The big question with generative AI these days is whether tools like ChatGPT will widen the inequality gap or give workers new skills and abilities.
A study(opens in a new tab) from the MIT Department of Economics designed to answer this question found that participants using OpenAI’s ChatGPT increased their productivity and the likelihood that they would use ChatGPT in future tasks. In the controlled study, this implies that “technology will be more strongly complementary to human workers,” meaning it favors tools like ChatGPT as a way to empower workers. But how these tools are actually implemented in the real world remains unclear.
How generative AI will affect the economy of creators
Unlike earlier AI tools that raised concerns about automating “routine” tasks, deep learning tools like ChatGPT are capable of performing more complex creative tasks like writing and designing. How generative AI is implemented in the workforce could have a negative or positive impact on workplace inequality. “Inequalities among workers could either decrease if low-ability workers are more supported by ChatGPT, or increase if higher-ability workers have the skills to take advantage of new technology,” the study says.
The experiment included 453 college-educated professionals and half of the randomly assigned participants with ChatGPT after completing their first assignment. The assignments were writing-based tasks, including press releases, short reports, and “tricky emails,” mimicking those that grant writers, marketers, consultants, data analysts and HR professionals would do in their daily work.
The study found that the group that had access to ChatGPT reduced the time it took to complete a task by 11 minutes and improved the quality. Notably, the performance of the treatment group (those using ChatGPT) increased between their first assignment (without ChatGPT) and subsequent assignments (with ChatGPT), which the study suggests may reduce the inequality gap between skilled and unskilled labour.
This has been anecdotal for anyone using ChatGPT. But the study provides hard evidence that workers armed with ChatGPT can be more productive and perform their tasks better. Yet how that plays out in the real world remains to be seen. Is this proof that ChatGPT should be considered a new tool in workers’ toolkits? Or will companies interpret this as proof that generative AI can successfully replace entire jobs? Ultimately, this study highlights how the implementation of generative AI depends on an extremely complex and unpredictable factor: human nature.
