Kelley’s case in particular raises the question, what if whistle-blowing was part of one’s job description? What if every organization, particularly those in highly regulated industries, explicitly created a whistle-blower position? The job seems essential, yet applicants might be scant and coworkers might view them similarly to the childhood schoolmate who reminds the teacher about the homework assignment.
The position’s social, reputational, and emotional risks thus make whistle-blower the perfect job for a robot. Robots—and algorithms—largely lack the “hot” social and emotional attributes that commonly (and, often, unfairly) litter portrayals of many whistle-blowers—self-interest, revenge, spite, disloyalty, betrayal, and resentment. At the same time, robots are proficient at “cold” skills necessary for diligent evaluation and inspection of organizational errors—calculation, routinization, automation, and consistency.
When human colleagues raise questions about improper safety precautions, fraudulent financial behavior, or governmental abuse of resources, we ponder their motives, which then color our interpretation of the issues they raise. Computers, however, cannot have motives. They cannot be self-interested, disgruntled, or disloyal (if we don’t program them to be that way), and therefore they offer a more objective eye for potential organizational violations. We trust Microsoft Word’s spellcheck to instruct us on word hyphenation whereas we might view a human editor’s same instruction as meddling or conceited. We abide by our car’s beeping seatbelt alarms to buckle up whereas we might view the same suggestion from a family member as overbearing. It is not far-fetched to imagine humans would also respond more favorably to a computer specifically designed to identify organizational failures than to a human identifying the same issues.