Generative AI & employment: first impacts
What is the impact of ChatGPT on work and employment? There’s nothing better than a scientific study to discuss this, especially when it’s a study relayed by the Financial Times. The research article “The Short-Term Effects of Generative Artificial Intelligence on Employment: Evidence from an Online Labor Market” published at the end of July 2023, examines the short-term impact of generative artificial intelligence, like ChatGPT, on the employment outcomes of freelancers on a large online platform.
The impacts are already there, as the study shows, and as illustrated by the Financial Times article by John Burn-Murdoch, who precisely comments on this article. Surprisingly, high-paying jobs are considered the most exposed to automation. The study shows that freelancers like writers and graphic designers have seen a significant decrease in their work opportunities and income shortly after the launch of ChatGPT, indicating that generative AI replaces not only their work but also reduces the value of their remaining work.
Another study conducted at Harvard Business School examined the use of GPT-4 by employees of the Boston Consulting Group. Consultants using GPT-4 were significantly more productive and produced higher quality work. However, for more nuanced tasks, AI was less effective, except for those who collaborated closely with it or focused on their own areas of expertise by delegating sub-tasks to AI.
The article concludes that regulation is essential to protect workers, that multifaceted roles are less likely to be fully automated, and that to maximize the benefits of AI while avoiding its pitfalls, it should be treated as an extension of oneself, checking its outputs as we would with our own.
The expected impacts in 2024 on employment and work
We can still talk about weak signals, but very quickly, it will be much more than that. To explore the future of work in the context of HR functions, it is crucial to look at the short-term effects of generative artificial intelligence (AI), particularly the impact of language models like ChatGPT. The study provides interesting elements that can help better understand and anticipate the trends expected for 2024:
Reduction in demand for knowledge workers
The study reveals that the introduction of generative AI has led to a decrease in employment and income for freelancers in knowledge-intensive areas. This trend indicates a potential shift in labor demand, where AI can not only assist but also replace human workers in certain tasks.
Impact on high-quality service providers
Contrary to expectations, the study suggests that the provision of high-quality services, measured by past performance, does not protect against the adverse effects of AI. This discovery is crucial for HR departments in reevaluating talent management and development strategies.
Reduction in productivity gaps
The disruptive influence of AI can reduce the productivity gap between high and low-quality workers. For HR, this could mean reevaluating the workforce composition and possible restructuring of work roles to integrate AI more effectively.
Versatile technology
The paper classifies AI as a versatile technology with extensive economic and societal effects. Leaders and the HR function must consider the broader implications of AI deployment, including ethical considerations and the need for retraining programs.
Short-term effects vs. long-term effects
While the paper focuses on short-term effects, the long-term implications of AI on employment and the nature of work could be significantly different. This uncertainty requires a proactive and adaptive approach from the HR function in workforce planning and policy development.
Diversified impact across industries
The study underlines that the effects of AI are not uniform across all sectors. HR professionals should conduct industry-specific analyses to better understand and prepare for the changes that AI could bring to their particular area.
Preparing the HR function for these changes
More than ever, the HR function is at a crucial crossroads. HR must not only adapt to current challenges but also anticipate future transformations. This section details strategic recommendations for HR professionals, aiming to optimize talent management, training and development, as well as organizational ethics in this rapidly evolving context:
Investment in upskilling and reskilling initiatives
- Skills diagnosis: identify essential skills likely to be affected by AI and those that will be valued in the future, considering the complementarity between human skills and artificial intelligence.
- Customized training and development programs: design training programs tailored to the individual needs of employees, focusing on the development of critical skills such as critical thinking, creativity, and emotional intelligence, which complement the capabilities of AI.
- Partnerships with educational and technological institutions: establish collaborations with universities, training institutes, and tech companies to create advanced and relevant training programs.
Diversified talent acquisition and management strategies
- Reassessment of skill profiles: redefine the skill profiles sought, emphasizing abilities such as adaptability, complex problem solving, and the capacity to work in synergy with AI technologies.
- Proactive talent management strategies: implement talent management strategies that anticipate changes in the company’s needs, focusing on identifying and developing internal talents for future roles.
Development of ethical AI usage policies
- Ethical framework for AI in HR: establish a clear ethical framework for AI use, addressing issues such as data privacy, non-discrimination, and transparency of algorithms.
- Training on ethical and legal principles: offer regular training to employees and managers on the ethical and legal aspects of AI use, emphasizing the importance of respecting standards and ethical values.
Improvement of AI culture and skills
- AI awareness and training programs: implement educational programs to enhance employee understanding of AI, focusing on how AI can be used to improve performance and innovation.
- Encouragement of experimentation and innovation: create an environment conducive to experimentation with AI technologies, encouraging employees to explore and innovate in their respective areas using these tools.
Monitoring long-term trends
- Continuous Strategic Intelligence: set up a monitoring system to track technological developments and labor market trends, to anticipate changes and prepare the organization to adapt effectively.
- Scenario planning and future preparedness: engage the organization in scenario planning for different possible futures related to AI, preparing adaptive strategies for various eventualities.
By integrating these recommendations, the HR function can play a central role in navigating through the rapidly evolving AI landscape, ensuring that the organization and its employees are well prepared and equipped to meet the challenges and seize the opportunities of this new technological era.
Some thinkers who had anticipated these trends
While this revolution may seem surprising to most people, great thinkers have already pondered the subject over the past fifty years. It is essential to draw from perspectives in sociology, economics, and philosophy. These disciplines offer crucial theoretical frameworks for understanding and interpreting the dynamic changes induced by AI.
