John Lund—Getty Images/Blend Images
By Lance Whitney
September 29, 2017

Who’s smarter — you, or the computer or mobile device on which you’re reading this article? The answer is increasingly complex, and depends on definitions in flux. Computers are certainly more adept at solving quandaries that benefit from their unique skillset, but humans hold the edge on tasks that machines simply can’t perform. Not yet, anyway.

Computers can take in and process certain kinds of information much faster than we can. They can swirl that data around in their “brains,” made of processors, and perform calculations to conjure multiple scenarios at superhuman speeds. For example, the best chess-trained computers can at this point strategize many moves ahead, problem-solving far more deftly than can the best chess-playing humans. Computers learn much more quickly, too, narrowing complex choices to the most optimal ones. Yes, humans also learn from mistakes, but when it comes to tackling the kinds of puzzles computers excel at, we’re far more fallible.

Computers enjoy other advantages over people. They have better memories, so they can be fed a large amount of information, and can tap into all of it almost instantaneously. Computers don’t require sleep the way humans do, so they can calculate, analyze and perform tasks tirelessly and round the clock. Notwithstanding bugs or susceptibility to power blackouts, computers are simply more accurate at pulling off a broadening range of high-value functions than we are. They’re not affected or influenced by emotions, feelings, wants, needs and other factors that often cloud the judgement and intelligence of us mere mortals.

On the other hand, humans are still superior to computers in many ways. We perform tasks, make decisions, and solve problems based not just on our intelligence but on our massively parallel processing wetware — in abstract, what we like to call our instincts, our common sense, and perhaps most importantly, our life experiences. Computers can be programmed with vast libraries of information, but they can’t experience life the way we do. Humans possess traits we sometimes refer to (again, in the abstract) as creativity, imagination and inspiration. A person can write a poem, compose and play music, sing a song, create a painting or dream up a new invention. Computers can be programmed to replicate some of those tasks, but they don’t possess the innate ability to create the way humans do.

What do experts in artificial intelligence make of all this? Let’s start by defining what we mean by “smarter” or “more intelligent.” Intelligence has two components, says Professor Shlomo Maital, Senior Research Fellow for the S. Neaman Institute at Technion – Israel Institute of Technology. One is the ability to learn, the other is the ability to solve problems. And in those areas, computers can be smarter than humans.

“Today, computers can learn faster than humans, e.g., (IBM’s) Watson can read and remember all the research on cancer, no human could,” says Maital. “With deep learning, Watson can also solve a problem, for example, how to treat a rare form of cancer — and it has done so. So in that sense, computers can be smarter than humans.”

Maital points to another example of computer intelligence in his article “Will robots soon be smarter than humans?” On February 10, 1996, IBM’s Deep Blue computer defeated world champion Garry Kasparov in the first of a six-game series, going on to eventually win the series a year later — the first computer ever to do so. Was Deep Blue intelligent? Yes and no, says Maital.

“No, because it was simply able to calculate an enormous number of possible chess moves in a fraction of a second,” writes Maital. “Speed is not intelligence. But, yes, because it was able to analyze these chess moves and pick the best one sufficiently well to beat Kasparov.”

Computers don’t suffer from important limitations that plague human beings. They’re not restricted by biology, they don’t get tired, they can crunch numbers for long hours, and they’re exceptionally smart while doing repetitive mathematical tasks, according to Satya Mallick from LearnOpenCV.com and the founder of Big Vision LLC.

“From an A.I. perspective, we can now train computers to perform better than humans in many tasks, for instance some visual recognition tasks,” says Mallick. “These tasks have one thing in common: there is a vast amount of data we can gather to solve these tasks and/or they are repetitive tasks. Any repetitive task that creates a lot of data will eventually be learned by computers.”

But experts agree that humans still tower over computers in general intelligence, creativity, and a common-sense knowledge or understanding of the world.

“Computers can outperform humans on certain specialized tasks, such as playing [the game] go or chess, but no computer program today can match human general intelligence,” says Murray Shanahan, Professor of Cognitive Robotics for the Department of Computing at Imperial College in London. “Humans learn to achieve many different types of goals in a huge variety of environments. We don’t yet know how to endow computers with the kind of common sense understanding of the everyday world that underpins human general intelligence, although I’m sure we will succeed in doing this one day.”

People possess creativity and intuition, both qualities that computer code doesn’t have, but more importantly may never have, according to John Grohol, founder & CEO of PsychCentral.com.

“We can, for instance, have computers mimic creativity through subsuming works of art into a database, and then creating a new work of ‘art’ from some amalgamation,” says Grohol. “But is that the same as human creativity, or is the computer’s code simply following an instruction set? I’d argue it’s very much just the latter, which makes the computer far inferior when it comes to that component of intelligence.”

Computers have no concept of meaning the way a human does, says Jana Eggers, CEO of artificial intelligence company Nara Logics. “Even if the computer can determine an emotion, it does not understand what experiencing an emotion means,” according to Eggers. “Will they? It is possible, but not clear how that will work with the current forms of computing.”

But what if we roll the clock far enough ahead? Experts generally agree that the computers of tomorrow will possess some of the traits that today are seen as uniquely human.

“The human brain has 86 billion neurons (nerve cells), all interconnected,” says Maital. “Computer neural networks have far, far fewer ‘cells.’ But one day such neural networks will reach the complexity and sophistication of the brain.”

All of this is likely coming sooner than later, believes Grohol. “Once we’ve cracked the neurocode that runs our brains, I believe we could replicate that structure and function artificially, so we could truly create artificial life with artificial intelligence,” he says. “I could definitely see that happening within the next century.

Some people, such as computer scientist Ray Kurzweil and Tesla co-founder Elon Musk, have warned against the potential dangers of A.I., envisioning a Terminator-type future in which machines have run amok. We certainly need to keep a handle on artificial intelligence so that we control the machines rather than the other way around. But the question seems less one of Hollywood-style “evil” machines rising up to exterminate puny humans, than of alignment: how do we ensure that machine intelligence that may eventually be utterly beyond our comprehension remains fully aligned with our own?

Some of that’s rethinking how we approach these questions. Rather than obsessing over who’s smarter or irrationally fearing the technology, we need to remember that computers and machines are designed to improve our lives, just as IBM’s Watson computer is helping us in the fight against deadly diseases. The trick, as computers become better and better at these and any number of other tasks, is ensuring that “helping us” remains their prime directive.

“The important thing to keep in mind is that it is not man versus machine,” says Mallick. “It is not a competition. It is a collaboration.”

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