ICPT.HUST 2023 - 34

Research purpose:
To explore the ethical implications of AI integration in HRM practices and its potential contribution to sustainable development.
Research motivation:
The rapid advancement of AI has brought forth numerous opportunities and challenges in HRM, including privacy concerns, bias, and discrimination. However, AI also has the potential to foster a culture of ethics and sustainability in organizations, and to address non-traditional security challenges and promote economic self-reliance.
Research design, approach, and method:
This paper will conduct a literature review of the latest research on AI in HRM and its ethical implications. The review will examine the relationship between AI and the ethical dimensions of HRM, such as privacy, surveillance, bias, and discrimination. It will also discuss the role of AI in fostering a culture of ethics and sustainability within organizations, and how it can be utilized to address non-traditional security challenges and promote an independent and self-reliant economy.
Main findings:
AI in HRM raises significant ethical concerns, including privacy and surveillance concerns, the potential for bias and discrimination, and the risk of over-reliance on AI at the expense of human judgment.
AI has the potential to contribute significantly to sustainable development by optimizing resource allocation, improving efficiency, and facilitating decision-making processes. It can also foster a culture of ethics and sustainability within organizations and address non-traditional security challenges.
However, the potential negative impacts of AI on sustainable development, such as its significant energy consumption and the risk of job displacement, should not be overlooked.
Practical/managerial implications:
To harness the potential of AI in HRM while mitigating its risks, it is crucial to establish best practices and guidelines for its ethical use.
These should include defining clear goals and objectives for AI implementation, involving stakeholders in the process, ensuring data quality, continuously monitoring and evaluating AI-driven processes, and addressing ethical considerations.
Organizations must also carefully consider and address the challenges of implementing AI in HRM, such as data privacy concerns, algorithmic bias, ethical considerations, resistance to change, integration with existing systems, ensuring AI complements human decision-making, legal and regulatory compliance, and skills gap.
Keywords: AI in HRM, AI ethics, sustainable development, data privacy, algorithmic bias, regulatory compliance
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