The work of iconic figures such as Émile Durkheim and Max Weber in sociology, Gary Becker and Joseph Stiglitz in economics, and Martin Heidegger and Marshall McLuhan in the philosophy of technology, provide indispensable insights into the transformation of professional roles, the valuation of skills and information, as well as the ethical and existential implications of AI in the workplace. Exploring their theories can help us more deeply grasp how AI is redefining our relationship to work and technology in contemporary society.
Sociology of work
- Émile Durkheim
- Solidarity and division of labor: Durkheim explores the transition from mechanical solidarity to organic solidarity in modern societies. This transition, characterized by an increasingly complex division of labor, can be compared to the integration of AI, which changes the structure of professional roles and the nature of social interactions at work.
- Anomy and social change: Durkheim’s notion of anomie, or the absence of clear social norms, can be relevant for understanding the disorientations and ethical challenges posed by the rapid introduction of AI into the workplace. - Max Weber
- Rationalization and bureaucracy: Weber’s theory on rationalization and the development of bureaucratic structures can be applied to the automation and increased efficiency brought about by AI. This raises questions about potential dehumanization and the loss of individual qualities within organizations.
- Professional ethics: Weber also studied professional ethics and the role of work in individual life, themes relevant to examining how AI redefines values and attitudes towards work.
Labor economics
- Gary Becker
- Human capital: Becker revolutionized the understanding of human capital, emphasizing education, training, and skills. In a world of work influenced by AI, his analysis could help understand how investing in human capital remains crucial, even when some skills become obsolete due to automation.
- Investment in education and training: The implications of continuous investment in education and training in a context where AI changes the nature of work. - Joseph Stiglitz
- Information asymmetries: Stiglitz explored how information asymmetries influence markets. Applying this theory to the AI labor market could reveal how unequal access to technological information and understanding of AI can create new inequalities in the workplace.
- Labor market and public policies: How his ideas on public policies could guide the development of strategies to manage career transitions and labor market disruptions due to AI.
Philosophy of technology
- Martin Heidegger
- Technology and being: Heidegger’s view of technology as a form of “enframing” (Gestell) offers a framework for understanding how AI can transform human perception of reality and our way of interacting with the world.
- Question concerning technology: His ideas on how technology reveals the world in a specific way, leading to a deeper understanding of the ethical and existential implications of AI. - Marshall McLuhan
- Media and society: McLuhan’s theories on the impact of media on society can be extended to AI, examining how technologies transform modes of communication and social interactions within organizations.
- The medium is the message: This idea can be used to explore how AI, as a “medium”, fundamentally changes the nature of work, communication, and human interaction.
By combining these sociological, economic, and philosophical perspectives, we can gain a richer and more nuanced understanding of the complex ways in which artificial intelligence is reshaping the socio-economic landscape.
Conclusion
As we stand at the crossroads of innovation and transformation, early studies are already shedding light not only on the challenges but also on the unprecedented opportunities offered by generative AI in the world of work. These revelations highlight an inevitable truth: AI is redefining the nature of employment and the skills valued in our modern society. However, rather than seeing it as a threat, we must embrace it as an invitation to evolve.
The HR function, in particular, is at the forefront of this revolution. It has the power and responsibility not only to navigate these uncharted waters but also to actively shape a future where AI and humans coexist in harmony. By learning from visionary thinkers and adopting proactive strategies of upskilling, reskilling, and ethics, the HR function can turn these challenges into opportunities for a more resilient, adaptable, and innovative workforce.
Our future of work will not be determined by AI alone, but by our ability to intelligently integrate this technology into our work systems, valuing and enhancing unique human skills. By embracing change and adopting a holistic perspective, we can not only survive but thrive in this new era. Once again, if it needs to be demonstrated, the choices we will make soon will determine our future and that of our children.
References
Becker, G. S. (1964). Human capital: A theoretical and empirical analysis, with special reference to education. New York: Columbia University Press.
Durkheim, E. (1893). De la division du travail social. Paris: Félix Alcan.
Durkheim, E. (1897). Le suicide: Étude de sociologie. Paris: Félix Alcan.
Heidegger, M. (1954). Die Frage nach der Technik. In Vorträge und Aufsätze (pp. 9–40). Pfullingen: Günther Neske.
Heidegger, M. (1977). The question concerning technology, and other essays. New York: Harper & Row.
Hui, X., Reshef, O., & Zhou, L. (2023). The Short-Term Effects of Generative Artificial Intelligence on Employment: Evidence from an Online Labor Market. SSRN online. http://dx.doi.org/10.2139/ssrn.4527336
McLuhan, M. (1964). Understanding media: The extensions of man. New York: McGraw Hill.
McLuhan, M. (1962). The Gutenberg galaxy: The making of typographic man. Toronto: University of Toronto Press.
Stiglitz, J. E. (2002). Information and the change in the paradigm in economics. American Economic Review, 92(3), 460–501.
Weber, M. (1922). Economy and society: An outline of interpretive sociology. (G. Roth & C. Wittich, Eds.). Berkeley: University of California Press.
Weber, M. (1905). The Protestant ethic and the spirit of capitalism. (T. Parsons, Trans.). New York: Scribner.
AI Assistance Statement
[Article written on November 12, 2023, by Jeremy Lamri with the support of the Open AI GPT-4 algorithm for about 10%. Images created with Adobe Firefly 2 Beta, all rights reserved, 2023].
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