Top 10 Surprisingly Safe Jobs from AI
This is a series of 4 articles I am sharing here, for people who are concerned and eager to understand more about job displacement impact potentially caused by artificial intelligence technology. You would read about “safe” versus “endangered” jobs in this series. The jobs listed in each article are demonstrative from my research research and technological knowledge, which may or may not fit into your personal scenario.
I highly encourage readers to take those as references and inspirations, and to start re-imagine and re-strategize your career today with our shared future — powered by AI.
How to determine what jobs are safe/unsafe?
- Repetition vs. strategic:
- Does your job have minimal repetition of tasks?
- Do you regularly come up with insights that are important to your company?
- Do you make key decisions that cross functions for your company?
- Simplicity vs. complexity:
- Do most decisions in your job require complexity or deliberation?
- In your job, do you need to regularly learn and understand a lot of complex information?
- Dexterity vs. repetition:
- Does it require at least a year of training to be qualified for your job?
- Does your job involve very little repetition of the same task(s)?
- Fixed vs. unstructured environment
- Is your job usually performed in different environments each time? (e.g., a taxi driver would always work in the same taxi)
- Is your work environment unstructured?
For all jobs: human-contact / empathy / compassion
- Is communication and persuasion one of the most important parts of your job?
- Do you spend >30% of your work time with people who are not employed by your company (e.g., customers, potential customers, partners) ?
- Is a key part of your job performance measured by how well you interact with people?
- Does your job result in happiness, safety, or health of those your directly service?
- Do you lead or manage people in your job?
Top 10 Surprisingly Safe Jobs from AI
While there will be better and smarter machines to help us exercise, fitness trainers will customize programs for each of us, provide companionship, and create a forcing function for us not to procrastinate. Also with more societal wealth, and more efficient forms of transportation (think smart or even automated Segway) , we will need more exercise than ever. Finally, in the age of AI, self-help, entertainment, and health will be main themes of growth in the era of AI because we will have more collective wealth and more free time.
McKinsey Health care occupations will increase world-wide by 51 million to 83 million globally by 2030. This category includes elderly caretaker, home health aides, personal care aides, nursing assistants, but the greatest gap will be related to elderly care. This need is increasing as we live longer, older people need substantially more health care, and the difficulty of filling these jobs. While AI can help with monitoring, security, and perhaps movement of the elderly, only human assistants can help with bathing, dressing, and most importantly conversation and keeping company. These are not doable by AI.
Housecleaner, gardener, and other jobs that work in unstructured spaces with changing conditions are difficult for robots. Smarter appliances like the Roomba will take away some workload, but the overall employment levels will probably be sustainable. We also envision that immigrant service providers will be more common (laws permitting), as AI further separates the wealthy country from the poorer ones.
Nurses, child care workers, mental health support specialists, and drug rehabilitation therapists are among the most difficult for machines to replicate, because of the high degree of human interaction, communications, and trust-building. For example, exceptional communication skills are needed for vulnerable and depressed patients, after first understanding what’s troubling the patients. These are well beyond AI today.
Concierge, hotel management, bespoke, and other premium services will be in high demand by the newly rich (e.g., the AI entrepreneurs and engineers). While standard services are handled by the Internet (travel websites), and AI (autonomous fast-food and coffee), there will be a larger premium offered to substantially better services with a human touch, personalization, and long-term relationship and trust. Leisure and entertainment will be good growth areas in the era of AI.
Athletics and sports will not be affected at all just because machines will become better at the games. These are human-participation entertainment. Sports superstars are like famous singers and movie stars. As people have more leisure time, it is possible talented and charismatic athletes even more money in this area.
Nanny is one of the most endearing jobs, perhaps even reaching an “extended family” status. Many of the physical tasks of the nanny (vacuuming, washing dishes) will ultimately be automated, as the nanny job gradually shifts to more “love and personalization” added services such as cooking a meal a child loves, or reading the child’s favorite story. More of the job will be about accompaniment, nurturing, and entertaining children of the family. That makes the job irreplaceable by AI (for nannies who make the transition)
A good tour guide is a good story teller, which means he or she combines personal experiences, theatrical styles, and encyclopedic knowledge into an inimitable experience. A good tour guide also makes interesting and informative conversation and leaves the tourists with a memorable experience. But of course, the tour guide who replays the same segments every time will be out of luck.
Human resources in general, recruiting in particular, and headhunters specifically, are very much about the human touch. To persuade someone to give up his or her job and consider another one is extremely difficult. It requires personalized understanding, trust-building, and a long-term relationship. Of course, the HR industry will adopt and AI for routine question-answering (such as responding to employee email), performance monitoring, solicitation (for recruiting), filtering (applicants), and job-matching, as the human resources jobs become even more “human”.
Data processing and labeling
We end with a huge surprise — everyone would think data entry and processing jobs will be mechanized and gone (often no AI is even needed). However, in the next 20 years, AI will be trained on an unbelievable amount of ever-increasing data, which at least initially need to be manually selected, processed, labeled, and categorized. Amazon Mechanical Turk is a case-in-point. But do not expect this job to be highly paid!