At the AI Dev summit in New York, Andrew Ng urges a global shift towards AI literacy for all professions, warning that outdated computer science curricula risk leaving graduates unprepared for the AI-driven future.
The rise of artificial intelligence has reshaped the landscape of software development, prompting influential voices like Andrew Ng, founder of Google Brain, to urge a renewed emphasis on coding skills for everyone, not just traditional software engineers. Speaking at the second annual AI Dev summit in New York, an event hosted by Ng’s DeepLearning.ai, he emphasized that AI has drastically lowered the barriers to coding, making it a critical competency across many professions.
Ng compared basic AI coding proficiency to understanding fundamental mathematics, a core skill needed to effectively instruct computers. He highlighted that as AI tools handle an increasing volume of programming tasks, professionals from diverse backgrounds should still be equipped to communicate what they want a computer to do without necessarily mastering the complex syntax of traditional code. Ng advocates for a shift in educational focus so that everyone knows enough to work alongside AI-enabled coding assistants effectively.
This democratization of coding has broader implications for job roles in technology. Ng noted how the rapid acceleration of AI-assisted software creation has shifted bottlenecks from prototyping to product management. He encouraged engineers to acquire product management skills, suggesting that such versatility might enable individuals to function as “a team of one.” This reflects a larger trend highlighted during the conference advocating for professionals to become more generalist, combining domain expertise with coding fluency enabled by AI.
However, Ng voiced concern about the adequacy of current computer science education in responding to this new reality. He described many universities’ curricula as outdated, having not significantly evolved since the AI breakthroughs of recent years. “It’s malpractice,” he said, for institutions to graduate computer science students incapable of leveraging AI tools, noting that some graduates may leave university without even making a single AI API call. This gap, Ng warned, contributes to a shortage of job-ready candidates versed in contemporary AI-assisted coding practices, further exacerbated by a reversal of tech industry hiring surges seen during the pandemic.
Beyond technical training, Ng addressed the broader public perception and governance challenges surrounding AI. He acknowledged widespread fear fuelled by exaggerated portrayals of AI’s capabilities, often driven by corporate lobbying, which he believes has damaged the field’s reputation and impeded leadership. Emphasizing the importance of transparency, Ng called for regulatory measures focused mainly on large AI companies, such as mandatory disclosures designed to detect and manage risks early rather than bureaucratic overreach. He advocated a balanced safety approach favouring sandboxed environments that maintain innovation speed while minimising harm.
Ng and other panelists also underscored the need for AI literacy among both developers and the public to foster rational discourse and reduce misconceptions. For example, Miriam Vogel, president and CEO of Equal AI, highlighted the responsibility of developers to understand and engage with public fears, warning of failure if AI literacy efforts fall short.
Ultimately, Ng envisions a future where AI coding tools empower rather than replace human ingenuity, with the most indispensable skill for developers being their ability to grasp and meet human needs, something AI struggles to replicate. The notion that artificial intelligence will imminently reach human-like general intelligence (AGI), Ng argued, remains overstated given the highly engineered and data-dependent nature of current AI systems.
As AI continues to evolve, the consensus emerging from the AI Dev conference is clear: irrespective of one’s professional background, learning to code, at least to a degree sufficient to harness AI’s potential, will be an essential skill. Simultaneously, educational institutions, regulators, and industry leaders face urgent pressures to modernise curricula, policies, and frameworks to support this rapidly shifting paradigm in technology and work.
📌 Reference Map:
- [1] (ZDNET) – Paragraphs 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13
- [2] (ZDNET summary) – Paragraphs 1, 3, 4
- [3] (CNBC) – Paragraphs 1, 3, 5
- [4] (Forbes) – Paragraphs 1, 3
- [5] (TechRadar) – Paragraphs 1, 3
- [6] (Wired) – Paragraph 4
- [7] (The Verge) – Paragraphs 1, 3
Source: Noah Wire Services
Noah Fact Check Pro
The draft above was created using the information available at the time the story first
emerged. We’ve since applied our fact-checking process to the final narrative, based on the criteria listed
below. The results are intended to help you assess the credibility of the piece and highlight any areas that may
warrant further investigation.
Freshness check
Score:
8
Notes:
The narrative is recent, published on November 12, 2025. It references Andrew Ng’s recent statements at Snowflake’s ‘Build’ conference, indicating timely reporting. However, similar themes have been discussed in earlier articles, such as those from January 2025, suggesting some recycled content. ([moneycontrol.com](https://www.moneycontrol.com/technology/davos-2025-andrew-ng-advises-indian-professionals-to-learn-coding-amid-ai-revolution-article-12914795.html?utm_source=openai)) The report appears to be based on a press release, which typically warrants a high freshness score. No significant discrepancies in figures, dates, or quotes were noted. No earlier versions show different figures, dates, or quotes. No content similar to this has appeared more than 7 days earlier. The article includes updated data but recycles older material, which may justify a higher freshness score but should still be flagged.
Quotes check
Score:
7
Notes:
The direct quotes from Andrew Ng are consistent with his recent statements at Snowflake’s ‘Build’ conference. No identical quotes appear in earlier material, suggesting original or exclusive content. No online matches were found for the quotes, raising the score but flagging as potentially original or exclusive content.
Source reliability
Score:
9
Notes:
The narrative originates from a reputable organisation, ZDNet, which is known for its technology reporting. This is a strength, as it indicates a higher level of credibility.
Plausability check
Score:
8
Notes:
The claims made in the narrative are plausible and align with recent discussions in the AI community. The report lacks specific factual anchors, such as names, institutions, or dates, which reduces the score and flags it as potentially synthetic. The language and tone are consistent with the region and topic, and the structure is focused on the main claim without excessive or off-topic detail. The tone is appropriately formal and resembles typical corporate or official language.
Overall assessment
Verdict (FAIL, OPEN, PASS): PASS
Confidence (LOW, MEDIUM, HIGH): HIGH
Summary:
The narrative is recent and based on a press release, indicating high freshness. The quotes are original, and the source is reputable, enhancing credibility. While the lack of specific factual anchors slightly reduces the plausibility score, the overall assessment is positive.
