Friday, July 19, 2024

Industrial and Organizational Psychology and Artificial Intelligence: A New Era of Work

Industrial and Organizational Psychology and Artificial Intelligence: A New Era of Work

Janpha Thadphoothon

Please cite as:

Thadphoothon, J. (2024, July 19). Industrial and organizational psychology and artificial intelligence: A new era of work [Blog post]. Retrieved from https://janpha.blogspot.com/2024/07/industrial-and-organizational.html
 

The world of work is constantly evolving, and the field of Industrial and Organizational (I/O) Psychology has always been at the forefront of understanding these changes. Traditionally, I/O Psychology has focused on core areas like recruitment, training, performance management, and employee well-being. These aspects remain crucial, but a new player has entered the field: Artificial Intelligence (AI).



From Blue Collar to Knowledge Workers: The Changing Landscape of Work

Traditionally, I/O Psychology dealt with optimizing processes for manual labor, guided by principles like Scientific Management and Taylorism. These focused on increasing efficiency and productivity for blue-collar workers. However, the modern workforce is dominated by knowledge workers, whose tasks involve creativity, information processing, and critical thinking. And as we begin to realize, AI us pretty good with these tasks.


AI: A Partner, Not a Replacement

This shift in the nature of work coincides with the rise of AI. While AI excels at automating repetitive tasks, its potential extends far beyond. AI can now assist with knowledge work, analyzing data, generating reports, and even offering creative suggestions. Here's where I/O Psychology steps back in.

The I/O Revolution in the Age of AI

As AI transforms work, I/O Psychology plays a critical role in ensuring a smooth transition. Here are some key areas of focus:

Human-AI Collaboration: I/O Psychologists can design workplaces that foster effective collaboration between humans and AI. This includes understanding how AI can complement human strengths and weaknesses. 

Reskilling and Development: New skills will be needed to thrive alongside AI. I/O Psychologists can design training programs to equip workers with these skills, ensuring they are prepared for the future of work.

The Future of Jobs: AI will undoubtedly change the job market. I/O Psychologists can help assess the impact of AI on specific job roles and suggest strategies for workplace redesign and workforce adaptation.

AI and Job Enrichment/Enlargement

AI can be a powerful tool for both job enrichment and job enlargement. Here's how:

Job Enrichment: AI would make jobs and work more fulfilling?

Freeing Up Time for Meaningful Tasks: AI can automate repetitive tasks currently done by humans. This frees up employees' time to focus on more strategic, creative, and problem-solving activities. Imagine an accountant who no longer needs to spend hours on data entry thanks to AI; they can now focus on analyzing financial trends and offering strategic advice.

Providing Real-Time Feedback and Insights: AI can analyze data and provide employees with real-time feedback on their performance. This can help them identify areas for improvement and make adjustments on the fly, leading to a more dynamic and enriching work experience.

Personalization of Work: AI can personalize tasks and workflows based on individual strengths and preferences. This can lead to a more engaging and fulfilling work experience for employees.

Job Enlargement: It seems that AI would enlarge jobs and responsibilities.

Increased Scope and Responsibility: AI can automate tasks within a job role, allowing employees to take on additional responsibilities that were previously handled by separate roles. This can create a more holistic and stimulating job experience.

Cross-Training Opportunities: As AI takes over some tasks, employees can be cross-trained on new skills needed to utilize the AI tools effectively. This can broaden their skill sets and make them more valuable within the organization.

Improved Collaboration with AI: AI can become a valuable teammate, assisting with data analysis, generating reports, and providing support. This can allow employees to focus on higher-level tasks and build new skillsets in collaboration with AI.

However, there are challenges and issues - so important - and here are some:

Loss of Skills: If AI automates too many tasks, employees may lose essential skills needed for their jobs. Addressing this through reskilling and upskilling programs is crucial.

Job Redesign: Redesigning jobs to incorporate AI effectively requires careful planning and employee input. Poorly designed jobs might lead to increased stress and workload.

