Just because your job gets exposed, doesn’t necessarily guarantee you productivity#gpt #LLM #exposure GPTs are general-purpose technologies
My Reading Summary of the Paper[1][1]" role="complementary" aria-hidden="true">#
Large Language Models (LLMs) and Generative Pre-trained Transformers (GPTs) LLM-powered software integrates both human expertise and GPT-4 classifications:” Our findings reveal that around 80% of the U.S. workforce could have at least 10% of their work tasks affected by the introduction of LLMs, while approximately 19% of workers may see at least 50% of their tasks impacted."
Exposure to LLMs and Detailed Work Activities (DWAs)#exposure-to-ll-ms-and-detailed-work-activities-dw-as' aria-label="Permalink to Exposure to LLMs and Detailed Work Activities (DWAs)" role="complementary" aria-hidden="true">#
A DWA is a comprehensive action that is part of completing a task, such as "Study scripts to determine project requirements." A task, on the other hand, is an occupation-specific unit of work that may be associated with none, one, or multiple DWAs. Occupation > Tasks > DWAs Exposure: a measure of whether access to a GPT or GPT-powered system would reduce the time required for a human to perform a specific DWA or complete a task by at least 50 percent. It is used as a proxy for potential economic impact without distinguishing between labor-augmenting or labor-displacing effects.” Reflects an estimate of the technical capacity to make human labor more efficient."
When regressing exposure measures on skillsets using O*NET’s skill rubric, we discover that roles heavily reliant on science and critical thinking skills show a negative correlation with exposure, while programming and writing skills are positively associated with LLM exposure.
In other words, workers facing higher (lower) barriers to entry in their jobs tend to experience more (less) exposure to LLMs.
We analyze exposure by industry and discover that information processing industries (4-digit NAICS) exhibit high exposure, while manufacturing, agriculture, and mining demonstrate lower exposure.
”Our findings indicate that the importance of science and critical thinking skills are strongly negatively associated with exposure, suggesting that occupations requiring these skills are less likely to be impacted by current language models."
”Conversely, programming and writing skills show a strong positive association with exposure, implying that occupations involving these skills are more susceptible to being influenced by language models (see Table 5 for detailed results)."
What Should I Do?
- Develop science and critical thinking skills
- Focus on value-driven creativity and innovation
- Remember that job exposure doesn't necessarily guarantee increased productivity
