Do you know ChatGPT Will Be Pursuing Your Office Job in 2023? The chatbot has a surprising ability to articulately respond to a wide range of concerns, from coding issues to legal complexities to historical inquiries. ANYONE WHO HAS SPENT A FEW MINUTES PLAYING WITH CHATGPT WILL UNDERSTAND THE CONCERNS AND HOPES SUCH TECHNOLOGY GIVES IN RELATION TO WHITE-COLLAR WORK.
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It’s not difficult to conceive that corporations would use these models to replace customer service representatives, legal assistants, or history teachers—as long as they can get beyond the troublesome way they frequently “hallucinate” false material. These expectations are stoked by studies and news articles that indicate ChatGPT can pass some commercial, legal, and medical exams. We are sure to notice the influence on office life soon enough with firms like Microsoft, Slack, and Salesforce introducing ChatGPT or comparable AI solutions to their applications.
A few research studies published online this week indicate that ChatGPT and related chatbots might be quite disruptive—but perhaps not in the ways you might anticipate.
The first step is to try to determine which occupations are most likely to be impacted by ChatGPT, according to Edward Felton and colleagues at Princeton University. To determine which professions are most at risk from chatbots with advanced linguistic capabilities, researchers utilised a benchmark called the AI Occupational Exposure, which correlates occupational tasks with the capabilities of various AI systems.
The findings indicate that significant changes may be coming for some professions, such as telemarketers, history teachers, and sociologists, while those in more physically demanding jobs, like bricklayers, dancers, and textile workers, may not need to be concerned about ChatGPT showing up at their place of employment.
Yet, a second study contends that those who work in positions that focus on language are not always doomed to be replaced. Graduate students at MIT Shakked Noy and Whitney Zhang examined what happens when office workers use ChatGPT. They assigned a set of straightforward office duties to 444 college-educated workers, including composing emails, short reports, and analytical plans. ChatGPT was available to half of them.
According to the study, those who had access to the chatbot were able to do the tasks in 17 minutes as opposed to an average of 27 minutes for those without it, and their job quality greatly increased. Those who used ChatGPT also expressed greater job satisfaction. The publication does not specify whether screening for the kinds of “hallucinated” errors that can appear in ChatGPT’s output was part of the study, despite the fact that it required asking experts to evaluate the quality of participants’ work.
These two experiments give us a glimpse of possible outcomes, but they are only preliminary (and have not yet been peer-reviewed) attempts to understand where ChatGPT is leading us. The influence of new technology on the workplace is notoriously difficult to foresee, and ChatGPT-related economic research is emerging quickly.
Ironically, textile workers were identified as possibly being immune to ChatGPT, despite the fact that those who worry about how AI will affect the labour market are frequently referred to as “Luddites” in reference to the nineteenth-century movement in which English textile workers smashed looms in protest of automation.
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In fact, according to some sources, Luddites were angrier with businesses that used technology to avoid paying workers properly than they were about automation itself.
It might be a good idea for staff members to start using ChatGPT on their own to increase productivity. Just be sure not to inform my supervisor. (I’m joking—WIRED just announced a new policy on use of generative AI that says we won’t publish AI-generated prose unless where it’s part of a story).
My initial attempt to automate my own work failed miserably. It makes sense that ChatGPT would propose articles from 2021 when I requested it to discover some links for this week’s email because the AI model was trained using data collected from the web in the past. There might not be a significant increase in productivity for newsletter writers just yet.