The man versus machine dichotomy has been a staple of pop culture for decades. From 2001: A Space Odyssey to Blade Runner to Terminator to The Matrix and beyond, film makers have envisioned what the world would look like if artificial intelligence took over.
However, a new mindset is taking shape — the era of AI-human hybrid intelligence. This combination of a human brain and a computerintelligence is known as a centaur. The centaur model sparked the growth of freestyle chess, a context in which Garry Kasparov concluded that “weak human + machine + better process was superior to a strong computer alone and, more remarkable, superior to a strong human + machine + inferior process.”
Kasparov’s statement regarding the centaur model is no longer relegated to the world of chess. As AI innovation continues to grow, we should carefully review the centaur model in terms of the workplace and consider how combinedhuman and computerintelligencewillredefinejobs.
History says machines won’t destroy the workplace
In 1800, farming accounted for nearly 75 percent of the U.S. labor force. However, the Industrial Revolution introduced a number of inventions that led many to believe there would be massive unemployment rates throughout the country.
The applications for the centaur model in the workplace are potentially endless.
The Industrial Revolution resulted in a 25 percent decrease in farming labor by 1890 — but we didn’t see the unemployment that the general public feared.
Instead, jobs moved to factories and eventually white-collar jobs like stockbrokers and business consultants emerged to further stabilize the workforce. Now, as we enter the Intelligence Revolution, it’s important to realize that technology won’t create historic unemployment rates.
Like in the 1800s, technology will result in the decline in certain types of jobs, but new positions that we haven’t even envisioned will give people an opportunity to fill in the gaps that machines can’t — seeing the big picture, thinking creatively and connecting seemingly disconnected ideas.
Thinking of technology as a means of reshaping the workplace rather than a means of replacing any and every job, you can see where the centaur model can redefine employment.
Where the centaur model fits into the workplace of tomorrow
Being a centaur in tomorrow’s workplace means combining your own emotional intelligence with the analytical power of AI-enabled technology. Google’s Deep Dream Generator is a good example of how this will work.
The Deep Dream Generator turns vision algorithms inward to display what neural networks see when analyzing an image. Now, Deep Dream is being used to create intricate artwork — but it can’t create images from nothing. The Deep Dream Generator relies on human input, a seed from which it can create art.
Being a centaur in the workplace means taking advantage of the vast analytical capabilities of AI-enabled technology and adding human thinking. The applications for the centaur model in the workplace are potentially endless, but here are a few example fields that are well-suited for the combination of deep analysis and human creativity:
- Security and network planning: The volume of cyber attacks will continue to grow and AI will become increasingly necessary in threat analysis. However, attackers will always be creative, launching non-computerized vectors to compromise business networks. This is why humans will be necessary to prompt machines toward new ways of keeping creative attackers at bay.
- Visual arts and music: Collaboration will replace the linear nature of artistic creation that we think of today. Two different algorithmic versions of a music program could give a human enough content to combine the two and generate an entirely new genre. Or, like Google’s Deep Dream, humans can input seeds of information for machines to generate artistic products.
Film and television: There are enough test cases for us to truly understand what a well-framed scene looks like. Teaching a machine how to essentially direct means filmmakers can set up scenes in VR and focus more on storytelling and creative connections than the minute details of production.
- Architecture and product design: Function over form has dominated each of these fields. However, leaving a machine to design based on function over form might have us living in buildings that are just white boxes. However, IoT sensors can teach machines how we interact with our environments to learn exactly what people need in terms of function, leaving humans to balance function with form — spending more time on the art and less on the details.
- Software engineering: Development is often thought to be a non-creative discipline, but the best software code is also the most creative. The best developers of tomorrow will direct computers on a certain problem, examine the output and continue to redirect machines until they have new ways to solve old problems.
It’s easy for a conversation about AI to devolve into a philosophical discussion about consciousness, because that’s what we bring to the table — a sense of consciousness and intuition that machines don’t possess.
But there’s no way around it; AI is going to redefine the workplace. However, machines are terrible risk takers and have no capacity to make leaps of faith. Rather than thinking about whether or not machines will rule the world, let’s think about how we can become workplace centaurs that creatively redefine the jobs of tomorrow.
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