Artificial intelligence (AI) is disturbing the work force. But can AI ultimately do the job better than humans?
IBM’s Watson is now helping with cancer research and tax returns, among other things. And AlphaGo, a computer program designed to play the ancient board game “Go”, beat Lee Sedol, one of the best players in the world, in a 4 to 1 landslide.
Despite these advancements, computers still have limitations. For example, even though AlphaGo leaned through deep learning to make moves that increased its chances of winning, its programmers didn’t know why the system made certain moves. Much of the information was distributed across large swaths of the computer’s neural network, which made it impossible to summarize why AlphaGo made a particular move.
Until this summarizing is possible, managers and CEOs who are experts in their various fields won’t trust a computer that can’t offer a reason a creative, yet risky, move is the best one to make.
Further, computers can’t always fill the gaps in our lack of understanding of how things work. The makers of phone cases dropped many encased smartphones on hard surfaces before selling their products. They didn’t just rely on computer simulations. Human theories will always need empirical measurements.
Given these limitations, my colleague Lee Spector and I have proposed a solution: a new human-computer interface that allows humans and computers to work together to counter each other’s weaknesses. Computers, for example, could prevent humans from falling prey to cognitive biases. And humans could make up for computers’ creative deficiencies. For such an approach to work, the interface needs to be both human and computer friendly.
We shouldn’t worry, therefore, about whether computers are going to overtake humans; instead, we should focus on designing a system that allows humans and computers to collaborate easily, so that each partner can build on the other’s strengths and counter the other’s weaknesses.
In some ways, this is already happening. After losing the first three “Go” games to AlphaGo, and witnessing the computer system make novel moves that players hadn’t seen before, Sedol made a highly creative move of his own and ended up winning the game.
By Tony McCaffrey
Tony McCaffrey is the chief technology officer of Innovation Accelerator.