Generative AI’s Real-World Impact on Job Markets – Newsroom | University of St. Thomas

Generative artificial intelligence (gen AI) is now an increasing concern throughout the world, with numerous sectors buzzing about its potential and the associated concerns about job displacement. This introductory examination will look at what gen AI is, its capabilities, and the causes for these developing worries. We will specifically look at how gen AI affects men and women differently, as well as if it has a disproportionate influence on people of color and minorities.

Understanding generative AI

Gen AI, a subclass of artificial intelligence, specializes in creating content, images, music and having human-like conversations. Computer-generated art and music have their origins in the mid-20th century, though the earliest examples were quite primitive. From the late 20th to the early 21st century, the field advanced much thanks to the advent of neural networks and deep learning. PixelCNN and WaveNet enable the generation of complex data sequences such as natural language and audio waveforms, whereas transformer-based architectures such as OpenAI’s GPT (Generative Pre-Trained Transformer) have significantly improved the ability to generate coherent and contextually relevant text.

In practice, gen AI is altering several industries with its diverse applications. In manufacturing, it improves design efficiency, predicts maintenance requirements, and guarantees strong quality control. It aids in the production, optimization and testing of software code. Financial services gain from its ability to develop investment plans, produce compliance documentation and improve client-investor interactions. Gen AI is critical in the media and entertainment sectors for content production, event highlighting and content management, enhancing both creative and decision-making processes.

As gen AI evolves, it is critical to consider its possible influence on diverse demographic groups to ensure that benefits are delivered equally while limiting any negative consequences on the workforce and society. The purpose of the article is to look beyond the initial enthusiasm about gen AI and objectively assess how it is affecting labor markets, positively and negatively. By examining its practical influence, we want to gain a better grasp of the potential and challenges that lie ahead in this new era of artificial intelligence.

The introduction of generative AI has significant consequences for labor markets across a variety of industries. This technology has the potential to increase efficiency and create new possibilities, but it also poses considerable dangers of job displacement, particularly in certain industries and positions.

The influence of AI on jobs highlights worries about job displacement, underlining the critical need for retraining. It emphasizes the importance of responding to technological advancements through continuing education, highlighting AI’s dual function in undermining existing professions while also increasing the need for new skills for future employment. Generative AI, in particular, excels at automating non-routine cognitive processes, creating a disruption risk across a wide range of vocations. According to a recent Goldman Sachs analysis, generative AI has the potential to automate up to 300 million full-time jobs in the U.S. and Europe. Furthermore, a McKinsey analysis predicts that by 2030, generative AI would automate 29.5% of the hours performed in the U.S. economy, up from 21.5% now.

Figure 1: With generative AI added to the picture, 30% of hours worked today could be automated by 2030 (2).

Furthermore, a Forrester projection indicates that, while generative AI may result in the loss of 1.5% or 2.4 million U.S. employment by 2030, it is projected to affect or transform a considerably bigger chunk of 6.9% or 11.08 million jobs. This suggests a tendency toward work augmentation rather than outright replacement, emphasizing generative AI’s transformational rather than purely disruptive potential.

The industries and positions most vulnerable to the impact of generative AI include:

The effect of generative AI on employment markets is not gender neutral. According to research, this technology’s displacement may have a disproportionate impact on women.

Figure 2: International Labour Organization graph on jobs with automation potential (9)

Women are disproportionately concentrated in white-collar, cognitive positions that are susceptible to generative AI automation, with an estimated 79% of working women employed in at-risk occupations (3). Men, on the other hand, are more evenly parted across white-collar and blue-collar professions, and thus are less subjected to the disruptive effects of generative AI overall. Professions where higher proportions of women may be employed such as clerical work, health care, and teaching, are among the most susceptible to the automation affected by generative AI.

Without appropriate regulation, reskilling efforts, and a practical approach to changeover management, the increasing usage of generative AI has the potential to impair current gender discriminations in the labor market.

Demographic impacts of gen AI

The advent of generative AI raises the possibility of extremely affecting minority and marginalized groups in the labor market. According to a McKinsey analysis, Blacks are overrepresented in positions that are at high risk of automation, with 24% working in such roles compared to 20% for whites (4). This gap underlines the possibility that generative AI will have a more severe impact on Black communities, exacerbating existing racial inequities.

The effect of generative AI on employment markets has the capacity to exacerbate existing inequality, markedly among women. According to a Euronews research, 79% of working women work in jobs with a high risk of automation, compared to 66% of males (3). This gender imbalance shows that the advent of generative AI may impair the current gender partition in the workforce.

A Worth Magazine report observed that, while the contrasts in generative AI acquaintance between men and women were less risky, men were still slightly more likely than women to work in jobs with “high exposure” (12.6% versus 11.2%) and “low exposure” (32% vs. 27.1%), while women were more likely than men to work in jobs with “moderate exposure” (61.6% vs. 55.4%) (5). This shows that women may be more susceptible to the disruptive impacts of generative AI in the labor market.