Published August 1, 2017Last updated July 21, 2022This article is more than 2 years old.
The age of artificial intelligence (AI) and robotics is upon us, but the current fad of emotional humanoid robots is not headed in the right direction.
First, let’s understand what robotics are based on:
- AI algorithms which are very good at optimization of explicitly defined goals (but cannot create, and have no feelings)
- Mechanical control which advances much slower than AI software algorithms
- Sensors which are rapidly improving but are often still too expensive, too large, or too power-hungry
Given the above, it is ludicrous to think that human-like robots will roam our homes any time soon. When a robot looks like a person, talks like a person, and has features like a person, home users will have unattainable human-capability expectations. The disappointment alone will doom any company hoping to bring science fiction to the living room in the next decade, not to mention the price-sensitivity for consumer markets.
Robotics must begin with utilitarianism in mind—robots should make money, save money, increase productivity, or deliver entertainment. There will be industrial robots that build other robots in high-volume, manufactured with today’s technologies. There will be commercial robots that deliver economic value (such as replacing security, receptionists, and drivers). There will be consumer robots that mimic today’s appliances and toys, requiring no consumer education, and causing no human-capability expectation.
These robots won’t look like a person. The industrial robot is a giant factory run in the dark by machines (like at Foxconn’s most advanced factories), or a warehouse with smart forklifts (like our investment Dorabot). The commercial robot comes in various forms and applications. It might look like an array of cameras (like our investment Megvii) or an automated store (like our investment F5 Future Store). The autonomous vehicle will look like a car, except will be first deployed in low-speed, freight, or fixed-function transport—such as in airport autonomous car-only lanes, or in transport from parking garages to shopping malls/theme parks (like our investment UISee). And the consumer robot may look like a speaker (like the Amazon Echo), a TV, a vacuum cleaner (like Roomba), an educational toy (like our investment Wonder Workshop Dash Bot), or a pad-on-steroids for family communications (like our investment Ainemo).
Will AI capabilities increase over time? Of course. Speech recognition will get better, computer vision will improve, SLAM will be improved to help the robot move around fluidly, and the robot will be able to translate languages, or have a dialog within limited domains. The robot may be able to read some of our emotions, or mimic certain human emotions. But this mimicking will go from laughable and entertaining to occasionally acceptable—and generally not genuine. For decades to come, robots by themselves will be unable to learn common sense reasoning, creativity, or planning. They also won’t possess the self-awareness, feelings, and desires that humans do. This type of “general AI” does not exists, and there are no known engineering algorithms for it. I don’t expect to see those algorithms for decades, if ever.
Trying to make robots human-like is a natural temptation for robotics and AI scientists, and predicting humanoid robots comes naturally to science fiction writers. But we humans simply think differently from AI. We create and AI optimizes. We love and AI is stoic. We have common sense and AI learns patterns from big data in a singular domain. Simply stated, we are good at what AI is not, and AI is good at what we are not.
In the future, the human edge will be in creativity and social interaction. Therefore, we need to focus robotics development toward what they’re good at: repetitive tasks, optimization, and utilitarian value creation. We should also let people do what they’re good at: innovation, creation, human-to-human interaction, and performing services.
I am an advocate of making utilitarian robots, and encouraging people to go into service jobs. I am not an advocate of making humanoid service robots—it is too hard today, and will not meet people’s expectations; therefore they will likely fail. Whether or not my analysis is correct, we need to be reminded that in the next decade AI will replace a massive number of manual-labor, repetitive, and analytical jobs. We have a human responsibility to help create societal service jobs—not to dream or plan a society in which all jobs come with the sign: “Humans Need Not Apply.”