{"id":48675,"date":"2024-06-21T09:44:09","date_gmt":"2024-06-21T08:44:09","guid":{"rendered":"https:\/\/www.innovationnewsnetwork.com\/?p=48675"},"modified":"2024-06-21T09:44:09","modified_gmt":"2024-06-21T08:44:09","slug":"assessing-impact-large-language-models-labour-market","status":"publish","type":"post","link":"https:\/\/www.innovationnewsnetwork.com\/assessing-impact-large-language-models-labour-market\/48675\/","title":{"rendered":"Assessing the impact of large language models on the labour market"},"content":{"rendered":"<h2>Though large language models (LLMs) and associated technologies are poised to disrupt jobs, little has been done to evaluate this risk or develop a policy to address it.<\/h2>\n<p>Now, a new study has developed a rubric to assess the effects of large language models on labour markets.<\/p>\n<p>The study, \u2018<a href=\"https:\/\/www.science.org\/doi\/10.1126\/science.adj0998\" target=\"_blank\" rel=\"noopener\">GPTs are GPTs: Labor market impact potential of LLMs<\/a>,\u2019 is published in <em>Science<\/em>.<\/p>\n<h3>Can large language models improve our experiences at work?<\/h3>\n<p>Despite a growing literature that aims to understand the labour market impacts of LLMs, there is still no clear understanding of how exposure to <a href=\"https:\/\/www.innovationnewsnetwork.com\/how-the-brain-learns-is-different-from-the-way-ai-systems-learn\/41450\/\">AI systems<\/a> will translate to real-world impacts on labour demand, wages, inequality, job quality, and other key outcomes.<\/p>\n<p>To assess this, the researchers used the O*NET 27.2 database \u2013 which covers dozens of occupations and their detailed workflows \u2013 and focused on 923 occupations.<\/p>\n<p>They used humans and trained GPT-4 to evaluate if LLMs could reduce the time required for a human to complete a task by at least 50% while preserving or improving quality.<\/p>\n<p>The authors estimate that about 80% of workers are in occupations with at least 10% of job tasks exposed to large language models influence in this way, with 18.5% of workers in occupations with 50% of their tasks exposed.<\/p>\n<p>An additional exploratory analysis revealed 1.86% of tasks could be fully automated with no human oversight.<\/p>\n<h3>The science and research industry is fully embracing AI<\/h3>\n<p>Overall, the researchers found that generally, higher wage occupations were more exposed to the effects of LLMs than lower wage occupations.<\/p>\n<p>In fact, the two job groups most exposed to LLMs are \u2018Scientists and Researchers\u2019 and \u2018Technologists\u2019.<\/p>\n<p>However, tasks currently considered out of reach of large language models might become more viable with future innovations, and conversely, tasks that seem more likely to be handled by LLMs might encounter unexpected barriers.<\/p>\n<p>This work highlights the importance of developing policies to ease transitions in LLM adoption and direct their development in a more socially beneficial direction, ensuring that economic gains are large and broadly distributed.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>A new study has developed a rubric to assess the effects of large language models on labour markets. Read more here.<\/p>\n","protected":false},"author":22,"featured_media":48676,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[830],"tags":[570],"acf":[],"yoast_head":"\n<title>Assessing the impact of large language models on jobs<\/title>\n<meta name=\"description\" content=\"A new study has developed a rubric to assess the effects of large language models on labour markets. 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