Chien Lee-feng vs. Tom Wang
Should People Fear Robots?
Many workers are worried that robots and AI will supplant them. CommonWealth Magazine Group publication Cheers brought together two experts to discuss whether those concerns are warranted and what can be done to stay ahead of the game.
Should People Fear Robots?By Yang Jun-jie, Zheng Min-sheng
Six years ago, Cheers Magazine invited Taiwanese author and columnist Tom Wang and Google Taiwan Managing Director Chien Lee-feng to discuss “interdisciplinary” learning. In the six years since then, the world has undergone massive changes. With an artificial intelligence-driven robot beating a Go champion, and unmanned services proliferating, everybody is wondering the same thing: “Will my job be taken away by a robot?”
Six years later, Chien Lee-feng still stands at the forefront of the technology wave, and Tom Wang has initiated several innovative startups, including “D.R.E.A.M. School” and “Start Up Latte.” When the science-oriented Chien and the liberal arts-oriented Wang faced off recently, where did they come down on the arrival of the AI era?
Cheers: The last time the two of you conversed was six years ago. Since then, the world has changed beyond what anyone could have imagined. What have you seen from where you are positioned?
Tom Wang: I was in China a few days ago to participate in a marketing forum. Advertisers and ad agencies were very nervous because their value in the past was in helping customers with ad purchases and strategic planning, but now it’s possible to more precisely create value through automated ad placements.
Chien Lee-feng: These six years may have been the fastest changing six years ever for technology. The biggest impact I’ve felt is that what I see and experience inside Google used to need some time before appearing in daily life, but now it’s almost instantaneous. From the perspective of the tech world, nobody can really predict the future. Over these past six years, anything I’ve heard about or known has not been a secret. Things we know about one day now happen the next day.
The so-called “intermediate goods” era that once existed has now disappeared with the emergence of e-commerce. Producers and consumers are conversing directly. In terms of knowledge, “intermediate” knowledge is also gradually disappearing. In the past, teachers “transferred” knowledge to students, but now more students are looking up information on the internet rather than asking teachers questions.
Tom Wang: In the labor market, the opportunities for those who want to make a living as intermediaries have disappeared. Secretaries, for instance, were able to earn their pay by translating English documents for their bosses, but now Google may be able to translate those documents better than humans, so those who work as intermediaries are now threatened.
Cheers: How should we define which jobs are “intermediary”? How can people determine if their own jobs are at risk of being eliminated?
Tom Wang: The jobs inside most companies can be broken down into seven broad categories: collecting information, organizing information, analyzing information, interpreting information, thinking, deciding, and executing. People could make a living working in those areas in the past, but now “intermediary” jobs involving collecting, organizing and analyzing information no longer exist, and even jobs involving execution are under threat.
But firefighters who are responsible for putting out fires, they probably won’t be replaced (laughs).
Chien Lee-feng: Actually, we may one day use robots to fight fires.
Tom Wang: The first three types of work I was talking about, collecting, organizing and analyzing information, and the last type of work, execution, are all intermediary jobs. What’s left are interpreting, thinking about and deciding the best course of action once information has been obtained and analyzed. These are areas where people still have an edge on machines.
Chien Lee-feng: That’s right. In the information flow process, the collecting and organizing roles are rapidly declining because of the large number, speed and low cost of machines. But the value of interpretation and deduction is on the rise. The focus at present is on machines substituting for humans in the workplace, but we might want to use a different perspective in considering the issue: What new paths exist that weren’t around before?
Machines are smarter than ever, so we worry about being replaced by machines. But because machines are getting smarter, they are actually creating many roles that have never existed. This should be the direction young people explore.
Tom Wang: Even though machines are taking away jobs, the situation has led to deeper responsibilities and possibilities for humans. For things that people couldn’t do in the past, machines can now do much of the task, giving humans deeper responsibilities and enabling humans to do the remaining work in greater depth.
Chien Lee-feng: I see my two sons play games every day, and I can’t help but say to them: “You’re wasting your time by playing games every day.” But my son answers: “What is there that I don’t do as well as you used to do?” That seems true. At this age, they’ve experienced more than we did. They can get all kinds of information from the internet, and they have a lot of extra time with which to play games. The amount of work time freed up by machines supplanting people can be given back to people, and if it is fully exploited, we will end up being able to do things the previous generation couldn’t.
Tom Wang: Knowledge isn’t as valuable as it has been in the past, but other things have more value. What I wanted to add is that people need to better understand how to break down “higher knowledge” into “learning” and “asking.” [Editor’s note: the two Chinese characters used to form the term meaning higher knowledge or erudition are the characters for “learning” and “asking,” thus Wang’s play on words.] Higher knowledge was seemingly worth a lot in the past, but now it can’t compete with Google and is no longer worth much.
Chien Lee-feng: But Google doesn’t know what it can do. People have to ask for it to know (laughs).
Tom Wang: And because of that, in the AI era, despite information being transmitted at high speeds and the existence of easy access to many different viewpoints on social media, people will still have to cultivate the ability to “learn to ask” in the future. That includes asking yourself “Why is my opinion different from that of so many people?” and asking others “Why do you think that?”
The ability to ask questions, listen, understand, empathize, give back, coordinate, and compromise are things machines still cannot do and represent value that can be capitalized on in the AI era.
These skills are more needed today and are what we should be focused on.
