AI-assisted work
The belief in meritocracy assumes that individuals are solely responsible for their success or failure based on their abilities and efforts. While this is a comforting model for many employers, it fails to acknowledge the systematic barriers that can limit educational and professional opportunities based on factors like race, gender, and socioeconomic status. Relying on meritocracy alone can lead to an inequitable distribution of rewards and recognition in the workplace.
The introduction of AI technology in the workplace has the potential to minimize some of the effects of these inequities.
One way AI can level the playing field is by enhancing productivity. A study from NBER by Erik Brynjolfsson, Danielle Li, and Lindsey R. Raymond, examining the impact of AI on call center employee productivity, found that employees in the lowest skill quintile experienced a 35 percent increase in resolutions per hour when assisted by AI, as opposed to a negligible productivity increase for the most skilled workers. This suggests that AI technology can help bridge the productivity gap between employees with varying skill levels, enabling those who may have had fewer opportunities for skill development to perform at a higher level.
AI can be a powerful tool for leveling the creative playing field as well. While creative thinking and problem-solving are crucial to success in many fields, employees that hold underrepresented identities often face pressure to conform to dominant norms, which can drain the cognitive resources that allow for creativity. While work needs to be done to reduce the need to assimilate at work, AI can help create a more equitable environment by supporting creative thinking.
A study by Anil R Doshi and Oliver Hauser, examining the impact of AI on the creativity of writers, found that the use of generative AI-sourced ideas increased writers’ quality of writing by 27 percent and people’s enjoyment of their writing by 23 percent (as assessed by third party evaluators) for writers with lower creativity scores, while providing a negligible-to-negative impact on high-creativity writers.
Additionally, an MIT study by Shakked Noy and Whitney Zhang, focusing on occupation-specific writing tasks by mid-level professionals, revealed that generative AI technology can narrow the gap in output between lower-ability and higher-ability workers. This increase in quantity and quality of work not only improves corporate results, but also benefits employees by contributing to a more equitable distribution of opportunities and rewards.
This occupation-specific potential was also validated by research from Jonathan H. Choi and Daniel Schwarcz, studying the use of AI in legal analysis. Their findings revealed that law students at the bottom of the class saw huge performance gains in multiple-choice testing when using AI assistance, while students at the top of the class saw performance declines.
While AI has the potential to lessen the inequitable aspects of meritocratic systems, there are important considerations that must be addressed alongside its use. This includes mitigating algorithmic biases that could perpetuate existing inequalities, and ensuring that processes are focused on enhancing, rather than replacing, human capabilities.
Most importantly, we must remember that the use of AI to create more equitable outcomes is not a replacement for efforts to promote diversity, equity and inclusion in the workplace. Combining AI with comprehensive DEI strategies can create a work environment where individuals have equal opportunities to succeed and thrive based on their potential, rather than being limited by an unwavering belief in meritocracy alone.
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