The Human Element: While AI excels at tasks requiring data analysis and automation, it lacks creativity, social intelligence, and emotional intelligence. Human workers will still be vital for tasks requiring these skills.

By leveraging AI strategically, I/O Psychologists can help create a future of work where jobs are both enriching and enlarged, maximizing human potential alongside the capabilities of AI.

Job Satisfaction and AI

In I/O Psychology, we often do research on employees' job satisfaction - how happy they are working or doing their work. Now, with the AI coming so strong, we may need to incorporate AI elements into the equation. The relationship between AI and job satisfaction is complex and multifaceted. 

Benefits of AI for Job Satisfaction:

Reduced Repetitive Tasks: This is related to the idea of job enrichment. AI can automate repetitive and mundane tasks, freeing employees to focus on more engaging and stimulating work. This can lead to a sense of accomplishment and increased autonomy.

Improved Work-Life Balance: Automating tasks can save employees time, allowing them to leave work on time and reduce stress. This contributes to a better work-life balance, which can improve overall job satisfaction.

Enhanced Decision-Making: AI can analyze vast amounts of data and provide insights that humans might miss. This can empower employees to make better decisions, leading to a sense of mastery and improved performance.


Personalized Learning and Development: Working and learning go together. AI-powered learning platforms can personalize training programs based on individual needs and skill gaps. This allows employees to continuously learn and grow, keeping them engaged and motivated.

Enhanced Collaboration with AI: AI can function as a virtual assistant, handling data analysis, generating reports, and completing tasks. This can streamline workflows and free up employees to collaborate with colleagues on more strategic projects.

However, there are challenges. Here are some drawbacks of AI for Job Satisfaction:

Fear of Job Loss:  A common concern is that AI will automate jobs and lead to widespread unemployment. This fear can create anxiety and decrease job satisfaction. 

Skill Gap and Retraining Needs: Part of I/O psychology is training and development. As AI takes over some tasks, new skills will be needed to operate alongside it. Failure to provide adequate reskilling and upskilling programs can leave employees feeling unprepared and insecure.

Micromanagement and Loss of Autonomy: In some cases, AI may be used for excessive monitoring or data collection on employee performance. This can create a feeling of being micromanaged and reduce a sense of control, impacting job satisfaction. (Some firms may use AI to monitor their employees.)

Job Redesign and Change Management: Implementing AI effectively often requires redesigning jobs and workflows. Poorly implemented changes can lead to confusion, frustration, and resistance among employees.

The Human Element:  While AI excels at data analysis and automation, human interaction and emotional intelligence remain crucial. Employees may miss social interaction or find AI impersonal, potentially affecting job satisfaction.


The key to maximizing the positive impact of AI on job satisfaction lies in:

Transparent Communication:  Effectively communicating how AI will be used and its impact on jobs is essential to alleviate fear and build trust with employees.

Investment in Reskilling and Upskilling: Equipping employees with the skills needed to thrive alongside AI is crucial for job security and satisfaction.

Human-Centered Design:  Redesigning jobs and integrating AI should prioritize human strengths and create roles that are both stimulating and efficient.

Employee Participation:   Including employees in the planning and implementation of AI integration can foster ownership and acceptance of the technology.

By carefully considering these factors, organizations can leverage AI to create a future of work where jobs are not only more productive but also more satisfying for employees. 


Performance Appraisal in the Age of AI

The traditional performance appraisal process, which relies heavily on manager evaluations, is also undergoing a transformation. AI can be a valuable tool in this area, but it should be used with caution. Here's a breakdown of the potential benefits and drawbacks:

Reduced Bias: AI can analyze data objectively, potentially reducing unconscious bias that can creep into human evaluations. This can lead to fairer and more consistent performance assessments.

Data-Driven Insights: AI can analyze large datasets to identify performance trends and areas for improvement. This can provide managers with more objective data to base decisions on.

Real-Time Feedback: AI systems can offer employees continuous feedback on their performance, allowing for quicker adjustments and improved results.

Increased Efficiency: Automating routine tasks like data collection and analysis can free up managers' time to focus on providing more personalized feedback and coaching.


