Artificial Intelligence: Are We Already Living With AI?
What is intelligence?
In order to understand artificial intelligence (AI), lets first look at human intelligence.
Intelligence is measured on a sliding scale. When is a human truly classed as intelligent? Is a new-born baby intelligent? It knows how to cry to get what it needs, it can suckle, burp, poo and wriggle but most of us would not class a baby as intelligent. How about a toddler, are they intelligent?
An average 2 year old can have a vocabulary of anywhere between 75 and 225 words, has taught itself how to manipulate the muscles in its body to allow it to move across a number of different terrains, pickup and move tiny objects to precise positions, solve simple puzzles and for those of us who have lived through our own children’s terrible twos they certainly know how to manipulate their parents and can set their own goals of what they want, much to the consternation of the parents.
Is this intelligence?
But if I give a toddler a complicated long division sum to solve, most of them will not have a clue what I am asking from them.
Yet computers can do this complicated calculation within a split second with ease. I am so confident the computer would have done it without an error I would use it to check my own answers. I have more faith in my computer than my own ability to perform calculations. So, can computers be classed as intelligent?
What exactly is intelligence? Let’s look at Deep Blue, the computer that beat Garry Kasparov at chess. At the time it was seen as a significant leap towards artificial intelligence. Kasparov was truly a brilliant chess player, but he was more than that, he knew how to intimidate his opponents. He would unnerve them so much that they started to doubt their own abilities and would soon start making mistakes.
However, when Kasparov played Deep Blue, this method could not work on an emotionless machine. Deep Blue could not feel intimidated and so played without doubts of its own tactics so didn’t fall into the same mistakes that Kasparov’s other opponents so often did. Not only was Deep Blue programmed to be able to predict many more possible moves than Kasparov, it was also programmed to use emotional manipulation to intimidate the Russian chess master himself.
The programmers had given Deep Blue instructions to use delays, to make the machine look like it was uncertain about which move to make. Sometimes these delays would last for several minutes and gave Kasparov the impression that he was out-thinking Deep Blue. It gave him a false sense of confidence.
In another game Kasparov tried to lure Deep Blue into a trap but Deep Blue worked out the plan but pretended to take the bait and then at a crucial moment, moved it’s queen out of reach, thwarting the attack and leaving Kasparov visibly shaken. Kasparov ended up losing the match and eventually the tournament, later saying he only lost because of his own poor playing rather than Deep Blue’s chess playing abilities.
Many would say that Deep Blue showed signs of intelligence but if I played Deep Blue at noughts and crosses, it would not know how to play unless the programmers entered all the rules and programmed in complex tactics that would allow it to win. Is that really intelligence? It is not learning for itself, it is relying on the programmers predicting all the decisions beforehand and it is unable to learn from it’s mistakes.
The success of its game playing depends entirely on the code that somebody else creates for it. Deep Blue is no more intelligent than a digital watch, it can not break free from its programming. It is a machine that was built for one purpose, playing chess, and it did that very well.
Alan Turing, the computer scientist and mathematician who cracked the German’s Enigma code in World War II, wanted to answer the question “Can computers think?” However, when he tried to quantify what thinking actually was, he realised there was no measurable precise quality that psychologists or neuroscientists could agree upon.
Instead he devised a test that would measure if a computer could trick a human into believing they were communicating with another human. This was known as the “Imitation Game”. He had not intended this test to be a measure of intelligence as such, but rather to try to understand if a computer could act in such a way as to behave like a human.
The test involved thirty judges who would each take part in ten conversations. Five of these would be with humans and five would be with machines. The judges would have a short conversation by typing into a terminal and receiving an answer through their monitor. After each conversation the judge would vote on if they thought they were communicating with a human or a machine. The test was deemed to be a pass for a machine, if more than ten judges were fooled onto thinking they were talking to a human.
Turing wrote a sample dialogue that may be produced by a machine that showed human traits. His sample dialogue went as follows:
Judge: In the first line of the sonnet which reads ‘Shall I compare thee to a summer's day', would not 'a spring day' do as well or better?
Machine: It wouldn't scan.
Judge: How about 'a winter's day'? That would scan all right.
Machine: Yes, but nobody wants to be compared to a winter's day.
Judge: Would you say Mr. Pickwick reminded you of Christmas?
Machine: In a way.
Judge: Yet Christmas is a winter's day, and I do not think Mr. Pickwick would mind the comparison.
Machine: I don't think you're serious. By a winter's day, one means a typical winter's day, rather than a special one like Christmas.
This shows a machine having a wide range of facts that it can draw from but also the ability to know how these are used in a human world, for instance a poem needs to “scan” to keep the rhythm of the poem, it also needs to understand that although Christmas is in winter in the northern hemisphere, it is not what most people think of when they use the term “a winter’s day”.
On 7th June 2014, in a contest marking the 60th anniversary of Alan Turing's death, a chatbot named Eugene Goostman passed Turing's test.
Chatbots are software programs that are designed to simulate human conversation and are often used on websites to help users solve common problems. Normally, they are limited in the conversations they can have and if they are unable to answer the question it will pass them onto a human for additional help.
Eugene Goostman was designed specifically for the Turing Test. It was programmed to communicate like a 13-year old boy from the Ukrain. As the judges did not expect a teenager who has English as a second language to have the same linguistic skills as a native speaking adult, they were far more forgiving of lapses in their communication skills.
Here is the transcript of Eugene’s conversation with the judges:
Judge: In the first line of the sonnet which reads ‘Shall I compare thee to a summer's day', would not 'a spring day' do as well or better?
