Frederick Dopfel 

This thought piece was written in collaboration with my peers Ryan Morgan, Ivy Nguyen, and Tiffine Wang. An abridged version is available on ReadWrite

 

With AIs answering our emails and robots increasingly replacing us on manufacturing assembly lines, mass unemployment due to widespread automation seems imminent. It is easy to forget amid our growing unease that these systems are not all knowing and competent.  As many of us have observed in our interactions with AIs, 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 types of jobs will arise in the new economic reality. We combine these two ideas to map out some new jobs that might arise in the highly automated economy of 2030.

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Training, Supervising, and Assisting Robots

As the tasks robots and AIs take on become increasingly complex, more humans will be needed to teach these robots how to correctively accomplish these jobs. Human Intelligence Task (HIT) marketplaces such as MTurk and Crowdflower already use humans to train AIs to recognize objects in images or videos. New AI companies are expanding HIT with specialized workers to train AI for complex tasks. Lola is one such company using professional travel agents to train its AI.

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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 but was ultimately harmless. Given how quickly Tay went off the rails, however, it is easy to imagine how dangerous a bot insured 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, AIs must be continuously training even after they achieve workable domain expertise, making expert human supervision critical to ensure that the AI remains correctly tuned for its intended function instead of evolving incorrect models that will impede its performance.

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Integrating humans into the design of a semi-autonomous system has enabled some companies to achieve greater performance despite current technological limitations. BestMile, a driverless vehicle deployed to transport luggage at airports, is one such company that 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 a 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 its competitors who must continue to refine their sensing algorithms to allow their robots to independently operate without incident.

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Frontier Explorers: Outward and Upward

Throughout history, people have emigrated between countries seeking better work opportunities. Examples include the German emigration to the United States in the 1800s and the ongoing emigration out of southern europe seeking better jobs. Since automation’s impact will be felt worldwide, the next big wave of emigration could be upward instead of merely out, leading to increased space exploration and settlement.  

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We already see that humans are ready and willing to emigrate to the final frontier in droves. 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. Furthermore, regardless of whether automation leads to increased poverty, automation’s threat of removing people from their current jobs and in essence some part of their sense of self worth could drive many to turn to exploration of our final frontiers. An old adage jokes that there are more astronauts from Ohio than any other state not because of Ohio’s great educational system but because there is something about the state that makes people want to leave this planet.

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Automation also has the potential to increase the “pull” that might lead to expanded space exploration.  By removing or reducing the cost of human labor, automation will lead to an increased demand for certain price-elastic goods. At some point, earth will begin running out of certain materials, many of which are abundant in space. Asteroid mining, while obscure, is not a new concept and is currently being pursued by startups including Planetary Resources and Deep Space Industries, even before increased demand for materials caused by automation. If the value of resources in space climbs sufficiently high, we may be able to witness a new “gold rush” in space, causing further upward human migration.

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One risk to human involvement in exploration is that exploration itself is also already being automated. Relatively few of our space exploration missions have been manned. Humans have never left earth orbit; all our exploration of other planets and the outer solar systems has been through unmanned probes. Even on earth, companies are finding it easier to explore remote areas using semi autonomous robots. Companies such as Liquid Robotics, which was acquired by Boeing in December 2016, are exploring the sea through unmanned ocean gliders.

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Artificial Personality Designers

As AIs creep into our world, we’ll start building more intimate relationships with them and the technologies will need to get to know us better. Just as an effective sales associate or waiter knows that different clients prefer different interactions, a single AI personality will not suit every user. 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 that make those interactions enjoyable and productive. This is where the Personality Designer or Personality Scientist comes in.

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While Siri can tell a joke or two, but humans crave for more and naturally we will have to train our “things” to provide for our emotional needs. In order to create a stellar user experience, Personality Designers or Scientists are needed to research and 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 such as our cars, media, electronics, fashion, and more—anything that AI might touch.

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A more intermediate and blunt solution that chatbot builders are using is hiring playwrights and poets to write lines of dialogues and outright 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 emerged in the last year.

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Startups such as Affectiva and Beyond Verbal are building technologies that assist with recognizing and analyzing emotions, enabling AIs to react and adjust their interactions with us to make the experience more enjoyable or efficient. A team from MIT 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.

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Human as a Service

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.

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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 careworkers by 168%. To extrapolate further, providing cuddling and other intimate, but non-sexual forms of human contact may become a common job in the future. 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 today are 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.

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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 (such as eating a meal) are already seeing a trend towards “paid friends.” For example, thousands of Internet viewers are already paying to watch mukbang, or live video streams of people eating meals, a trend that originated in Korea, in order to remedy the feeling of living alone. In the future, it is possible to imagine people whose entire job is to eat a meal and engage in polite conversation with clients.

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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.

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Looking forward

These jobs might seem outlandish today, but many high demand jobs such as app developers, social media managers and data analysts did not exist merely ten years ago. Despite what many startups claim, designing a fully autonomous system is incredibly complex and remains far out of reach. Training a human to help a robot with unexpected tasks or obstacles, or fulfilling the roles that require that intangible human touch will continue to be much cheaper than designing yet another robot to fill that role. While it is important to acknowledge that global upheaval caused by increasing automation continues to grow, it is equally vital to look ahead what more we can do with the time and resources, and therefore possibilities, that automation unlocks.

 

This thought piece was written in collaboration with my peers Ryan Morgan, Ivy Nguyen, and Tiffine Wang. An abridged version is available on ReadWrite