The Challenges of Algorithm-based HR Decision-making for Personal Integrity

Organizations increasingly rely on algorithm-based HR decision-making to monitor their employees. This trend is reinforced by the technology industry claiming that its decision-making tools are efficient and objective, downplaying their potential biases. In our manuscript, we identify an important challenge arising from the efficiency-driven logic of algorithm-based HR decision-making, namely that it shifts the delicate balance between employees’ personal integrity and compliance toward favoring compliance. The reason is that algorithm-based HR decision-making may marginalize human sense-making, promote blind trust in rules, and replace moral imagination. We suggest that critical data literacy, ethical awareness, the use of participatory design methods, and private regulatory regimes within civil society can help overcome these challenges. Our paper contributes to literature on workplace monitoring, critical data studies, personal integrity and literature at the intersection between HR management and corporate responsibility.