The Implications of Artificial Intelligence on Work: Analyzing the Productivity Paradox of the Digital Age
By: Rooz Aliabadi, Ph.D.
The accelerated interest in artificial intelligence (AI) has highlighted its impressive potential to mimic human capabilities and the possibility of these algorithms replacing many human roles. Such a shift could have monumental societal and economic implications.
The pathway to this economic metamorphosis is via the workplace. A widely shared Goldman Sachs study estimates that around two-thirds of current jobs could be impacted over the next decade, with algorithms potentially handling 25–50% of recent human work. This could mean the modification of up to 300 million jobs worldwide. Similarly, McKinsey & Company’s study suggests an annual $4.4 trillion boost to the global economy due to AI advancement. However, it’s crucial to examine the reliability of these projections.
In my current role at ReadyAI, I also explore how digital technologies impact livelihoods worldwide and how this influence evolves. Analyzing the past result of digital technologies like personal computers and the internet on employment provides insights into AI’s possible future effects. However, we must anticipate some unexpected outcomes if previous trends are any indicator.
A crucial parameter for gauging the influence of technology on the economy is the growth in worker productivity, i.e., the output a worker can produce per hour. This statistic directly links to the worker’s potential earnings, suggesting increased productivity can lead to increased wages.
Generative AI, capable of producing written, graphic, and audio content or software with minimal human involvement, has excellent potential to increase workforce productivity. While this may threaten specific fields like advertising and creative work, economists remain optimistic about its potential to boost productivity.
The Goldman Sachs study foresees an annual productivity growth of 1.5% due to generative AI adoption, almost twice the growth rate from 2010 to 2018. McKinsey predicts an even more significant impact, forecasting a productivity increase of up to 3.3% per year by 2040 due to automation and AI technologies. This level of productivity enhancement would likely be welcome by economists and workers.
However, the productivity growth history in the U.S. during the 20th century presents an interesting pattern. Despite a robust 3% annual growth from 1920 to 1970, there was a decline in productivity growth in the 1970s and 1980s, paradoxically coinciding with the advent of computers and early digital technologies.
Despite substantial corporate investment in computers and the internet, which undeniably transformed workplaces, the benefits to the economy and workers’ wages still need to be clarified.
The dawn of the 21st century brought a fresh wave of the technology revolution, marked by the release of Apple’s iPhone in 2007. However, labor productivity growth again began to stall in the mid-2000s, experiencing only a brief rise during the Great Recession in 2009 before falling into a slump from 2010 to 2019.
As we ventured into a new era dominated by AI and automation, the onset of the COVID-19 pandemic introduced a new variable to the productivity equation. Notably, in 2020, global worker productivity surged to an unprecedented 4.9%.
However, investments in specific tech sectors collapsed after the pandemic, and some promises about groundbreaking technologies faded. In contrast, “generative AI” came to the forefront, offering the vast potential to boost productivity while impacting jobs on a large scale.
Moving forward, it’s essential to consider not only the quantitative effects of AI on jobs and productivity but also its influence on factors like workplace diversity and social inequalities. These elements deeply impact economic opportunity and workplace culture.
The future of work is also highly dependent on how society reacts to the adoption of generative AI. Despite promising analyses suggesting productivity boosts in specific fields, there are growing concerns about the significant risks of generative AI, including its substantial computing and environmental costs.
Given the inaccuracies of past predictions, there’s a high chance that many of today’s forecasts about AI technology’s impact on work and productivity will also prove erroneous. Therefore, it’s best to use these analyses as starting points for discussing potential scenarios and proactively exploring the factors that could influence these outcomes.
The story of technology’s impact on work has always been riddled with surprises; we should be prepared for future technological advancements to continue this trend.
ReadyAI — GenerativeAI-Chat GPT Lesson Plan and others are available FREE to all educators at edu.readyai.org
This article was written by Rooz Aliabadi (rooz@readyai.org). Rooz is the CEO (Chief Troublemaker) at ReadyAI.org
To learn more about ReadyAI, visit www.readyai.org or email us at info@readyai.org.
