Andrew Ng: AI Will Not Cause Job Apocalypse, Software Engineers Still in Short Supply
Former Baidu Chief Scientist and founder of DeepLearning.AI, Andrew Ng, stated in an interview with The Economist that there is currently a shortage of software engineers, and there is also high demand for marketing, sales, and operations personnel who understand how to use AI.
He directly refuted predictions of mass unemployment due to AI, saying, "I don't see any realistic path to the so-called 50% unemployment or people protesting in the streets." Ng pointed out that AI can only automate certain tasks within a job, and the remaining work still requires human effort. Early data has not shown the severe employment shocks that were previously feared.
Using software engineering as an example, he noted that this field is the most visibly affected by AI, yet hiring demand remains strong, with excellent engineers busier than ever. The real challenge is equipping people with new job skills, rather than just teaching them to use AI tools. University curricula are lagging behind and failing to match current employer needs.
This statement is opinion-driven, emphasizing the automation of certain tasks rather than the overall disappearance of jobs; the beneficiaries are professionals who can integrate AI into specific workflows, while those under pressure are individuals who continue to work in the traditional manner of 2022 or rely solely on conventional educational paths, as the complementary effect increases the value of remaining human tasks.
Source: Public Information
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Ng has long advocated for AI education and practical application, having co-founded Google Brain and Coursera, and has repeatedly pointed out that hiring demand in fields like software engineering, which are most affected by AI, has not decreased; instead, there is a shortage of AI-related skills. His approach emphasizes compensating for the lag in university curricula through online learning and rapid iteration.
On the capital front, he is focusing on AI engineering skills training and application development tools, motivated by the goal of transforming AI from automating certain tasks into enhancing productivity, thereby increasing rather than decreasing job demand due to the rising value of remaining human work.
Drawing a parallel to the transition from punch cards to keyboard terminals, where programmers continued to be hired, we are currently in a phase of re-pricing from the narrative of "AI replacing jobs" to "AI changing task structures"; compared to predictions of mass unemployment, the automation of certain tasks makes complementary work more valuable.
Essentially, this represents a localization of technological substitution: the impact of AI on employment is primarily reflected in the automation of tasks rather than the overall disappearance of jobs; the mechanism is that most jobs consist of both automatable standardized parts and remaining parts that require judgment and coordination, with the latter's value increasing due to the efficiency gains from the former, thus maintaining or expanding demand for skilled workers.
ABAB News · Cognitive Law
- AI performs part of the tasks, humans perform the remaining part
- Skills gap is more realistic than unemployment
- Complementary effects elevate the value of human work.