The Abstraction Added by AI May Erode Engineering Skills, Writes Researcher

The growing role of AI and automation in software and system development may turn engineering work into more supervision than actual problem-solving, assesses Sujithra Periasamy in her article published in AI & SOCIETY. According to Periasamy, engineering expertise has traditionally been built through direct 'encounters with faults': errors were visible concretely, for example, as burnt marks on circuit boards, illogical behavior in programs, or persistent compilation errors, which were solved using tools like measuring devices, logs, and debuggers. Such activities taught cause-and-effect relationships and how systems fail. The core argument of the article is that in the current development environment, this contact with failure is becoming distant. Errors are 'handled upstream': AI-assisted management views interpret system states, and automated management layers fix fault situations. As problems filter and correct through abstraction layers, according to Periasamy, the engineer may end up observing the process rather than understanding the root cause. Periasamy suggests that the underlying issue is a misconception about how engineering competence is built: skill does not arise solely from smooth tools but from struggling with faults and learning to read system behavior. The article raises concerns that too smooth an abstraction may ultimately obscure the very cause-and-effect relationships on which technical understanding is based. Source: The vanishing engineer: how AI abstraction is de-skilling an entire generation, AI & SOCIETY.