Members of the Integrated Systems Laboratory (ISL) were among the engineering students at AI for Engineering Practice, a session run by the School of Engineering in room PKY1 of the central teaching building at the University of Phayao. It forms part of the School’s programme for preparing students before they leave for internships and co-operative education placements.
The School’s stated aim is practical rather than theoretical: students are about to spend months inside companies, and the question is less what artificial intelligence is than what it is for once there is a job to do. The session set out to give them enough grounding to use these tools during a placement, and to fit into the way a workplace actually operates.
That emphasis showed in the material. The slide the room was working from was headed “using AI for the task at hand” and listed six things under it — customising an assistant, prompting, tools, building your own GPT, working on a project, and responsible AI. The hall was full, and hands went up throughout.
The last of those six is the one that matters most to a laboratory. Engineering work is accountable: a measurement is defended, a design decision is justified, and a result that cannot be explained is not yet a result. A tool that produces an answer the student cannot account for does not meet that standard, whatever produced it. Learning where these tools help — and where using one means you no longer understand your own work — is the part of this subject a placement will test hardest.
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