Claims that artificial intelligence (AI) could soon replace computer scientists are deeply misguided, according to the latest research published in The Conversation. As anxieties rise about the role of AI in the future of work, particularly in technical professions, this new analysis by a leading academic in the field emphasizes that computer science expertise will remain indispensable for years to come (The Conversation).
The recent surge of generative AI technologies, such as language models and coding assistants, has sparked widespread speculation – including among prominent economists and secondary school advisors – that computer science degrees may be rendered obsolete. These narratives have gained so much traction that some Thai students are reportedly being discouraged from pursuing computer science or software engineering, with fears that AI will make these careers redundant.
However, the latest research challenges this perception on both technical and practical grounds. Much of the pessimism, the report argues, originates from individuals outside the domain of computer science who may not fully grasp the breadth and depth of the profession. While AI can assist with certain code-writing tasks, true computer science involves a wide array of skills, including designing complex systems, developing new programming languages, securing infrastructures, and validating systems for correctness – areas where AI currently falls far short.
AI excels at predicting outcomes and generating content by remixing existing information. It can boost productivity by summarizing, formatting, and refactoring code, but does not possess genuine reasoning, creativity, or contextual awareness. Unlike humans, AI cannot care, desire, or truly innovate. These limitations are especially critical in scenarios that demand adaptability, trust, and oversight.
The research identifies 10 core reasons why AI cannot replace human computer scientists any time soon, each demonstrating the unique human expertise and judgment required for high-stakes technical work. These reasons include:
- Adapting financial algorithms to changing economic realities, which demands both technical ability and market acumen.
- Troubleshooting cloud service failures at scale, which requires contextual analysis beyond pattern recognition.
- Rewriting code for quantum computers, a task which lacks the extensive historical data upon which AI depends.
- Architecting and securing entirely new operating systems, which involves innovation and thorough testing.
- Developing energy-efficient AI infrastructure, which means inventing new solutions rather than just optimizing existing ones.
- Engineering embedded control software for critical systems (e.g., nuclear plants), where safety and reliability are paramount.
- Validating safety in surgical robotics, under unpredictable real-world conditions.
- Designing cybersecurity protocols for emerging threats, blending cryptography, behavioral science, and system architecture.
- Auditing and refining AI-powered healthcare diagnostics, where trust and accountability are critical.
- Creating the next generation of safe, controllable AI – a fundamentally human responsibility.
These examples highlight not only the current limits of AI, but also the enhanced importance of computer science in an era when digital technology shapes every aspect of society. In prior periods of industrial revolution, fears of automation were often mirrored by eventual surges in demand for technical and engineering skills. Far from being eliminated, experts in operating, improving, and advancing technology became more vital than ever.
The author of the analysis further explains, “Whenever we face an entirely new problem or layer of complexity, AI alone will not suffice for one simple reason: it depends entirely on past data.” Put another way, the true value of computer scientists lies in their ability to innovate, to build new frameworks for unpredictable challenges, and to lead the ongoing evolution of AI – rather than being mere code typists.
In Thailand, where the digital economy is growing rapidly and the government has identified advanced technology skills as strategic priorities (Thailand 4.0 policy – Thai government), discouraging young people from computer science because of AI fears could have damaging long-term consequences. Many of the country’s most promising tech startups, digital financial platforms, and public health initiatives rely on a continuous pipeline of high-level technical talent. Thai tech educators, industry leaders, and policy officials typically urge students to learn how to work with AI instead of fearing it, emphasizing the value of human-AI collaboration.
Globally, these concerns are echoed by major technology firms and education think tanks. For example, LinkedIn has reported that rather than shrinking, the core responsibilities of computer science roles are expanding in the AI era, demanding even more technical leadership and cross-disciplinary knowledge (LinkedIn Economic Graph). Meanwhile, job advertisements for the much-hyped role of “prompt engineer” (where humans craft AI inputs) have become vanishingly rare, illustrating that breadth of real-world problem-solving – not rote interaction with AI – is where lasting value lies (Wired).
Some experts point out that AI’s limitations are not simply temporary, but stem from its fundamental nature as a data-driven system. Current forms of generative AI cannot generate entirely new concepts, understand the broader context, or provide trust and accountability. A computer science academic cited in the report notes, “The only scenario in which we might not need computer scientists is if we reach a point where we no longer expect any new languages, systems, tools, or future challenges. This is vanishingly unlikely.”
The history of technological change suggests that new tools rarely eliminate domains entirely; instead, they shift the skills required for success. During the industrial revolution, technical skills and the ability to innovate became the most in-demand, not the least. Today, as Thailand pushes for a digital leap under initiatives like “Smart City” and tech-driven tourism and healthcare programs, the country’s future will depend on nurturing more – not fewer – homegrown computer science experts (Ministry of Higher Education, Science, Research and Innovation – Thailand).
Looking ahead, the report argues for dispelling misleading advice that AI can make computer science obsolete. Indeed, those who design, build, and safeguard the digital architecture of society are more essential than ever before. Instead of steering students away from these careers, educators and policymakers should deepen young Thais’ understanding of what computer science really means: tackling unpredictable problems, collaborating with machines, and innovating for the common good.
For Thai students and families, the message is clear. Don’t let fears about AI’s rise undermine your ambitions. If anything, focus on developing the kind of creative, adaptable, and ethical computer science skills that AI cannot replicate. Continuous learning, cross-disciplinary connections – such as combining computer science with business, health, or the arts – and a commitment to lifelong upskilling will help Thai graduates stay ahead in a rapidly changing economy.
As with all sectors influenced by technological disruption, those who thrive will be people with the confidence and skills to work alongside new tools, while also thinking beyond them. The future of computer science in Thailand – and around the world – belongs to innovators, not imitators.
To explore this further, Thai readers are encouraged to seek information from reputable sources, attend career seminars held by universities and industry groups, and experiment with AI tools to understand their practical limitations firsthand. By doing so, a new generation can ensure Thailand not only keeps pace with digital change, but helps lead it.
Sources:
AI won’t replace computer scientists any time soon – here are 10 reasons why – The Conversation
Thailand 4.0 policy – Thai government
LinkedIn Economic Graph
Wired – The Prompt Engineer Is Dead. Long Live the Prompt Engineer
Ministry of Higher Education, Science, Research and Innovation – Thailand