The media sphere is often dominated by articles and features warning the public that eventually, all of our jobs will be replaced by artificial intelligence. Is this actually the case?

Author Bernard Marr has written an interesting piece for Forbes about how it will not be a matter of “either, or”, rather than a matter of humans and robots working together.

When talking about the future, Marr refers to it as “shades of grey”, and urges the people to rather focus on finding a merger between man and machine, than worrying about who will rule over whom.

Because after all, when working together, it will allow us to bring out the best in both. Marr refers to the time IBM’s Deep Blue beat the grand chess master in a game of chess, highlighting a piece from the book, The Signal and the Noise: 

“In 2005, the online chess-playing site hosted what it called a ―freestyle chess tournament in which anyone could compete in teams with other players or computers. […] The winner was revealed to be not a grandmaster with a state-of-the-art PC but a pair of amateur American chess players using three computers at the same time. […] Weak human + machine + better process was superior to a strong computer alone and, more remarkably, superior to a strong human + machine + inferior process.”

This case study explains Marr’s message – that separately, robots and humans are not as strong as when working together. Humans are certainly superior when it comes to creative-and abstract thinking, whereas computers are very strong in areas that require detailed and complex analysis and computations.

“But combine the two and you suddenly have a new powerhouse of computing to solve difficult problems”, Marr writes.

Human Computation:

Marr refers to the journal Science, researchers from Cornell University and the Human Computation Institute presented the idea of “human computation”:

“In short, human computation is what’s known colloquially as “crowd sourcing;” a computational or analytical task is sent out in tiny micro-tasks to many different individuals, and the data are then stitched back together by a computer. The results are often more efficient and accurate than either humans or computers working alone could produce”, Marr explains.

If you are a frequent user of the Internet you have most likely come across Google’s reCAPTCHA security feature, which is one of these examples of human computation. Whenever you are asked to enter numbers from a photo, which computers can’t read, Google then applies these answers to gather knowledge from the users and improving their maps-and street-view functions.

Marr refers to another example of the website that enables users to play a game to help analyse data, which the lead-researcher believes will eventually reduce tome to treatment discovery from decades, to just a few years.

“As computers are becoming learning machines rather than simply doing machines, the fear is that they will replace humans. But it seems much more likely to me that these learning machines will help humans adapt to rapidly changing problems, environments, and systems, and we humans will continue to provide the creativity and ingenuity that the computers can’t match”, Marr writes.

Researchers have expressed the potential of AI to span from solving some of the world’s most pressing and complex issues, such as climate change, disease, world peace, etc.

Marr now believes that the question is no longer who will win, but rather how we can work together to tackle some of the world’s biggest issues, in new and innovative ways.

This article was originally published at:

For the latest news and conversations about AI in business, follow us on Twitterjoin our community onLinkedIn and like us on Facebook.