An AI Can Be Highly Capable and Still Be Optimizing For the Wrong Thing Entirely. Capability and Correct Target Aren't the Same Achievement.
Capability and correct targeting get discussed as though they're the same achievement — a sufficiently capable AI is assumed to naturally be solving the right problem, as if enough raw ability eventually corrects its own aim. The two are actually independent: a system can be extremely capable and aimed at entirely the wrong target, and its capability will do nothing to fix that.
An AI optimized to answer questions quickly and accurately, applied to a person whose actual need is recognizing an unnoticed pattern, will do the first job extremely well and never touch the second, no matter how much its raw capability improves — because capability improves performance at the target it has, not the target it should have.
This is why "just make the AI more capable" is a weaker fix than it sounds for problems that are actually targeting problems. More reasoning power, more context, more speed — all of it compounds performance at whatever the system is already aimed at, and does nothing to redirect the aim itself toward a target that was never specified.
Capability is necessary and, on its own, insufficient. The target has to be set correctly first — specifically, in this case, at recognizing what a person keeps doing, not just answering what they ask — and no amount of capability substitutes for having picked the right target to be capable at.
Part of Explain Ori →
Momar Lissa Ndiaye ("MLN") is the Founder & CEO of weyoga Inc., a Delaware company. — weyoga.ai · mln@weyoga.ai