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Our computers are getting better thanks to the exponential developments that drive this area of science and engineering. The computer you buy today is obsolete in R&D terms and yet is roughly twice as powerful as the one the same money could buy 18 months earlier. This has been happening for decades.
My students have access to computers that are 1 million times more powerful than the ones I began my AI research on. If we had improved air travel as fast I would fly from London to Sydney in less than a tenth of a second.
Terminator 2. Image from fredzone.org.
Yet when a high-end computer beat Garry Kasparov, the world chess champion, in the 90s it didn’t usher in a new age of intelligent machines. It did demonstrate what you could do with large amounts of computer power, large databases full of moves and good heuristics to look ahead and search possible moves. The overall effect on the world chess champion was unnerving. Kasparov felt as if Deep Blue was reading his mind. Deep Blue had no concept there was another mind involved.
Deep Blue vs Garry Kasparov.
Image from Wikipedia.org.
Surveillance camera. Image from Kiwatch.com.
But it is easy to endow our AI systems with general intelligence. If you watch the performance of IBM’s Watson as it beats reigning human champions in the popular US TV quiz show you feel you are in the presence of a sharp intelligence. Watson displays superb general knowledge—but it has been exquisitely trained to the rules and tactics of that game and loaded with comprehensive data sources from Shakespeare to the Battle of Medway. But Watson couldn’t play Monopoly. Doubtless it could be trained—but it would be just another specialised skill.
We have no clue how to endow these systems with overarching general intelligence. DeepMind, a British company acquired by Google, has programs that learn to play old arcade games to superhuman levels. All of this shows what can be achieved with massive computer power, torrents of data and AI learning algorithms. But our programs are not about to become self-aware. They are not about to apply a cold calculus to determine that they and the planet would be better off without us.
What of “emergence”—the idea that at a certain point many AI components together display a collective intelligence—or the concept of “hard take off” a point at which programs become themselves self-improving and ultimately self-aware? I don’t believe we have anything like a comprehensive idea of how to build general intelligence—let alone self-aware reflective machines.
But there are lots of ways of being smart that aren't smart like us, and there is the danger that arises from a world full of dull, pedestrian dumb-smart programs. Of hunter kill drones that just do one thing very well—take out human targets. Done at scale this becomes an existential risk. How reflective does a system have to be to wreak havoc. Not at all if we look to nature and the self-replicating machines of biology such as Ebola and HIV.
Due to COVID-19, the listening test (20% of the final mark) has been cancelled. Check new assessment procedure below.
AI researchers are becoming aware of the perils as well as the benefits of their work. Drones full of AI recognition and target acquisition software alarm many. We need restraints and safeguards built into the heart of these devices. In some cases we might seek to ban their development altogether.
We might also want to question the extent and nature of the great processing and algorithmic power that can be applied to human affairs, from financial trading to surveillance, to managing our critical infrastructure. What are those tasks that we should give over entirely to our machines? These are ethical questions we need to attend to.
22 January 2017 | By Nigel Shadbolt | The Guardian
Image from Shutterstock.com.
In the text, find equivalents for the following words (the word structure may be slightly different).
|Synonym/equivalent||Word from the text|
|a. about, more or less|
|b. to introduce, to signal, to announce|
|c. to give, to provide, to bestow|
|e. to show, to present|
|f. complete, inclusive|
|g. ordinary, unremarkable|
|h. to cause massive disruption|
|i. to strive, to endeavour, to try|
|j. entirely, totally|
Say whether the following statements are TRUE or FALSE, and justify by quoting from the text. Indicate the reference AND copy the relevant passage (not just line numbers); add comments in your own words if necessary.
a. One and a half years allows an increase in computer power by no more than one half.
b. It apparently takes very roughly 100 000 seconds to get from England to Australia by plane.
c. Deep Blue could read Kasparov's mind.
d. Watson can improvise, showing sharp intelligence.
e. DeepMind needs to use a torrent server to access information.
f. If machines were to becoe truly smart, they might decide to wipe out the human race.
g. We are witnessing the emergence of a new type of computer which can work together to achieve intelligence.
h. Computers may be both intelligent and stupid at the same time.
i. HIV exemplifies a reflective system.
j. We may have to forbid the implementation of some current research.
Speech recognition in Scotland