AS THE BOUNDARY BETWEEN AUTOMATED AND HUMAN DECISION-MAKING NARROWS, THE FUTURE OF WORK AND INDUSTRY IS BEING REDEFINED.
The concept of artificial or "human-adjacent" intelligence and the dangers it poses has consumed our collective imagination since Mary Shelley published Frankenstein in 1818. While artificial intelligence (AI) raises host of questions with ethical, practical as well as business implications, it is important to recognize that true artificial intelligence does not currently exist and likely won't for a long time.
Computers have successfully navigated the Turing Test, convincing users they are interacting with a human rather than a machine (although poetry by algorithm so far has failed to stir the soul), however, computer programs have yet to reach the point where decisions can be made without some form of human guidance. It can be argued, then, that augmented intelligence is a more apt description for the combination of data science, machine learning and automation that together comprise AI.
AI could and eventually will be used to create new kinds of experiences, but current applications are focused primarily on improving efficiency. Already automation has "optimized" hundreds of thousands of jobs across almost every imaginable sector, from manufacturing to customer service and even journalism.
Considerable coverage has been given to the impact self-driving trucks could have on the nation's 1.7 million long haul truckers. In the near term, however, the complexities of the road mean that technological advances will be more about supporting drivers with augmented intelligence than replacing them. Construction zones can flummox even the most advanced computer system, which is why autonomous vehicle pioneers Google and Delphi have engineers in the car ready to take control of the wheel at any moment. As the boundary between automated and human decision-making narrows, the future of work and industry is being redefined.
Six years ago, Eli Pariser gave one the most popular TED talks ever on the threat of what he dubbed "the filter bubble": Two people can type identical search terms in Google, but based on their unique individual search histories, different sets of links will be generated. Our digital past is prologue for our digital futures.
As shocking at that was at the time, the bubbles have become stronger as more and more of our data are collected and algorithmically linked. It is not just web browsing histories any more, but data gathered from smart phones and watches and increasingly a raft of IoT-enabled devices. From a business perspective, this collective "virtual footprint" can have significant positive value for customizing digital experiences. Yet is also raises serious questions: Should people be presented only with options that reinforce bias? Has data mining and aggregation made it more difficult for people to bridge political, social and economic divides? What happens to the serendipity of discovery? And what about privacy?
The most important part of the automation and optimization story, however, turns out to be not technology, but rather human potential. As robots and algorithms take over countless mundane and repetitive tasks, entrepreneurs with access to vast amounts of data, cheap cloud computing and AI-enhanced manufacturing will create new products and services—new sectors and industries—that we can scarcely imagine today.
There is also no question that the quick pace of innovation in automation and machine learning has a dark side. This is profoundly disruptive technology, so it is critical to be both thoughtful and proactive in making sure that individuals, communities and, indeed, society at large are helped rather than harmed by a transformation affecting all our lives in ways both obvious and subtle.
The power of artificial—or augmented—intelligence is not about replacing humans, but about unleashing their creativity.
by Rachelle Hampton, Medill School of Journalism