Being Fair and Non-discriminantory

Scenario

You’re working as a software engineer at a global tech company where you're asked to develop an algorithm to streamline the hiring process, using the advanced technology to assist in identifying top talents. You’re excited about the project and start working on your algorithm to efficiently analyze resumes, coding samples, and other materials applicants submit.

After weeks of dedication, your algorithm is integrated into the company’s hiring process. It operates seamlessly, processing applications and producing results that guide hiring decisions. The initial results are promising, and you’re confident in the capabilities of the algorithm you’ve developed.

However, as time passes, you start hearing concerns and reservations about the algorithm’s outcomes. Reports suggest that qualified candidates from certain demographic backgrounds and institutes are often rejected. Digging deeper into the data, you discover that the algorithm inadvertently introduces biases, leading to differences in hiring outcomes.

Confronted with this unexpected setback, you wonder how despite your good intentions, your algorithm is displaying biases that undermine the principles of equality and inclusivity. As a responsible engineer, do you acknowledge the biases, openly address the issues with your team, and work toward rectifying them? Or do you choose to let it be, because you think it may not be that big of an issue and besides, the bias was totally unintentional?