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Michael Li, founder and CEO of The Data Incubator, addressed the Future Trends Forum of the Bankinter Innovation Foundation, focusing on education and the urgent need for training in data science in the era of artificial intelligence (AI). He highlighted AI as a significant challenge for employment over the next decade, with studies indicating that up to 50% of jobs might disappear due to automation. Despite this, Michael remains optimistic about education’s role in maintaining employability, emphasizing the necessity of better understanding AI and computing. He advocated for leveraging the comparative advantages of both humans and AI: computers excel in consistency and statistical tasks, while humans contribute essential context and empathy.
Michael illustrated his points with the example of doctors, whose roles will increasingly integrate AI for routine functions, yet still require human empathy and contextual judgment. He stressed the evolving human role in the workplace, where both technical and non-technical knowledge of data and AI is crucial. According to McKinsey, the U.S. alone faces a shortage of 200,000 data analysts and scientists, alongside a need for 1.5 million executives and managers who comprehend AI and data. This underscores a universal imperative for education systems to expand data literacy beyond technical skills, preparing a workforce capable of thriving alongside AI advancements.
Expert Michael Li explains the need for training to have a better understanding of artificial intelligence and computers.
Michael Li, founder and CEO of The Data Incubator, participated in the last meeting of the Future Trends Forum, the think tank of the Bankinter Innovation Foundation, with a conference on education and the need for training in data.
Is artificial intelligence a considerable challenge for employment in the next 10 years? Michael begins his presentation by raising this question to the rest of the experts gathered, who agreed with him that it is a challenge to be taken into account. In addition, he points out, some studies show that around 50% of jobs are at risk of disappearing.
Until now, education has always been a way to apply for higher-level positions and maintain employability. Will it continue to be like this? Michael, who confesses to being optimistic, thinks so. But, as he recalls, we need a better understanding of artificial intelligence and computers.
“You have to let both humans and artificial intelligence do the things where they have a comparative advantage, economically speaking. Computers and artificial intelligence will probably be better for things like consistency, statistics… We have talked about competition without understanding, that competition factor is there, and we want to take advantage of computers for that kind of thing. Humans will be there to provide context and empathy.”
Michael gives the example of the role of doctors in the future and how some of their functions will be automated by artificial intelligence. However, he assures that the context and empathy that only humans can provide will still be lacking.
What role do humans play in the workplace and data?
How will we have to train and educate ourselves? Michael makes a distinction between:
- Technical part. In the U.S. alone, there are about 200,000 more analysts and data scientists needed than there are, according to McKinsey.
- Non-technical part. It takes one and a half million executives and managers who understand how data and artificial intelligence work. Educating yourself in data will be a universal need.
These examples highlight the need to train people in data science, and not only at a technical level, because there is an increasing demand for these professionals.
The Data Incubator
