Intelligence has always been an amazing topic for conversations: whether it’s about discussing what it is precisely or other people’s lack of it, it never fails to provide food for thought. Now with the rise of artificial intelligence, we have one more topic to debate, make predictions about and feel excited (or threatened) by. So far we have taught machines to draw, drive cars, write poems, beat humans playing Go, and even chat with us. AI is obviously getting smarter, but is it already smarter than us?
In 2002, Mitchell Kapor, co-founder of the Electronic Frontier Foundation and the first chair at Mozilla, and Ray Kurzweil, author, computer scientist, inventor and futurist who works for Google, established a $20,000 wager. The bet was over whether a computer would pass the Turing Test by 2029. They called it “A Long Bet.” Kapor bet against a computer passing the Turing Test by 2029, while Kurzweil believed it would happen. Has the bet been resolved in 2018? Let’s take a deeper look.
AI: The Origins
Let’s go all the way back to ancient history. Just think about all the myths and stories about artificial beings who get their consciousness by a divine power. The seeds of AI were planted by philosophers who tried to describe the process of human thinking as the mechanical manipulation of symbols. In 1308, the Catalan poet and theologian Ramon Llull published Ars generalis ultima (The Ultimate General Art), which perfected his method of using paper-based mechanical means to create new knowledge from combination of concepts. Following that in 1666, mathematician and philosopher Gottfried Leibniz published On the Combinatorial Art , which proposed an alphabet of human thought and argued that all ideas are nothing but combinations of a relatively small number of simple concepts. All of this culminated with the invention of the programmable digital computer in the 1940s. So scientists had the base to start discussing the possibility of building an electronic brain.
The term “artificial intelligence” was coined in a proposal for a “2 month, 10 man study of artificial intelligence” in August 1955 in Dartmouth College. The workshop involved John McCarthy (Dartmouth College), Marvin Minsky (Harvard University), Claude Shannon (Bell Telephone Laboratories) and Nathaniel Rochester (IBM). The workshop took place in 1956 and is considered the official birth of the new fied. In 1959 Arthur Samuel coined the term “machine learning” when he was trying to program a computer to learn to play a better game of checkers better than the person who wrote the program.
AI: The Test
In the far 1950, Alan Turing developed an actual test, which would help determine a machine’s ability to exhibit intelligent behavior compared to that of a human. The test involved a human evaluator who would judge natural language conversations between a human and a machine designed to generate human-like responses. The judge will be aware that a machine is involved. The conversation would be limited to a text-only channels such as a computer keyboard and screen. If the evaluator cannot reliably tell the machine from the human, the computer passes the test. In this test there are no right and wrong answers- just answers close to human speech.
The test has been introduced in Turing’s paper “Computing Machinery and Intelligence.” The first sentence states: “I propose to consider the question, ‘Can machines think?’” But thinking is too difficult to define so Turing replaces this question with another: “”Are there imaginable digital computers which would do well in the imitation game?” Turing believed that the new question can be answered.
AI: The Bet
In 2014 a computer successfully convinced a panel of judges that it was human. Thus it passed the Turing Test. The test was held by the University of Reading and the organization announced that for the first time a computer passed. The computer’s name was Eugene Goostman and it tricked the judges 33% of the time. But did it really helped Kapoor win the bet so that Kurzweil owes him $20,000?
Yes, Eugene Goostman passed the Turing Test and fooled the judges more than 30% of the time in their five-minute conversations. No, Kurzweil doesn’t owe Kapoor $20,000. Yet. The bet had explicit rules and the experiment at the University of Reading didn’t meet all of the listed criteria. For example, to help Kapoor win, a computer needs to have a conversation of at least eight hours, which means the computer will need to convince two out of three judges.
But why should Kapoor be worried?
Machines are getting better at everything we are teaching them to be. What makes machines smarter? Seth Shostak, the former director of the Search for Extraterrestrial Intelligence Institute (SETI), believes that we can build computers that can beat humans at specific tasks (like winning the game Go). The machines can’t do everything better, but he thinks that eventually we will design AI that is as complex and intelligent as a human brain.
“But the assumption is that that will happen in this century. And if it does happen, the first thing you ask that computer is: Design something smarter than you are,” says Shostak. “Very quickly, you have a machine that’s smarter than a human. And within 20 years, thanks to this improvement in technology, you have one computer that’s smarter than all humans put together.”
AI is learning quickly. Just one recent example is The AI Hacker: in 2016 the Darpa Cyber Grand Challenge hosted the first hacking contest between a pit bot against bot. Designed by seven teams of security researchers from across academia and industry, the bots were asked to play offense and defense, fixing security holes in their own machines while exploiting holes in the machines of others.
Not to mention the infamous story which the more dramatic amongst us (or the Black Mirror fans) saw as the beginning of the reign of AI over humans: that time when Facebook had to shut down two chatbots, just because no one understood what they were talking about. The researchers didn’t seem to worried about it. “There was no reward to sticking to English language,” Dhruv Batra, Facebook researcher, told FastCo. “Agents will drift off understandable language and invent codewords for themselves.”
In the meantime Google is feeding its AI with unpublished books and, in return, the AI is composing mournful poems. And if you’ve played with the AI-powered tool that Google released in 2016, you’ve actually helped it learn how to draw. The program is called Sketch-RNN and it draws pretty well…for a machine. The drawings are basic, but they are not what is important. The method used to create them can be quite useful. It is paving the way for AI programs which can be used as creative ads for designers, architects and artists.
We, on the other hand, have focused on the image recognition abilities of AI. A while ago we asked you to play in the Clash of Tags. Players were presented with two sets of images for a given text tag and had to vote which set was describing the image better. It turned out that machines were almost as good as humans. So for now, the result is even. But the battle is not over.
Human: Intelligence?
So what is intelligence? According to Einstein, “The true sign of intelligence is not knowledge but imagination” Socrates said, “I know that I am intelligent, because I know that I know nothing.” Philosophers got created in the ancient search finding the true measure of intelligence and meaning. Today neuroscientists try to answer questions about intelligence from a scientific perspective. It is widely accepted that there are different types of intelligence—analytic, linguistic, emotional, to name a few—but psychologists and neuroscientists disagree over whether these intelligences are linked or whether they exist independently from one another.
In the meantime, computers will be getting smarter. Yes, they can process certain kinds of information much faster than any of us can. Computers learn more quickly and narrow complex choices to the most optimal ones. They have better memories and can analyze huge amount of information. Computers can calculate and perform tasks without stopping. On the other hand, humans are better at making decisions and solving problems. Humans are capable of experiencing life. We have creativity, imagination and inspiration. Computers replicate tasks, but they can’t create. Yet.