This is a problem that comes up every now and then when I am asked to review a paper.

In my old field of research (robotics), papers straddled the line between creative problem solving and theoretically sound science. The general layout of all of the papers is to first provide a scientific reason that your method should work, and then present the method and any tweaks you had to make in order for the actual engineering problem to be solved.

Many times this led to a dubious scientific background and leaps of logic.

Here is an example: A paper might be about an algorithm to solve X problem. X is something that humans do naturally (for instance, grasping a delicate object without breaking it), so logically one would go to the scientific literature to find out how humans do it. The paper would then include a detailed and theoretically correct background section into the biology that governs human abilities. Then, the paper would include a big leap in logic that is not supported by the actual science, and that leap in logic would be used to justify their algorithm. Authors would state this leap as though it is an established scientific fact, when in fact the science is either unsettled or their conclusions are wrong about the biology.

The problem is that the algorithm does in fact work when tested on the engineering system (a robot, in our continuing example). It just doesn't actually have any significant resemblance to the biology that the authors claim it was based on. So really the issue isn't that the algorithm is a bad one or that the testing and data were fudged; it's that the justification of the design didn't follow from the evidence presented. If it weren't presented as though it was decided fact I wouldn't even think about it.

In addition, it is highly unlikely that, if I were to ask the authors to justify their results better, they would be able to do it—the science simply doesn't support it, but they tinkered with it enough that it works.

What would be an appropriate response here?

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    Coming in to Mechatronics (Engineering) I can tell you that there are orders of magnitude more examples of this to be found in design 'justification' in Architecture programs... Sep 7, 2022 at 9:37

2 Answers 2


It's appropriate to respond just as you have here: criticize the unfounded motivation and ask that the authors present their paper without it. For example:

the authors suggest that humans and other great apes navigate diverse terrain using wheels, however the authors do not support this assertion with appropriate citations to the literature on human physiology, and it seems to conflict with evidence that apes in fact use legs. Therefore, while their horse-drawn wheeled cart does seem like a promising logistical solution, I recommend that they remove any suggestion that this solution is biologically motivated unless the authors can provide sufficient references for their assertions.

As a neuroscientist I must say I very much sympathize with this problem, and occur it regularly on other Stack Exchange sites as people confuse what is known and useful within artificial neural networks with what is known about biological brains and neural circuits. However, while it's understandable to encounter these issues among learners in a field, it's not something that should ever make it into published papers.

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    I've never personally encountered something like this (and it's pretty unlikely in my area), but I think it might make sense if the authors say that whatever algorithm they have is inspired by some biological phenomenon, even if there is no rigorous way to derive one from the other. This is of course very different from what OP seems to describe, which looks to me like bad, misleading science.
    – tomasz
    Sep 7, 2022 at 13:02
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    I want to point out that it's not just misleading science, but it has effects outside of academia as well, as someone can then go point to this robotics paper and claim chimps are doing wheelies in the jungle, and they would have gained some ethos doing so. The fact they would have a paper, that may even have a bunch of people citing it makes it hard for the people on the ground to argue against things that are not just speculative, but flat out wrong. We see this all the time with climate change.
    – Krupip
    Sep 7, 2022 at 17:36
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    For example, oten when we see this in climate change, since there's so many different disciplines working in the field, what actually happens is someone, working on something that will help reduce energy usage, or use clean energy, will say something about a prediction that was never said by an actual climate scientist or paper, and then climate change denialists will then go use that paper as a source for saying "See, obviously the world hasn't melted by 2020, so clearly all of this is bunk!"
    – Krupip
    Sep 7, 2022 at 17:38
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    I remember reviewing a paper about a database model for doing search and query on music. The problem was that the musicology was completely flawed, in fact it was essentially dreamt up in the researcher's head. But I was relying on my own extremely limited knowledge to recognise that. So the only thing I could really do was to tell the editors that the paper needed some expert musicological input. Sep 8, 2022 at 16:29

I would just ask the authors to rewrite that part to ensure the science is correct, and state the algorithm is inspired by the biological aspects of human abilities.

This is how researchers in the bio-inspired (nature inspired) meta-heuristics research areas approach the problem; FYI, these researchers design algorithms that mimic biological processes.

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    See also: Genetic Algorithm - "a metaheuristic inspired by the process of natural selection"
    – Pharap
    Sep 8, 2022 at 19:00

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