Artificial intelligence (AI) affects many industries and occupations in a variety of ways. Recent studies examining taxi drivers in Yokohama, Japan, show that AI demand forecasts, which are unrelated to autonomous driving, can improve productivity for less experienced drivers and close the skills gap. This finding challenges the assumption that AI merely supports advanced workers in technology-dependent industries.
The news is full of stories about AI and its impact on society. Some news sites also have dedicated tabs for such stories. Although subjects vary, many stories raise alarms about potential negative effects and more. However, researchers, including researchers at the University of Tokyo, recently discovered something positive related to the profession of taxi driving.
Their research examines the AI apps used by taxi drivers, predicting where customers will have the highest demand and suggesting the best route for them. The goal is to reduce the time spent without passengers and increase overall efficiency. Comparing drivers with different levels of skill, and thus their demand forecasting capabilities, teams saw the biggest advantages of low-skilled drivers, increasing productivity by 7%, with highly skilled drivers having little advantages.
“We believe this shows that AI can act as a 'Deskar' technology, reducing the relative benefits of highly skilled counterparts while increasing productivity for low-skilled workers,” he says, reducing the relative benefits of Watanabe Yasutora, a graduate school of Public Policy. “This shift challenges decades of technical trends that have supported skilled workers and expanded inequality.”
To ensure the impact of AI tools on taxi driver efficiency, Watanabe also measured the impact of AI APPs that were not affected by AI, which dealt with unique challenges, by Professor Kawaguchi, Shimaoka, and lecturer Kawakawa Kawakawa at Yokohama National University. Importantly, the use of variations in data that randomly uses AI in analyses, similar to how medical researchers randomly assign subjects to treatment and control groups in clinical trials. Their methods relied on the random nature of where taxi rides ended. Drivers begin looking for new customers from locations that were randomly determined by the location where the previous ride ended, thus randomly affecting the probability that the driver will turn on AI according to location familiarity.
“The meaning of this study goes beyond taxi drivers. If AI can narrow down the skill gaps among taxi drivers, they can do the same elsewhere,” explained Shigeoka. “These findings may apply to jobs such as paralegals reviewing contracts and reviewing pathologists who identify malignant cells. AI could significantly benefit less skilled workers and improve performance.
However, this study also revealed some inexplicable things. Many of the less skilled drivers did not use the app, even if they could significantly improve their performance. The researchers acknowledged that this hesitation could be attributed to reluctance to embrace new technologies, and that addressing this barrier could benefit workers in a variety of fields.
“Companies may focus on designing reskilling programs to help employees develop complementary capabilities,” Kawaguchi said. “By automating skills such as demand forecasting, employers are shifting their focus to hiring AI employers, not replicating AI as better communication skills or focusing on others.”
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