You have a bachelor’s diploma? -Yes. Add master’s degree to get more credibility. Now you have a master’s diploma? -Yes. Add a PhD degree to get more credibility. You say you already got it? -Yes. Add a postdoc degree for more credibility. You say you did that, too? -Yes. Become a professor to get the most credibility. Wait, you are a professor now? -Yes. Now, forget about the credibility and go get a life.

Credibility…credible…You mean the thing that people “earn” by showing off their fancy certificates? Times are changing. AI starts exposing the fake credibilities already so much in academia. It also does so in industry by being used everyday by software developers and engineers to build online banking services and systems. In universities, undergrads are asked to write a scientific report to be able to graduate in their final year, and guess how the reports are written. By heavily using AI. Everything seems so smooth and homogenous. Every student seems equally-capable – the differences fade away. There is no smartest kid in the room, nor the dumbest one. There are only different bodies with the same intelectual output.

In this current era of AI, credibility is not earned, it is generated. Everything becomes indistinguishably fake. Posts written in proper English start to seem ugly, and the ones with imperfections like this one start to become ancient artifacts. We need new ways of solving “credibility-assignment” problem. Maybe we always had the wrong idea of how credibility should be assigned. Maybe having a good (scientific or non-scientific) output shouldn’t have led to getting more credibility in the first place. Instead, maybe producing a good output should lead to more credibility. Or, even further than that: maybe it should be your effort that purely defines your credibility.

What if it was the amount of effort that mattered, not whether the output was or was not desirable in terms of the goals and milestones set initially? Genuinely high-effort works cannot be of low quality. Not all long-worked scientific papers or software systems may reach the desired goals of the person doing the work or the people waiting to consume them. However, I would argue that it certainly does not necessarily mean that the work carried has low value regarding the doors it may open up in the future. The value of the work carried by a person or a group of people is not in its outcomes solely, but also in its rigor and insights discovered along the way. For what it’s worth, a paper with unsatisfactory outcomes might have prevented others to fall in the same path, or allow other to carve new paths out of the others’ (previous) deadends.

To conclude, maybe we need a new systematic way of measuring the effort and not the output. Your effort defines who you are more than your final output. Cheating in universities has become easier, because universities do not tend to measure students’ effort and the ones that do is more AI-prone when it comes to cheating.