A new phenomenon is emerging in the remote work world that challenges the very notion of what it means to work: over-employed individuals are using ChatGPT to secretly work multiple full-time jobs.
The COVID-19 pandemic has upended the traditional office-based work environment, leading to an increase in remote work and flexible working arrangements. And according to a recent expose in the New York Post, some workers are turning to ChatGPT, a language model developed by OpenAI, to help them manage multiple jobs at the same time. By using ChatGPT to automate certain tasks, such as responding to emails, writing reports, doing research, or creating online content, these workers are able to maintain the appearance of being fully engaged with their primary employer while simultaneously working for other companies.
The article cites several examples of workers who have successfully managed to juggle multiple jobs using ChatGPT. One worker, identified only as "John," works a full-time job as a software engineer and also takes on freelance work for several other companies. By using ChatGPT to handle routine tasks, John is able to keep his various employers separate and avoid detection.
Another worker, identified as "Sarah," works two full-time jobs in the healthcare industry. By using ChatGPT to automate paperwork and scheduling, Sarah is able to manage her workload and maintain a high level of productivity across both jobs.
While the use of ChatGPT to manage multiple jobs may seem like a clever solution for over-employed individuals, it raises a number of ethical and legal concerns. For example, workers who engage in this practice may be in violation of their employment contracts or intellectual property agreements. Additionally, they may be at risk of burnout or other negative health consequences as a result of working long hours and managing multiple responsibilities.
However, some employers think differently. Having an attitude of the ends justifying the means can result in the sustained use of ChatGPT to leverage available technologies and expedite productivity. If the work is getting done, they say, does it really matter who does it?