How can avoid people using my code for evil? <p>I'm not sure if this is quite the right place, but it seems like a decent place to ask.</p> <p>My current job involves manual analysis of large data sets (at several levels, each more refined and done by increasingly experienced analysts). About a year ago, I started developing some utilities to track analyst performance by comparing results at earlier levels to final levels. At first, this worked quite well - we used it in-shop as a simple indicator to help focus training efforts and do a better job overall.</p> <p>Recently though, the results have been taken out of context and used in a way I never intended. It seems management (one person in particular) has started using the results of these tools to directly affect EPR's (enlisted performance reports - \ it's an air force thing, but I assume something similar exists in other areas) and similar paperwork. The problem isn't who is using these results, but how. I've made it clear to everyone that the results are, quite simply, error-prone.</p> <p>There are numerous unavoidable obstacles to generating this data, which I have worked to minimize with some nifty heuristics and such. Taken in the proper context, they're a useful tool. Out of context however, as they are now being used, they do more harm than good.</p> <p>The manager(s) in question are taking the results as literal indicators of whether an analyst is performing well or poorly. The results are being averaged and individual scores are being ranked as above (good) or below (bad) average. This is being done with no regard for inherent margins of error and sample bias, with no regard for any sort of proper interpretation. I know of at least one person whose performance rating was marked down for an 'accuracy percentage' less than one percentage point below average (when the typical margin of error from the calculation method alone is around two to three percent).</p> <p>I'm in the process of writing a formal report on the errors present in the system ("Beginner's Guide to Meaningful Statistical Analysis" included), but all signs point to this having no effect.</p> <p>Short of deliberately breaking the tools (a route I'd prefer avoiding but am strongly considering under the circumstances), I'm wondering if anyone here has effectively dealt with similar situations before? Any insight into how to approach this would be greatly appreciated.</p> <p>Update: Thanks for the responses - plenty of good ideas all around.</p> <p>If anyone is curious, I'm moving in the direction of 'refine, educate, and take control of interpretation'. I've started rebuilding my tools to try and negate or track error better and automatically generate any numbers and graphs they could want, with included documentation throughout (while hiding away as obscure references the raw data they currently seem so eager to import to the 'magical' excel sheets).</p> <p>In particular, I'm hopeful that visual representations of error and properly created ranking systems (taking into account error, standard deviations, etc.) will help the situation.</p>