Preventing biased code – coding with ethical considerations
Hopefully, you now have enough motivation to output code that is as unbiased and fair as possible. Here are some things to consider when aiming to create unbiased code.
Get good data
To start with, get the right data.
When training an ML model, make sure you use data that is diverse enough and encompassing enough to represent the population you’re looking to serve. If your data is skewed or incomplete, you can get bias from it [ChatGPT].
Ethical guidelines
Follow the regulations in your country and the countries in which you’re planning to deploy the code. Further to that, follow established ethical guidelines and standards, such as those offered by the Association of Computing Machinery (ACM) and the Institute of Electrical and Electronics Engineers (IEEE). Those resources can be found here, respectively: https://www.acm.org/binaries/content/assets/membership/images2/fac-stu-poster-code...
