There is, in some quarters, concern about high-level machine intelligence and superintelligent AI coming up in a few decades, bringing with it significant risks for humanity. In other quarters, these issues are ignored or considered science fiction. We wanted to clarify what the distribution of opinions actually is, what probability the best experts currently assign to high-level machine intelligence coming up within a particular time-frame, which risks they see with that development, and how fast they see these developing. We thus designed a brief questionnaire and distributed it to four groups of experts in 2012/2013. The median estimate of respondents was for a one in two chance that high-level machine intelligence will be developed around 2040-2050, rising to a nine in ten chance by 2075. Experts expect that systems will move on to superintelligence in less than 30 years thereafter. They estimate the chance is about one in three that this development turns out to be 'bad' or 'extremely bad' for humanity.

In 1997, an AI beat a human world chess champion for the first time in history (it was IBM's Deep Blue playing Garry Kasparov). Fourteen years later, in 2011, IBM's Watson beat two winners of Jeopardy! In late 2017, DeepMind's AlphaZero reached superhuman levels of play in three board games (chess, go and shogi) in just 24 hours of self-learning without any human intervention, i.e. it just played itself. Some of the people who have played against it say that the creativity of its moves make it seem more like an alien that a computer program. But despite all that, in 2019 nobody has yet designed anything that can go into a strange kitchen and fry an egg. Are our machines truly intelligent? The fact is that today AI can solve ever more complex specific problems with a level of reliability and speed beyond our reach at an unbeatable cost, but it fails spectacularly in the face of any challenge for which it has not been programmed.

The last few decades have witnessed innovations in modern medicine, science and technology at a much faster rate than at any time before in history. A large portion of the credit goes to computers, for helping us solve problems more efficiently and therefore at a faster pace. Most recently, this has included the rise of Artificial Intelligence (AI), machine learning as well as neural networks that can simulate human thought patterns. They can then apply their more efficient brains to issues that desperately require resolution, many of which are in STEM fields like medicine or cryptography. STEM stands for science, technology, engineering and mathematics, but a far wider range of academic disciplines fall under this description. Courses one could study range from aerospace engineering and astronomy to civil engineering and statistics.

A robot holding a human brain in a virtual display isolated on a binary data numbered background, as an Artificial Intelligence (AI) in futuristic digital technology and medical concept/3-D illustration. The last few decades have witnessed innovations in modern medicine, science and technology at a much faster rate than at any time before in history. A large portion of the credit goes to computers, for helping us solve problems more efficiently and therefore at a faster pace. Most recently, this has included the rise of Artificial Intelligence (AI), machine learning as well as neural networks that can simulate human thought patterns. They can then apply their more efficient brains to issues that desperately require resolution, many of which are in STEM fields like medicine or cryptography. STEM stands for science, technology, engineering and mathematics, but a far wider range of academic disciplines fall under this description.