Saturday, 23 January 2016

Future of Intelligence – How do we define Intelligence anyway?

In December 2015,
 at the Nobel Prize gatherings in Gothenburg, Sweden, the theme was the future of intelligence.  Ray Kurzweil was the keynote speaker – Ray is somebody I admire for his many wonderful qualities and his ability to project the technological progress in a way that sounds credible but frightens many people for what it portends.  In his projections, Ray focuses on different technologies that are changing our ability to see and understand large sets of information and create computer systems that might reach and then quickly surpass human level thinking.

Personally, I have some difficulty in understanding what intelligence is – what is the definition?  It is always good to know what one is talking about.  I did some legwork.  The results are as follows:  Intelligence is…

Collins Dictionary:  The capacity for understanding;
                               Ability to perceive and comprehend meaning
Oxford Dictionary:  The faculty of reasoning, knowing and thinking as distinct from feeling
From the Web:       A person’s cognitive abilities to learn.
                               Is an estimate of the quality that we attribute to the decision- making and abstract thinking of people around us.
                               Refers to one’s cognitive abilities which include memory, comprehension, understanding, reasoning, abstract thought.

Wiki says:  Human intelligence is the intellectual capacity of humans, which is characterized by perception, consciousnessself-awareness, and volition. Through their intelligence, humans possess the cognitive abilities to learnform conceptsunderstand, apply logic, and reason, including the capacities to recognize patterns, comprehend ideas, planproblem solvemake decisionsretain information, and use language to communicate. Intelligence enables humans to experience and think.

It became clear to me that intelligence is not something that can be measured by the IQ tests. The well-known Flynn effect (paradox) about the drastic increase of IQ score in the 20th century has its own rationalisations and make interesting reading (

Without getting too bogged down in defining intelligence, may be we should come back to the Nobel Week Dialog and what Ray had to say about the accelerating increase in technological progress.  I also notice that AI used to mean artificial intelligence but it is frequently used to mean accelerating intelligence – I call it the Kurzweil effect!

Ray’s keynote speech may be found at
and is very enjoyable to listen to. Particular attention should be given to the difference between linear thinking and exponential thinking.  Humans are used to linear extrapolations and that is what our common sense dictates in most circumstances.  I have some beautiful examples of exponential change in my talk on population growth
It is worth having a look at those.

Ray Kurzweil was interested in the accelerating growth of technology and gave examples of transistor price, transistor cycle time, DNA sequencing costs, growth in supercomputer power, transistor per chip and many more.  It is amazing that the smart phone in your pocket is a billion times more powerful than the computer I had in my nuclear physics lab in Canada in 1966. 
All this points to the way big data can be handled and made sense of.  This is what the human brain is so capable of doing.  With accelerating growth – I like the phrase exponential growth more – computers are getting more versatile and capabilities like pattern recognition which were impossible a few decades ago are well within the reach of super-computers.  We are not at a stage that computers can match human intelligence fully or even partially but there are signs that progress is in the correct direction.  The main bottleneck is that we still do not understand properly how the brain processes information and what gives rise to abstract thinking – where does intelligence lie in the brain?

Artificial Intelligence (AI) purports to match human intelligence sometime in the near future and then surpass it very soon after that.  Actually, it is better to think AI at three different level  and I quote
“1) Artificial Narrow Intelligence (ANI): Sometimes referred to as Weak AIArtificial Narrow Intelligence is AI that specializes in one area. There’s AI that can beat the world chess champion in chess, but that’s the only thing it does. Ask it to figure out a better way to store data on a hard drive, and it’ll look at you blankly.
2) Artificial General Intelligence (AGI): Sometimes 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. Creating AGI is a much harder task than creating ANI, and we’re yet to do it. Professor Linda Gottfredson describes intelligence as “a very general mental capability that, among other things, involves the ability to reason, plan, solve problems, think abstractly, comprehend complex ideas, learn quickly, and learn from experience.” AGI would be able to do all of those things as easily as you can
3) 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. ASI is the reason the topic of AI is such a spicy meatball.”

There is still a long way to go to reach ASI but with accelerating growth in technology – who knows?  There are many apprehensions, worries and expectations generated by the ever quickly developing technologies.  Ray Kurzweil neatly summarized the task at hand and again I reproduce his list of topics for discussion:
·         When will artificial intelligence exceed human intelligence?
·         Are fears of super-intelligent systems justified?
·         Does our developing relationship with technology change our brains?
·         How well do we understand the basis of human intelligence?
·         What are the economic consequences of increasingly intelligent systems?
·         What role will creativity have in the future?
·         Who will benefit and who will lose out?
·         What is the link between technology, education and inequality?
·         What will humans do when robots take over even more of our roles?
·         How can society best prepare for the changes ahead?
·         What should we learn in the future?
·         How will learning change in the decades ahead?

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