For example, making decisions as a CMO requires you to incorporate many different types of information, and respond to an ever-changing work environment. To be an effective CMO, you need years of education and experience, and you’ll be making decisions that can impact multi-billion dollar corporations in some cases.
AI is constantly getting better, so from a certain perspective, it’s only a matter of time before AI algorithms become sophisticated enough to handle more complicated jobs.
We’ve already seen this play out in a handful of areas. For example, AI is being increasingly used in the marketing industry to crunch numbers and intelligently recommend new strategies. It’s being used to write content on a regular basis—and the content it produces is almost indistinguishable from content generated by human writers. AI is also being used in the medical field, responsible for executing precise surgeries on patients and analyzing and filling prescriptions for patients in a pharmacist role.
Perhaps the most promising area of development in AI and automation is the inclusion of human emotion. Engineers are developing chatbots and other forms of AI that can both “understand” and replicate human emotions; in the near future, you may be able to have an open conversation about your feelings to an AI-based, virtual HR rep. You may hear notes of compassion in the voice of a chatbot when you call a customer service line. You may even rely on an AI algorithm in a therapy session.
Tech optimists see these forms of progress as an indication of where we’re headed. In 1996, AI was sophisticated enough to beat the human chess champion Garry Kasparov in a game of chess. In 2015, AI became sophisticated enough to beat human go players (with go being considered one of the most complex traditional games). It wasn’t that long ago that it was considered impossible for computers to become advanced enough to beat human players in either chess or go.
The mentality here is that we’ve seen AI do “impossible” things on a consistent basis. Every year, we develop machines to accomplish something new that was previously thought to be unthinkable. Following this line of logic, it’s hard to assert that there’s anything truly impossible for machines to do.
AI and Humans: A Perfect Partnership?
Of course, just because AI could have the power to accomplish human responsibilities doesn’t mean AI is going to replace human beings in a takeover of their current jobs. There are a number of possibilities that could allow humans and AI to work together in harmony.
In the first vision, AI is merely used to handle responsibilities that humans can’t handle, for one reason or another. For example, completely automated surgery may be reserved for handling surgeries when human surgeons are busy or unavailable; there’s a doctor shortage in the United States, and AI-based systems could arise to help fill the void, thereby jeopardizing few (if any) human jobs.
In another vision, AI could mostly serve as a complement to human thinking. Rather than depending exclusively on human creativity or AI-powered calculus, the best systems would reflect a partnership between these modes. Human beings in analyst and creative positions would utilize AI as tools to enhance their own skills, knowledge, and abilities. Their abilities would be enhanced, rather than replaced.
It’s also worth noting that AI could replace some human responsibilities without actually replacing the humans engaging in those responsibilities. For example, if part of your job is generating marketing reports, the AI could take over that portion of your workday—and you could spend more time handling other, more complex responsibilities. In this vision, the nature of white collar work would gradually change, with white collar workers taking on bigger, higher-level, and more complex responsibilities over time. This could result in an even bigger skill gap between blue collar and white collar workers, and spur a number of problematic economic side effects; however, it wouldn’t mean the true end of any white collar jobs.