By Prasad Akella, founder and CEO of Drishti
I always use spell check when I write business correspondence and other important material. If I make a spelling error—or even frequent errors—no one knows about it. Thanks to this program, I always seem like a master speller. My creative ideas and unique thoughts are now better presented, and more effective.
But spell check isn’t going to replace me as a writer or thinker. It’s a useful tool, but it’s not going to take over all correspondence for me any time soon. The ideas and the hard work come from me.
This is what we need to keep in mind when we read the headlines—like some we’ve seen recently—suggesting that artificial intelligence will be booting even the smartest, best educated professionals out of a job.
In stark contrast, the reality is that automated systems can actually help human workers retain their jobs. Robots help companies scale-up during busy times (Christmas holiday or tight labor markets) and scale back without firing human workers. According to a recent Wall Street Journal article, logistics company Radial uses robots for just that purpose, ramping up its workforce by over 20,000 people next year, and not just for the Christmas holiday. What allowed for such drastic growth in that company’s staffing? The robots that made scalability so much easier.
It is stories like this that we must keep in mind when considering how robots will impact the future of our workplace. Often, when it comes to advancements in robotics and AI, the headlines are alarmist. They read that way in the late 1990s, when I led the GM team that, working with academics, brought collaborative robots (cobots) to the manufacturing lines at General Motors and the manufacturing world at large.
Two decades later, there are still 350 million human beings at work on assembly lines, at companies like GM and many others. By comparison, there are some 1.8 million robots working on those lines. If you do the math, it’s apparent that robots do not even make up a half of a percentage point in the factory workforce. So how does that stack up against our fears of robots replacing all human jobs?
Humans are nowhere near replacement by robots or AI, and this is true whether you’re using your hands to assemble products or using your mind to solve complex problems. I’ve had a long career in automation, including being on the front lines when robotic systems became dominant in parts of the factory floor. From designing robotic hands at Stanford to automating assembly lines at GM, I remain convinced:
Humans and machine both perform better when one is augmented by the other. 1+1 is often greater than 2.
Automatons and Lean Manufacturing
Automation is not a new concept. In fact, the term “automaton” was used in Homer’s Iliad, in reference to self-operating machines that were created to help Greek gods mass-produce weaponry and other equipment.
The term “automatic” came into widespread use in the 1940s, when Henry Ford (who had already disrupted decades’ worth of “one-off” manufacturing with the introduction of the assembly line earlier that century) established an automation department at Ford..
Decades later, Toyota and the Japanese manufacturing industry introduced the concept of Toyota Production System (TPS, later generalized to “lean” manufacturing), to reduce waste and inefficiency without sacrificing productivity by, in large part, empowering the front line associates.
This is an ideal we’re still striving for today. TPS was a revolutionary concept when it was introduced half a century ago, but it was only so effective, because the data informing every manufacturing decision was sorely lacking.
Eliminating inefficiency is difficult when we can’t clearly see where the inefficiencies lie. Manufacturers have long known that inefficiencies happen on manual assembly tasks, but couldn’t do a whole lot to fix it. With incomplete or inaccurate data, we won’t be able to boost productivity in a significant way.
This was the inspiration for Drishti.
Using computer vision, we can get the data that has been missing in lean manufacturing. And using artificial intelligence, we can use this data to create a more productive, efficient and profitable manufacturing business. The best part is, Drishti enables manufacturers to do this even as they invest in and develop their very creative and flexible human team, gaining from their deep insights and experiences on the floor, so both the person and the company come out ahead. It does not need to be one at the expense of the other.
And, as before, the human/machine symbiosis makes both parties stronger—and the combination even more powerful..
The Human-Machine Relationship
My career has been one of curiosity and exploration of not only what the human mind can do, but how it can work in conjunction with a machine. I’ve been fortunate to have a successful career in automation and robotics. My success comes down to focusing on how people can function at their highest level in an increasingly automated world.
The future will be all about people and machines working productively together, so the real opportunity lies in enabling and enhancing the relationship between the two. Too many companies have focused solely on the technology, and left the human component out of the equation, which neglects the biggest asset of any corporation.
At Drishti, we focus on the fact that more than 70% of all tasks performed on the factory floor are performed by people, even decades after automation appeared on the scene. Drishti will be the company that fills the significant information gap that has persisted over the decades.
When Drishti was a one-person company with an idea and an early prototype, I was able to sign on a major electronics maker and a large auto parts manufacturer as customers. Why? They knew where the value lay: in maximizing the effectiveness of the human by drawing on the insights delivered by a machine that can gather and distill data at a scale beyond which any human can ever dream.
Drishti continues to grow and help other companies maximize their potential, and it’s because we’ve embraced all of the attributes of an Enterprise 4.0 company. Manufacturing is a $12 trillion dollar industry. 345 million people work in factories worldwide. We currently have customers primarily in automotive, electronics and medical devices with a combined revenue of well over $450 billion. We achieved that through recognizing human potential and leveraging the power of unique data.
A New Era for Enterprise Tech
So how do we maximize human potential in a world seemingly dominated by machines? Drishti deploys dozens or even hundreds of small cameras throughout the manufacturing operation. These cameras record the manual tasks being performed on the line, and beam that information to a cloud-based system that uses AI to analyze many manufacturing attributes.
It’s an extremely sophisticated system, but simple to use. To the line associate and supervisor, Drishti provides constant information on manual tasks and manufacturing processes. At the same time, Drishti points the plant manager to the lines where he or she should focus attention.
Just as a doctor or a patient does not need to understand how the core imaging technology in an MRI machine works to learn that your kidneys are just fine, our customers don’t need to understand computer vision or AI because those functions are embedded deeply into a system that’s intuitive and easy to use. What they need to focus on, as became very clear to us in working closely with our customers, is consuming this data which is presented to them in a contextual and accessible manner.
To do this, they need to train their teams on the fundamentals of statistics, so they can interpret the large volumes of data that have suddenly become available. But, the cardinal rule that we learned still stands: minimize the amount of work manufacturers need to do to master new technologies and maximize the value that you deliver to them. This is what today’s customer expects.
We were able to build an intuitive system by leveraging unique sets of data—in our case, the data being the everyday activities of manual processes, which we capture with cameras and computer vision. This data is then processed in a manufacturing context and provided to our customers so they can reassess the the age old question every successful company considers: in addition to equipment, am I making the best use of my human capital?
This is what the new era of enterprise technology is all about. To succeed, companies must work closely with the customer to solve real-world business problems, and use data technologies in such a way as to add value without requiring extra effort.
In stark contrast to most AI companies, Drishti won’t be building automated systems that put people out of work; actually, it’s quite the opposite. When we look out into the future, we see a world where humans and machines work together closely, collaboratively and effectively. It is this human-machine relationship that we aim to celebrate and make the best it can be.
