If you're worried about AI taking your job, these careers are the safest bets, an AI politics professor says

As the pace of AI innovation accelerates, concerns about job displacement are growing. However, not all careers are equally vulnerable to automation. Baobao Zhang, an AI politics professor at Syracuse University, shared her insights on the London School of Economics' "Ballpark" podcast, identifying roles that are likely to remain safe from AI takeover for the next decade. Zhang emphasizes that hands-on trades, such as electricians, plumbers, and repair technicians, are among the safest occupations. These jobs require physical dexterity and problem-solving in unpredictable environments, making them difficult for machines to replicate. She also highlighted caregiving professions—nursing, primary school teaching, and nursery teaching—where emotional intelligence, empathy, and interpersonal skills are crucial, qualities that AI has yet to master. In addition to these fields, Zhang pointed out advanced manufacturing as an area where human oversight is still essential. Despite the rise of automation in factories, specialized roles that demand human judgment and expertise remain vital. "These positions may not be seen as prestigious, but they are indeed harder to automate," she explained. Looking ahead, Zhang noted that while choosing a resilient career path is important, adaptability will be equally critical. With the job market increasingly saturated with AI-generated resumes, she advised students in more vulnerable fields to be prepared for retraining and to leverage human connections when seeking employment. The landscape of job security in the age of AI is complex. Research from Microsoft indicates that roles heavily reliant on writing and communication, such as translators and historians, face greater exposure to automation. Conversely, professions like nursing assistants and hazardous materials workers are less likely to be affected. This view is echoed by Geoffrey Hinton, a prominent figure in AI, who argues that physical trades will fare better than many white-collar jobs. While some experts predict drastic job losses by 2030, Zhang advocates for a more measured perspective, focusing on empirical data to gauge the real impact of AI on the workforce today and in the near future.