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The Challenges of Algorithm-Based HR Decision-Making for Personal Integrity.

Ulrich Leicht-Deobald1,2, Thorsten Busch2, Christoph Schank2,3

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Algorithm-based HR tools can reduce employee personal integrity by prioritizing compliance. Critical data literacy, ethical awareness, and participatory design can mitigate these risks in workplace monitoring.

Keywords:
Algorithm-based decision-makingCritical algorithm studiesMoral imaginationPersonal integrityWorkplace monitoring

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Area of Science:

  • Human Resources Management
  • Critical Data Studies
  • Workplace Ethics

Background:

  • Organizations increasingly use algorithm-based systems for HR decision-making and employee monitoring.
  • The technology sector promotes these tools as efficient and objective, often overlooking inherent biases.
  • This reliance raises concerns about the balance between employee personal integrity and organizational compliance.

Purpose of the Study:

  • To identify challenges posed by efficiency-driven, algorithm-based HR decision-making.
  • To explore the potential negative impact on the balance between personal integrity and compliance.
  • To propose solutions for mitigating these challenges.

Main Methods:

  • Literature review on workplace monitoring, critical data studies, and HR management.
  • Analysis of the efficiency-driven logic in algorithm-based HR decision-making.
  • Conceptual framework development for addressing identified challenges.

Main Results:

  • Algorithm-based HR decision-making, driven by efficiency, may erode employee personal integrity by favoring compliance.
  • Potential biases in these systems can create an imbalance, prioritizing organizational needs over individual rights.
  • Existing literature often underemphasizes the impact on personal integrity.

Conclusions:

  • Critical data literacy and enhanced ethical awareness are crucial for employees and organizations.
  • Participatory design methods and private regulatory regimes can help rebalance integrity and compliance.
  • Further research is needed at the intersection of HR, corporate responsibility, and data ethics.