AI Needs to Become Less Elitist

Executive Summary

20% of kids who were not interested in AI said they did not think they were smart enough. 24% said they would prefer a more creative career. Both of these results point to an elitist attitude toward AI from government and in the media. That attitude needs to change if we’re going to prepare for a world where lots of jobs involve using or interacting with AI. The best thing the technology community can do to help is to debunk the notion that only people who know how to code can work with AI. Schools aren’t the only institutions that need to rethink who’s qualified for AI work. The business world is missing out on the most obvious answer to solving the shortage of AI talent: retraining and re-skilling existing employees today for the jobs of the future. Ultimately, the AI community will need diverse types of expertise, experience, and education to ensure that the technology represents the people it serves.

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A survey conducted last year by my company, Sage, in partnership with YouGov, found that one in four children aged 8-18 in the UK is interested in pursuing an AI career. What about the rest of them? Well, 20% of kids who were not interested in AI said they did not think they were smart enough. The most common answer (24%) was that they would prefer a more creative career. Both of these results point to an elitist attitude toward AI from government and in the media. That attitude needs to change if we’re going to prepare for a world where lots of jobs involve using or interacting with AI.

At Sage, we worked through Sage Foundation, with an external partner, to bring AI development down to Earth for kids from diverse communities in the UK last year. The program taught us that success means more than teaching kids technical skills in computing and IT. Curricula must include basic computing skills and coding as standard to prepare kids to work with automated technologies like AI in the near future. But they must also teach non-technical skills including problem-solving, creativity, communication, and collaboration.

The best thing the technology community can do to help is to debunk the notion that only people who know how to code can work with AI. Instead, the world needs to focus on lowering the educational and psychological barriers to entry for computer-skill training and AI literacy – and that starts in grade school. In the United Kingdom, for instance, there is a clear digital skills gap and, unfortunately, stark gender disparity among student populations interested in computer science. In fact, only 12% of high school students in the country chose to take computer courses in 2017. On top of that, only 20% of those students were female. Both numbers need to increase dramatically in the UK – and, frankly, around the world – not only for the sake of students’ careers but so that the people building technology accurately represent the people they are creating it for.

Schools aren’t the only institutions that need to rethink who’s qualified for AI work. The business world is missing out on the most obvious answer to solving the shortage of AI talent: retraining and re-skilling existing employees today for the jobs of the future. Those jobs will require people to understand the basics of AI regardless of title or discipline. Not everyone who receives this sort of training needs to have an advanced degree or plan to become a data scientist. The evolution of IT created a wide range of occupations, with different educational requirements, many of which became high-paying middle-class roles. Similarly, we need to prepare a broader workforce not just to build but to test, support, sell, and secure AI systems. Most companies have lots of current employees who could be trained to excel in these roles. These efforts should complement ongoing education system initiatives to expand learning – including progressive programs that prioritize teaching STEM subjects from an early age.

Ultimately, the AI community will need diverse types of expertise, experience, and education to ensure that the technology represents the people it serves. And the companies who build and use AI over the next decade stand to benefit from the vibrant perspectives of artists, creative writers, and linguists, as well as the technical know-how of programmers and data scientists. The onus is on both industry and the public sector to equip both children and adults with the hard and soft skills needed for AI to reach its potential.

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