Chien Lee-feng: I really like Tom’s play on the words for “higher knowledge” – “learning to ask.” The “higher knowledge” that we currently have is only a tiny fraction of what currently exists in the internet world. If we learn to ask, we can obtain any “higher knowledge” we need.
Cheers: In the past, there were simple, repetitive tasks that had to be done, so ordinary people still had a place to survive. But these tasks are now being handed over to technology to supplant humans. Can we say that “ordinary” or “mediocre” will emerge as threats to people?
Tom Wang: People who perform ordinary tasks will likely be replaced by machines. So to maintain an edge amid this robotic invasion, each person has to develop their own personal specialties. The term “person” should even be highlighted to emphasize that developing “personal” specialties means developing special “human” characteristics that cannot be simulated or replicated.
Chien Lee-feng: When we imagine the future, we always imagine only society’s smartest surviving. But that’s not completely true. Every person will change with the new environment, but this change won’t necessarily involve only the most talented people. The vast majority of people will still have opportunities.
Tom Wang: That’s a great point. We should redefine the meaning of “excellence” in this era. The traits that were considering outstanding in the past, such as being able to get good grades or take tests, don’t have nearly as much value today. Whatever the information, machines can analyze better than people can. So whether in education or management, we should redefine “excellence” and use “special characteristic” instead as the antonym for “ordinary.”
Cheers: Young people often complain that there aren’t enough opportunities, but now there’s another complaint reflecting even greater pessimism: “Work is very hard to find, and we even have to compete with robots.” Is that in fact how things are? Or can we use technology to turn things around?
Tom Wang: I represent more “non-scientific people,” and what I want to say is this: even if you didn’t study science or engineering, there are still opportunities. We need to change the mentality of “the times are already difficult and we even have to compete with robots.”
If you are competing with robots, it means you have already lost to them.
For example, of the three founders of room-sharing platform Airbnb, two were not engineers but industrial designers. They “harnessed technology” and found a third partner who understood technology to build the website, and together they used technology to connect other homeowners and shape the business as it exists today.
Liberal arts students should consider how to find their niche and harness technology while at the same time developing strengths that show more sensitivity to people’s minds, natures, and emotions. In that case, robots cannot be our rivals.
If we don’t take advantage of this strength and don’t harness technology and instead continue to do mundane, repetitive tasks, of course we’ll lose.
So right from the beginning we have to turn around how this battle is defined and develop strengths appealing to people’s minds, emotions and natures while using robots to do things bigger and better.
Chien Lee-feng: From the perspective of a non-scientific person looking at science-oriented people, the assumption seems to be that we understand all of this, when in fact we have never understood any of it (crowd laughs). So many people have had to contribute for technology to advance so quickly, yet every person is simply doing their job. In fact, we are still “managing people,” not “managing robots.”
So every individual and every generation needs to be able to make adjustments and have “mobility,” both “geographic mobility” and “knowledge mobility.” Taiwan is already very small, and it would be too bad if land defined boundaries. Knowledge mobility means constantly adjusting because there is nobody who doesn’t need to extend and expand their domain.
Tom Wang: I especially like the concept of “knowledge mobility.” In the era that social media has given rise to, knowledge mobility is even more difficult. We are all trapped to a certain extent in small “echo chambers,” so being aware of the limitations of your particular echo chamber and finding a way to break through in terms of knowledge or mindset is extremely important.
Chien Lee-feng: The similar information that reverberates in an “echo chamber” can easily make people think that the world is the same. But if you go to another echo chamber, you can immediately see an even bigger world. With that in mind, you have to boldly search rather than passively accept things. I don’t use any social media, but I search the internet at least 1,000 times a day and can get a feel for the major issues people are concerned about just the same. I don’t rely on their “pushes” and “notifications.” I search on my own.
Cheers: For those identified as having jobs likely to be lost to technology, what actions should they take? And for the group considered to be “hotshots,” what should they pay attention to?
Chien Lee-feng: There are no “hotshot” professions (laughs). They’re only hotshots today. Tomorrow’s hotshots have yet to emerge. The impact of every shift in the tech sector is huge, and nobody knows what the hottest industries in the future will be.
Tom Wang: Maybe we are all “hotshots” and we just don’t know it. If it’s just about writing programs, then liberal arts students won’t be the big players, but figuring out how to use a service to meet customers’ needs, that’s a business. Students should feel fortunate that they are already in a popular industry; they just have to expand their horizons to pick up on this new trend.
So I think that as long as people don’t turn into machines, machines won’t be able to turn into people.
When people perform repetitive, routine, impersonal tasks at work every day, they become machines, and of course will be supplanted by machines. But if you can inject warmth and expertise, develop insight and increase human value, then machines cannot become people.
Chien Lee-feng: If you work like a machine, even if you like the job, others will feel sorry for you and send a robot to rescue you (laughs). If you treat yourself as a machine, then it will only be natural that machines become people. But if you position yourself as a person of a higher order and use information to generate strength, then people will continue to do fine.
AI has made gradual advances; it didn’t just emerge today, and as a result, people should not be too concerned. It’s very easy to acquire knowledge now; all it takes is to learn how to “ask” and you can strengthen the skills needed in the future to the point where you’ll have nothing to fear, no matter how powerful robots get.
Translated from the Chinese article by Luke Sabatier