With virtual assistants answering our emails and robots replacing humans on manufacturing assembly lines, mass unemployment due to widespread automation seems imminent. But it is easy to forget amid our growing unease that these systems are not “all-knowing” and fully competent.
As many of us have observed in our interactions with artificial intelligence, these systems perform repetitive, narrowly defined tasks very well but are quickly stymied when asked to go off script — often to great comical effect. As technological advances eliminate historic roles, previously unimaginable jobs will arise in the new economic reality. We combine these two ideas to map out potential new jobs that may arise in the highly automated economy of 2030.
Training, supervising and assisting robots
As robots take on increasingly complex functions, more humans will be needed to teach robots how to correctly accomplish these jobs. Human Intelligence Task (HIT) marketplaces like MTurk and Crowdflower already use humans to train AI to recognize objects in images or videos. New AI companies, like Lola, a personal travel service, are expanding HIT with specialized workers to train AI for complex tasks.
Microsoft’s Tay bot, which quickly devolved into tweeting offensive and obscene comments after interacting with users on the internet, caused significant embarrassment to its creators. Given how quickly Tay went off the rails, it is easy to imagine how dangerous a bot trusted with maintaining our physical safety can become if it is fed the wrong sets of information or learns the wrong things from a poorly designed training set. Because the real world is ever-changing, AI must continuously train and improve, even after it achieves workable domain expertise, which ensures that expert human supervision is critical
Integrating jobs for people into the design of semi-autonomous systems has enabled some companies to achieve greater performance despite current technological limitations.
BestMile, a driverless vehicle deployed to transport luggage at airports, has successfully integrated human supervision into its design. Instead of engineering for every edge case in the complex and dangerous environment of an airport tarmac, the BestMile vehicle stops when it senses an obstacle in its path and waits for its human controller to decide what to do, enabling the company to enter the market much more quickly than competitors, which must refine their sensing algorithms to allow their robots to independently operate without incident.
Frontier explorers: Outward and upward
When Mars One, a Dutch startup whose goal is to send people to Mars, called for four volunteers to man their first Mars mission, more than 200,000 people applied.
Regardless of whether automation leads to increased poverty, automation’s threat of displacing people from their current jobs and in essence some part of their sense of self-worth could drive many to turn to an exploration of our final frontiers. An old saying jokes that there are more astronauts from Ohio than any other state because there is something about the state that makes people want to leave this planet.
One risk to human involvement in exploration is that exploration itself is also already being automated. Recently, relatively few of our space exploration missions have been manned. Humans have never left Earth’s orbit; all our exploration of other planets and the outer solar systems has been through unmanned probes.
Artificial personality designers
As AI creeps into our world, we’ll start building more intimate relationships with it, and the technology will need to get to know us better, but some AI personalities may not suit some people. Moreover, different brands may want to be represented by distinct and well-defined personalities. The effective human-facing AI designer will, therefore, need to be mindful of subtle differences within AI to make AI interactions enjoyable and productive. This is where the Personality Designer or Personality Scientist comes in.
While Siri can tell a joke or two, humans crave more, so we will have to train our devices to provide for our emotional needs. In order to create a stellar user experience, AI personality designers or scientists are essential — to research and to build meaningful frameworks with which to design AI personalities. These people will be responsible for studying and preserving brand and culture, then injecting that information meaningfully into the things we love, like our cars, media, and electronics.
Chatbot builders are also hiring writers to write lines of dialogue and scripts to inject personality into their bots. Cortana, Microsoft’s chatbot, employs an editorial team of 22. Creative agencies specializing in writing these scripts have also found success in the last year.
Startups like Affectiva and Beyond Verbal are building technology that assists in recognizing and analyzing emotions, enabling AI to react and adjust its interactions with us to make the experience more enjoyable or efficient. A team from the Massachusetts Institute of Technology and Boston University is teaching robots to read human brain signals to determine when they have committed a fault without active human correction and monitoring. Google has also recently filed patents for robot personalities and has designed a system to store and distribute personalities to robots.
As automated systems become better at doing most jobs humans perform today, the jobs that remain monopolized by humans will be defined by one important characteristic: the fact that a human is doing them. Of these jobs, social interaction is one area where humans may continue to desire specifically the intangible, instinctive difference that only interactions and friendships with other real humans provide.
We are already seeing profound shifts toward “human-centric” jobs in markets that have experienced significant automation. A recent Deloitte analysis of the British workforce over the last two decades found massive growth in “caring” jobs: the number of nursing assistants increased by 909% and care workers by 168%.
The positive health effects of touch have been well documented and may provide valuable psychological boosts to users, patients, or clients. In San Francisco, companies are even offering professional cuddling services. Whereas today such services are stigmatized, “affection as a service” may one day be viewed on par with cognitive behavioral therapy or other treatments for mental health.
Likewise, friendship is a task that automated systems will not be able to fully fill. Certain activities that are generally combined with some level of social interaction, like eating a meal, are already seeing a trend towards “paid friends.” Thousands of Internet viewers are already paying to watch mukbang, or live video streams of people eating meals, a practice which originated in Korea to remedy the feeling of living alone. In the future, it is possible to imagine people whose entire jobs are to eat meals and engage in polite conversation with clients.
More practical social jobs in an automated economy may include professional networkers. Just as people have not trusted online services fully, it is likely that people will not trust more advanced matching algorithms and may defer to professional human networkers who can properly arrange introductions to the right people to help us reach our goals. Despite the proliferation of startup investing platforms, for example, we continue to see startups and VC firms engage placement agents in order to successfully fundraise.
Despite many claims to the contrary, designing a fully autonomous system is incredibly complex and remains far out of reach. For now, training a human is still much cheaper than developing robot replacement.
“TRIF” is a team of venture capital experts including Tiffine Wang of Singtel Innov8, Ivy Nguyen of Zetta Venture Partners, Ryan Morgan of DFJ Growth, and Freddy Dopfel of Stanford University.