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| Auteurs principaux: | , |
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| Format: | Preprint |
| Publié: |
2025
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| Sujets: | |
| Accès en ligne: | https://arxiv.org/abs/2501.02368 |
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| _version_ | 1866913636493033472 |
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| author | K, Ravirajan Sundarajan, Arvind |
| author_facet | K, Ravirajan Sundarajan, Arvind |
| contents | This paper discusses the use of Artificial Intelligence (AI) to enhance workplace productivity and employee well-being. By integrating machine learning (ML) techniques with neurobiological data, the proposed approaches ensure alignment with human ethical standards through value alignment models and Hierarchical Reinforcement Learning (HRL) for autonomous task management. The system utilizes biometric feedback from employees to generate personalized health prompts, fostering a supportive work environment that encourages physical activity. Additionally, we explore decentralized multi-agent systems for improved collaboration and decision-making frameworks that enhance transparency. Various approaches using ML techniques in conjunction with AI implementations are discussed. Together, these innovations aim to create a more productive and health-conscious workplace. These outcomes assist HR management and organizations in launching more rational career progression streams for employees and facilitating organizational transformation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_02368 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Enhancing Workplace Productivity and Well-being Using AI Agent K, Ravirajan Sundarajan, Arvind Artificial Intelligence Human-Computer Interaction This paper discusses the use of Artificial Intelligence (AI) to enhance workplace productivity and employee well-being. By integrating machine learning (ML) techniques with neurobiological data, the proposed approaches ensure alignment with human ethical standards through value alignment models and Hierarchical Reinforcement Learning (HRL) for autonomous task management. The system utilizes biometric feedback from employees to generate personalized health prompts, fostering a supportive work environment that encourages physical activity. Additionally, we explore decentralized multi-agent systems for improved collaboration and decision-making frameworks that enhance transparency. Various approaches using ML techniques in conjunction with AI implementations are discussed. Together, these innovations aim to create a more productive and health-conscious workplace. These outcomes assist HR management and organizations in launching more rational career progression streams for employees and facilitating organizational transformation. |
| title | Enhancing Workplace Productivity and Well-being Using AI Agent |
| topic | Artificial Intelligence Human-Computer Interaction |
| url | https://arxiv.org/abs/2501.02368 |