Global population forecasts say the world’s population will reach almost 8.5 billion by 2030. With the speed at which AI, computational processing power and robotics are developing, it is safe to predict that the global workforce and demands will change markedly in the near future. Job functions will transform rapidly following the pace of technology, so a priority should be to have a workforce that is educated and adaptable, ready to adjust to changing competency demands.
As we argue in our book, “Expand: Stretching the Future by Design,” these demands will be shaped by how work processes between man and machine are designed. Will the machine’s analytical power replace human power? Will the human presence in some job functions become obsolete? Those questions are framed mistakenly. It’s not a question about replacing one or the other; it’s about how machines and humans supplement each other.
Pioneering designers and industry players are talking about how humans and machines can work together for the greatest benefit. The smartest questions aren’t designing the fastest CPU or the strongest robot. AI and robotic development will be about developing the best teams, processes and user experiences.
Designers will be looking at solutions where humans and machines complement each other to democratize the potential of both. Computational power should not be reserved only for the brightest specialists, but for everyone. We will increasingly live and work with robots built for collaboration.
As Andrew Maynard, a professor at Arizona State University has pointed out, there is much we can learn about the future of human-machine interaction and the real dilemmas involved in science fiction movies. Take the first Pacific Rim movie from 2013 as an example. In the movie, we follow the unlikely hero Raleigh and his brother Yancy. Raleigh describes the pair “…you wouldn’t have been picked by my brother Yancy and I for heroes… No chance. We were never starring athletes, never at the head of the class, but we could hold our own in a fight. And it turned out we had a unique skill: we were drifting compatible.”
Being “drift compatible” means that the two brothers are able to work as a team while neurally linked to control a giant killer robot, the Gipsy Danger. The brothers are neither bright nor strongest but still form a great team. Compared to the other killer robots and monsters in the movie, Gipsy Danger is also neither the strongest nor best-equipped, but nonetheless, it is the most successful. Why? Because the brothers and their robot form a formidable team.
Are Human-Robot Teams Possible?
A key question becomes this: What does it take to create human-robot teams that don’t just get along but are formidable? Recently, researchers at Aalborg University in Denmark have explored this question by focusing on trust: What does it take for people to trust robots? And what happens if people trust robots too much? Too much trust in self-driving cars might get the driver killed, as this happened to a Tesla Model S driver in a 2016 Florida accident. At the workplace, trusting a large industrial robot beyond what is warranted can lead to equally dangerous situations (a person can be knocked to the floor, or worse if an XL-size robot hits it accidentally).
In the former case of too little trust, workers will simply choose not to work with the robot and the firm’s investment in the technology will lose value. To explore how trust is affected by robot behavior, the researchers at Aalborg University have tried speeding up a collaborative robot in unpredictable ways while measuring workers’ physical responses. After the experiment, people indicated they were less likely to trust the robot due to their erratic behavior. Next up: Real-time experiments where humans and their robot collaborators will work on advanced carbon fiber weaving tasks – some of the more complex processes in auto manufacturing.
We should approach the future of robotic design in the context of humans and machines working together forming the best teams. A survey of a thousand companies working with AI published in Harvard Business Review stated in 2018 that “… Most activities at the human-machine interface require people to do new and different things (such as train a chatbot) and to do things differently (use that chatbot to provide better customer service). So far, however, only a small number of the companies we’ve surveyed have begun to reimagine their business processes to optimize collaborative intelligence.”
Collaboration between man and machine will be the key to how innovation in the field of AI and robotics will grow in the near future. The best designers will know that product development will not be about replacing humans, but rather seeing how the interaction between humans and machines across various fields can be optimized and simplified.
How do machines and humans complement each other? How can they interact smoothly and successfully? Garry Kasparov, the world’s last human chess world champion, wasn’t the only one to reach that conclusion after his games against IBM’s Deep Blue AI. His “opponent” IBM is actively working to ensure that design thinking is applied in all aspects of the business. Today, at least 110,000 of the company’s 388,000 employees are applying design thinking methods to develop the company’s business domains such as AI and CPUs. IBM is iterating and experimenting with how they can improve the user’s experience of working with computational power. This is because we need more than humans and robots just getting along. We need them to create value together that neither man nor machine could realize on their own.