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The implications of artificial intelligence (ai) on future jobs, questioning whether it represents progress or redundancy. The author discusses the definition of ai, its current capabilities, and its impact on various industries such as manufacturing, marketing, medical professions, and even the arts. The document also touches upon the ethical and security concerns related to ai.
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In this project I will explore how the use of AI (Artificial Intelligence) will affect our jobs in the future. I think this is important, as we are possibly on the fringes of another revolution. We may choose to accept this change. We may not. But most importantly, is this progress, or our slide into redundancy?
Firstly I will define Artificial Intelligence. This is harder than it sounds, as intelligence itself has quite a hazy definition. The Oxford Dictionary defines AI as ‘The theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision making, and translation between languages .’ But this means that any artificial beings, including^1 statistical generators such as Google Translate are intelligent, as they have speech recognition software, translate between languages and make decisions on which word fits most with the input. Most would still agree that google translate is not intelligent, merely a program drawing matched words from a database. This then begs the question, what is intelligent?
For those who work in research of AI, a joke on the definition follows that ‘AI is anything a computer cannot yet do.’ This could be true though, as in the 1950s, it was thought that once we were able to create a computer which could beat the best human at chess, everything else would follow on easily. This was achieved in the 1970s, by IBM’s computer, Deep Blue. In today’s age however, this is not seen as intelligent, as Deep Blue, though impressive, was again a very large database of moves. It didn’t show any signs of a very human trait which can be used to distinguish between people and androids: adaptability. That is beginning to change. Recently, on 9th March 2016, Google Deepmind’s AlphaGo computer beat Lee Se Dol at another type of board game, Go. AlphaGo used Deep Learning, a type of complex programming, which made it capable of improving. It played itself thousand of times, discovering and developing it’s own strategies before the game. AlphaGo also improved throughout the match, adapting to it’s situation. I think that is what makes a machine truly intelligent, adaptability, even if within a specialised activity.
Research into AI has really taken off in the last few years, and growth is estimated to speed up more and more. We are beginning to develop computer systems that can actually be described as intelligent. Up to this point we have programmed machines, giving them instructions. A piece of hardware just filing through functions can never be described as intelligent, but now we have robots driving, producing creative texts and winning complex games like go. Industrial Perception has created a robot who
(^1) The Oxford Dictionary Website: http://www.oxforddictionaries.com/definition/english/artificial intelligence#artificial intelligence__
can stack shelves, a seemingly simple task, but hard for basic computers there may be different sizes, and not already sorted pre stacking. With the use of AI the machine is able to work out how to stack items of strange shapes, pick them up from funny angles and place them correctly. Although this process is a slow one, it is set to be able to stack boxes at a speed of 1 second per box, compared to a sluggish, human 6 seconds per box. This is true of many machines, and all this technology is a result of creating neural networks in computers, similar to the setup of our own brain. AI as intelligent as a human is predicted to be around by 2029.
Another important part of AI is the use of big data. Big data is the ever growing large amounts of data collected across all stretches of life, that can be used by computers to predict things, for example, film preferences. Programs look at similarities between the data and the user’s liked films so far, as, if you liked a certain combination of films, there is bound to be someone else out there who has also liked that combination of films. The computer will see what else that user has liked, and recommend it to you. This sort of process can make a real difference in the real world, for example, business, where big data lets companies get into the minds of consumers.
The concept of AI has only been around for half a century or so, and therefore not many jobs have fallen to intelligent machines yet, but we are on the fringes of another industrial revolution. At the moment AI has taken over a few jobs, but only on a very small scale, for example some journalism, particularly sport is written by AI, though in 50 years time 90% of all articles written will have been penned by a robot. Also beginning to be filled with computers are jobs such as online marketing, which can predict using big data what will most attract a consumer about a product, medical professions, both in diagnostics and surgery, as AI is simply more accurate and even factories,which are already very automated are set to have further job loss. This is still only the tip of the iceberg it is estimated that 50% of jobs we will be doing in 20 years time haven’t been invented yet, but it is clear that no longer is it just the repetitive, monotonous jobs at risk, as machines are enabled to learn and think for themselves, fostering creativity as well, how long will it be before even the arts fall to the siege of AI?
There is much support for AI. Although it is accepted that jobs will be lost, there is much evidence to suggest that new jobs that we cannot even imagine now will be created at the start of the 20th century who could have predicted the swathes of people to be working in the IT industry (Google’s last earnings report counted 55, full time employees ).^2 Despite massive automation of millions of jobs, more Americans had jobs at the end of each decade up through the end of the 20th
(^2) https://www.quora.com/How many employees does Google have
Freidman, upon seeing a government construction jobs program where no machinery was present, only spades and other manual work tools: “So then, why not give the workers spoons instead of shovels?” , and not be scared of advancing^6 society.
(^6) Martin Ford’s Book, The Rise of the Robots