

We are still playing in the field of ANI. Our mobile phones are little worlds of ANI systems that help us in our daily lives. We have AI bots present in stock trading and directing medical procedures or even helping you learn new languages. But all these little ANI steps will lead us to eventually achieve AGI and then, in all probability, ASI. It’s our ethical decisions in forming new ANI systems that will lead the way for the future of ASI systems. So what becomes my role as a designer? Since I lead my world with emotional intelligence at my core, should I be creating systems in place that push the boundaries to instruct emotional intelligence in AI? But critically, if a computer stimulates emotion, does that really count as a true emotion?

Interaction & Service Design Concepts: Principles, Perspectives & Practices 2016

Graduate Seminar 1, Fall 2016, Carnegie Mellon School of Design

Manjari Sahu

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India | USA | The Netherlands…A designer broadening her perspective on critical thinking and how to do good by design.

Interaction & Service Design Concepts: Principles, Perspectives & Practices 2016

Graduate Seminar 1, Fall 2016, Carnegie Mellon School of Design