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International Business Times UK
International Business Times UK
Technology
Vinay Patel

Youngest Self-Made Billionaire, Not Kylie Jenner, Reveals The AI Skills You Should Learn For Today's Economy

Billionaire Alexandr Wang stresses the need for mastering AI prompt engineering and tackling complex AI reasoning problems to succeed in the future economy. (Credit: Pexels)

The world's youngest self-made billionaire has shared information about the artificial intelligence (AI) abilities young people should acquire to navigate the upcoming economy.

In 2016, Alexandr Wang, a college dropout from MIT, co-founded ScaleAI, an AI startup specialising in data labelling that is valued at $14 billion. Backed by Amazon, ScaleAI propelled Wang to billionaire status at age 24. He maintains his title as the world's youngest self-made billionaire at 27, with a net worth of $2 billion.

In a discussion with Jeff Berman, CEO of WaitWhat media, and Intel's Lama Nachman, Wang responded to the query, "What are the skills you think young people need to develop today for the economy that's coming?"

Key AI Competencies For The Next Generation

In his response, Wang emphasised the importance of prompt engineering, which alludes to the skills required to craft instructions for AI chatbots. However, he noted that a more critical skill is the ability to solve the complex challenge of enabling AI to think and reason in a manner resembling human cognition over extended periods.

"I think this is something that humans will always be differentiated in... we're very good at long-form thinking and very good at thinking over very long time horizons," Wang said.

According to Wang, while AI models can effectively predict immediate outcomes, they struggle with accurately processing multiple steps in a sequence. "They usually make a mistake on the third, or fourth or fifth, reasoning step or chain of thought," he said.

Wang, recently lauded by industry peers Brian Armstrong and Elon Musk for his merit-based hiring approach, maintains that humans will possess a significant edge over AI in the realm of long-term thinking. He underscored the importance of delving deeply into these areas.

Wang identifies math, physics, and other technical subjects as prominent examples of disciplines that cultivate long-term thinking. "It's classic stuff, like doing math, doing physics, doing these technical fields is very important," he said.

"I think there are a lot of fields like economics which force you to think very long-term and think through implications many steps down that are valuable," he added.

Wang also mentioned that most existing AI models are trained on a vast majority of internet data. This observation aligns with recent statements made by Microsoft AI CEO Mustafa Suleyman, who indicated that AI systems can be trained on nearly all online content.

Wang's comments echo the findings of the World Economic Forum's 2023 Future of Jobs Report. The report predicted a surge in AI adoption by companies within the next five years (over 75 percent). This shift necessitates a new skillset, as highlighted by research from Inteliligent.com.

According to the research, nearly half (49 percent) of business leaders believe proficiency in tools like ChatGPT will hold increasing value.

AI-related jobs, classified under the broader category of computer and information technology (IT) careers, are projected to experience rapid growth, with approximately 377,500 job openings annually in the decade leading up to 2032, according to the US Bureau of Labor Statistics.

While this estimate indicates robust job growth, AI-specific skills and expertise demand will likely outstrip this number.

Essential Technical Skills for AI Jobs

A 2023 Goldman Sachs report indicated that AI technologies could significantly impact approximately 300 million jobs globally [9]. A strong foundation in technical skills is crucial to thrive in this evolving landscape. While many other skills are valuable, these technical proficiencies are particularly sought after by employers in the AI domain:

  • Technical AI Skills

  1. Prompt engineering
  2. Data science and analysis
  3. Programming languages (Julia, Python, C++, Javascript)
  4. Mathematics (statistics, algebra)
  5. Big data technologies
  6. Machine learning
  7. Cognitive learning and language processing
  8. Application programming interface (API) application
  9. Frameworks and algorithms
  • Workplace AI Skills

  1. Emotional intelligence
  2. Interpersonal skills
  3. Active learning and willingness to continue learning
  4. Innovation and creative thinking
  5. Bias detection
  6. Analytical judgment and critical thinking
  7. Flexibility and adaptability

As the AI landscape rapidly evolves, individuals equipped with a combination of technical expertise and critical thinking will be well-positioned to capitalise on emerging opportunities.

While the demand for AI talent is surging, staying updated on the latest trends and skill requirements is essential to remain competitive in this dynamic field.

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