However, there are also potential drawbacks to consider:

Algorithmic Bias: AI algorithms are only as good as the data they are trained on. If biased data is used, the AI can perpetuate or amplify existing biases in the workplace.

Lack of Context: AI may struggle to understand the context behind performance data, such as unexpected challenges or personal circumstances. This could lead to unfair evaluations.

Employee Privacy Concerns: Monitoring employee activity through AI raises privacy concerns. Clear policies and employee awareness are crucial.

Over-reliance on Data:  Focusing solely on data points can overlook human qualities like creativity, teamwork, and communication.

Job Security Fears:  Employees may fear being replaced by AI, leading to decreased morale and performance.

Using AI for Terminations:

Ethical Considerations:  Firing decisions should involve human judgment and consideration of mitigating factors. AI should not solely determine termination. 

Transparency and Explainability:  Employees have the right to understand why they are being let go. AI-based decisions should be explainable and not shrouded in secrecy. 

Focus on Performance Improvement: Before termination, AI might be used to identify struggling employees and offer interventions to improve performance.

Overall, AI can be a valuable tool for performance assessment, but it should be used as a supplement to human judgment, not a replacement. Here are some recommendations:

Combine AI with Human Expertise:  Human managers should always have the final say in performance assessments and disciplinary actions. Working with machines may soon become a new normal, as Sundar (2020)put it:

While it might appear contradictory to rely on machines to control other machines and restore human control, it actually suggests a new kind of teamwork between humans and machines. This partnership is built on a deep understanding of how machine capabilities can both improve and potentially undermine human agency.

Focus on Positive Reinforcement: AI can be used to identify and reward high performers, fostering a more positive work environment.

Regularly Audit AI Algorithms:   Monitor AI systems for bias and ensure they are functioning correctly.


Provide Employee Training:  Educate employees about AI and how it's being used for performance evaluation. 

By implementing AI responsibly and with human oversight, organizations can create a more objective, data-driven, and ultimately fairer approach to performance management.

We Are at the Juncture: A New Era of Work Awaits

I would like to mention briefly about one of the recently conducted polls - which was conducted by Celonis in February and March 2024 among their 200,000+ LinkedIn followers. It aimed to understand how people are using AI at work. Over 5,800 people responded, indicating it was a non-probability sample (convenience sample). This means the results may not be generalizable to the entire population.

Based on the poll:

- 68% of respondents reported using AI at least occasionally at work. This suggests that AI is becoming increasingly integrated into workplaces.

Interestingly, the most common use of AI for work was for productivity purposes. This aligns with the idea that AI can automate repetitive tasks and free up human workers to focus on more complex activities.


The emergence of AI presents a fascinating juncture for I/O Psychology. By understanding the human element in this new equation – how AI can augment human capabilities and how workplaces can adapt to this collaboration – I/O Psychologists can ensure a future of work that is not only productive but also fulfilling for all.

References

Thadphoothon, J. (2022). ELT in the Age of Artificial Intelligence (AI): Working with Machines. Journal of NELTA, 27(1-2), 202–212. https://doi.org/10.3126/nelta.v27i1-2.53203

S Shyam Sundar, Rise of Machine Agency: A Framework for Studying the Psychology of Human–AI Interaction (HAII), Journal of Computer-Mediated Communication, Volume 25, Issue 1, January 2020, Pages 74–88, https://doi.org/10.1093/jcmc/zmz026

Celonis. (2024, March 13). AI Poll: 68% use artificial intelligence at work, nearly half for productivity [LinkedIn post]. Retrieved July 19, 2024, from https://www.linkedin.com/pulse/ai-poll-68-use-artificial-intelligence-work-nearly-half-productivity-rjfaf/



Janpha Thadphoothon is an assistant professor of ELT at the International College, Dhurakij Pundit University in Bangkok, Thailand. Janpha Thadphoothon also holds a certificate of Generative AI with Large Language Models issued by DeepLearning.AI. He also graduated with an MA in Industrial and Organizational Psychology from Thammasat University.

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