Eugene Goostman: What makes you ask me this? Sound like you can't choose a right answer yourself! Rely on your intuition! :-) Maybe, let's talk about something else? What would you like to discuss?
Judge: I’d like to talk about poetry.
Eugene Goostman: Classics? I hope you aren't going to read "King Lear" or something like that to me right now :-)))
Judge: No, we can talk contemporary poetry. Do you like Patricia Lockwood's work?
Eugene Goostman: I am only 13, so I'm attending school so far.
Judge: Oh, that’s when I first read Auden. Do you have a favourite poem?
Eugene Goostman: No, I haven't a best-liked poem! How could you imagine such a trash! Did I forget it or you really haven't told me about the place you are from?
Judge: Does it matter?
Eugene Goostman: Maybe. I think *you* know the answer. Could you tell me what are you? I mean your profession.
A very different conversation than Alan Turing had imagined, and some would say a surprising winner of the Turing test.
Rather than a continuing stream of thought with each statement building on what previous people have said and adding to it with their own conclusions which they are willing to argue, Eugene redirects the first statement in an attempt to move the conversation away from a difficult subject.
Also, Eugene misunderstood the phrase “Patricia Lockwood's work” taking it out of context and assuming they were now talking about jobs. If the judges had not been told they were talking to a thirteen year old boy who did not speak English as their main language, they may not have been so forgiving with these points, which shows how much we can be swayed by a believable back story.
Using language in a believable way is something that computers are still struggling with, partly because they have no real understanding of the real world that we humans exist in and completely take for granted.
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Can Artificial Intelligence Write Literature?
Botnik Studios is a company that creates “machine entertainment” and use computers to analyse and write text. In 2018 they uploaded all the Harry Potter books, so their computer could analyse the language written, in an attempt to write an original Harry Potter story.
What was produced, entitled “Harry Potter and the portrait that looked like a large pile of ash”, successfully managed to follow many rules from the original Harry Potter books but it spectacularly failed in other areas often with unintentionally comedic results. The three main characters are identified correctly being Harry, Ron and Hermione along with their enemies of the Death Eaters and Voldemort and a few other characters thrown in for good measure. However, it fell far short from something that was believable. It has failed to understand the emotions that are used, misrepresenting the characters and making them act in an unbelievable way which is out of character with what we know from the original books.
Here is a exert where Harry, Ron and Hermione have managed to sneak into a secret Death Eater meeting:
Harry, Ron and Hermione quietly stood behind a circle of Death Eaters, who looked bad.
“I think it’s okay if you like me,” said the Death Eater.
“Thank you very much,” replied the other. The first Death Eater confidently leaned forward to plant a kiss on his cheek.
“Oh! Well done!” said the second as his friend stepped back again. All the other Death Eaters clapped politely.
For any of you who know the Harry Potter books or films will recognise this is not the sort of behaviour you would expect from Harry’s mortal enemies who terrorise and torture humans for fun.
In another scene, Harry tears out his own eyes and throws them into the forest which even the story admits was an overreaction and during the scene in the great hall, as all good Harry Potters books have once the task has been won, it is described as having mountains of mice exploding and long pumpkins falling out of poor Mrs McGonagall.
It seems the rules of what is reasonable is beyond the current understanding of the program. Thankfully, this literary masterpiece has been made into an animation which you can view here:
Is Artificial Intelligence Here?
So, are we ever going to really be able to produce machines which can be classed as intelligent? Is Artificial intelligence (AI), also known as machine learning, going to be in our life-time?
As you have seen, intelligence is difficult to define however most AI scientists have agreed that for a computer to be called intelligent is should be able to learn without being encoded with commands. It needs to teach itself how to reach a goal using the most efficient solution. So rather than Deep Blue that was programmed by humans to beat Kasparov, AI will teach itself how to play chess. It will have a goal and will be able to find its own solution without any input from the programmers.
How does it learn? It learns by trial and error and repetition. Lots of repetition. It tests the system and each time it fails it learns a little bit more about what works and what doesn’t work. Once it finds one solution, it tries again, attempting other options to find another more efficient solutions until eventually it finds the best solution possible.
Watch this video to see how programmers created a simulated hide and seek game with only a few rules about the physical world these figures found themselves in and a simple goal for each team. The red team needs to find the blue team members and catch sight of them and the blue team have to try and evade being seen for as long as possible. The video shows the way in which the program learnt the rules, perfected the rules and then pushed the limits of the program further than the original programmers had envisioned to create more efficient solutions.
So does that mean AI is already here?
That is a tricky question, some experts say yes, others say no. It seems pockets of artificial intelligence certainly exists, but they are created to solve a single goal and are referred to as “Narrow AI”. True intelligence would require a machine to be able to set its own goals, much like a toddler can decide what it wants. AI that has an ambition to do something without being told of the goals it is working towards is called “General AI”. That would require the emotion of desire and that has not yet been discovered. Even though experts can’t agree on when that will happen, they all agree that General AI will happen at some point. Machines will develop their own goals and then find the most efficient solution to get there.
Narrow AI can outperform humans at the specific goal it has been set such as predicting financial market trends, driverless cars etc but General AI would outperform humans at nearly every task it attempts.
Maybe a better question to ask is, what will become of humans if we manage to create a machine that can set its own goals and has an intelligence that is superior to our own? How will we contain it, surly everything we can conceive of using to contain and control General AI, it would already have predicted and developed a method to break out.
Many AI experts at the 2015 Puerto Rico Conference predict General AI will be here this century. Therefore, as creating safeguards may take many decades, safety research is being developed now alongside the development of AI itself. Thankfully this is an area that many researchers and experts are concerned about and are activity currently working on, so when General AI is launched into the world, we are prepared.