If you have a child about to enter university, you might be anxiously wondering, "What major should my child study so they won't be replaced?" When asked this question this week, NVIDIA CEO Jensen Huang gave a concise answer: "I don't think what they study is important. All the things that were important in the past will still be important in the future."
He argues that instead of hiding in a subject that AI cannot touch, it is better to learn how to use AI to deepen any field of study.
AI can't do storytelling for you.
In the interview, Jensen Huang named several fields that he believes will remain valuable in the AI era: news, narrative, art, and design. At first glance, this list seems to contradict the mainstream market logic that "learning AI means safety."
His reasoning lies in the nature of a skill. Taking journalists as an example, he said that the best interviewers not only do their homework, but also "focus on the present, listen carefully, and respond flexibly."
These three actions, taken together, actually describe a highly contextualized judgment—knowing when to ask follow-up questions, when to remain silent, and when a glance is more powerful than ten questions. AI can analyze transcripts and search for background information, but it cannot perceive the pause when an interviewee's tone suddenly becomes low, nor can it determine whether that silence is an avoidance or the brewing of a true statement.
"The ability to tell stories will be just as important now as it will be in the future." This is one of the few positions that Huang Jen-hsun directly asserted in this interview.
Therefore, he believes that there is no need to worry about "which subject to choose" first. Instead, one should first put aside one's existing passion, whether it is literature, biology, music, or engineering, and then ask one question: How far can AI push the learning speed, how far can it hone skills, and how far can it bring meaning to life on this path?
If you change the subject of the question from "What should I avoid?" to "What can I amplify?", the entire answer structure will be rewritten.
Does AI make people dumber? He directly refuted this hypothesis.
Another concern surrounding AI is that "humans will degenerate due to over-reliance on AI." In this interview, Jensen Huang challenged this assumption.
His argument follows a historical analogy: the rise of every major technological wave ultimately strengthens, rather than suppresses, human ambition. He doesn't use abstract theories, but rather pulls this logic back to the PC era: those who refused to learn how to use personal computers were the ones ultimately replaced; those who learned were thus able to access jobs previously unavailable.
The same principle applies today: accountants who can't use Excel will lose to those who can; finance professionals who can't use AI-assisted analysis will lose to their peers who know how to let AI run models and focus on interpreting the results themselves. The tools may differ, but the logic remains the same.
Applying this analogy to the AI era, it becomes his widely circulated statement: "You won't lose your job because of AI, you'll only lose your job because of people who know more about using AI than you."
Jensen Huang's assessment is that after AI automates the execution level of many tasks, it will push humans to higher-level tasks, namely those that require judgment and creativity. This is a discussion of "changing the nature of work," not "jobs disappearing."
Related reports
An open letter from a computer science professor: What kind of world am I sending my students into?
