Machine learning allows software to mimic and then perform tasks that were until very recently carried out exclusively by humans. Simply put, software can now substitute for workers’ knowledge to a level where many jobs can be done as well — or even better — by software. This reality makes a conversation about when software will acquire consciousness somewhat superfluous.
When you combine the explosion in competency of machine learning with a continued development of hardware that mimics human action (think robots), our society is headed into a perfect storm where both physical labor and knowledge labor are equally under threat.
The trends are here, whether through the coming of autonomous taxis or medical diagnostics tools evaluating your well-being. There is no reason to expect this shift towards replacement to slow as machine learning applications find their way into more parts of our economy.
The invention of the steam engine and the industrialization that followed may provide a useful analogue to the challenges our society faces today. Steam power first substituted the brute force of animals and eventually moved much human labor away from growing crops to working in cities. Subsequent technological waves such as coal power, electricity and computerization continued to change the very nature of work. Yet, through each wave, the opportunity for citizens to apply their labor persisted. Humans were the masters of technology and found new ways to find income and worth through the jobs and roles that emerged as new technologies were applied.
Here’s the problem: I am not yet seeing a similar analogy for human workers when faced with machine learning and AI. Where are humans to go when most things they do can be better performed by software and machinery? What happens when human workers are not users of technology in their work but instead replaced by it entirely? I will admit to wanting to have an answer, but not yet finding one.
Some say our economy will adjust, and we will find ways to engage in commerce that relies on their labor. Others are less confident and predict a continued erosion of labor as we know it, leading to widespread unemployment and social unrest.
Other big questions raised by AI include what our expectations of privacy should be when machine learning needs our personal data to be efficient. Where do we draw the ethical lines when software must choose between two people’s lives? How will a society capable of satisfying such narrow individual needs maintain a unified culture and look out for the common good?
The potential and promise of AI requires a discussion free of ideological rigidity. Whether change occurs as our society makes those conscious choices or while we are otherwise distracted, the evolution is upon us regardless.
Jonathan Aberman is a business owner, entrepreneur and founder of Tandem NSI, a national community that connects innovators to government agencies. He is host of “What’s Working in Washington” on WFED, a program that highlights business and innovation, and he lectures at the University of Maryland’s Robert H. Smith School of Business.