As advances in generative artiicial intelligence (Al)continue at an unprecedented pace,large languagemoddls(LLMs)are emerging as transformative toolswith the potertial to redefine the jpb landscape.Therecent advancements in these tools,like GitHub’sCopilot,Midjourney and ChatGPT,are expectedto cause significant shifts in global economies andlabour markets.These particular technological
advancements coincide with a period of considerablelabour market upheaval from economic,geopolitical,green transition and technological forces.TheWorld Economic Forum’s Euture of Jobs Report2023 predicts that 23%ofglobal jpbs will changein the next five years due to industry transformation,induding through artificial intelligence and other text,image and voice processing technologies.
This white paper provides a structured analysis ofthe potential direct,near-term impacts of LLMs onjobs.With 62%of total work time invohning language-based tasks,’the widespread adoption of LLMs,such as ChatGPT,could significantty impact a broadspectrum ofjob roles.
To assess the impact of LLMs on jpbs,this paperprowides an analysis of over 19,000 individualtasks across 867 occupations,assessing thepotential exposure of each task to LLM adoption,classifying them as tasks that have high potentialfor automation,high potential for augmentation,lowpotential for either or are unaffected (non-languagetasks).The paper also provides an oveview of newroles that are emerging due to the adoption of LLMs.
The longer-term impacts of these technologiesin reshaping industries and business models arebeyond the scope of this paper,but the structuredapproach proposed here can be applied to otherareas of technological change and their impact ontasks and jobs.
The analysis reveals that tasks with the highest
potential for automation by LLMs tend to be routineand repetifive,while those with the highest potentialfor augmentation require abstract reasoning andproblem-sohing skills.Tasks with lower potentialfor exposure require a high degree of personalinteraction and collaboration.
-The jpbs ranking highest for potential automationare Credit Authorizers,Checkers and Clerks (81%of work time could be automated),ManagementAnalysts (70%),Telemarketers (68%),StatisticalAssistants (61%),and Tellers (60%).
一 、Jobs with the highest potertial for taskaugmentation emphasize mathematicaland scientific analysis,such as ihsuranceUnderwriters (100%of work time potentiallyaugmented),Bioengineers and BiomedicalEngineers(84%),Mathematiaians (80%),andEditors (72%).-Jobs with lower potential for automation or
augmentation are jobs that are expected to
remain largely urchanged,such as Educational,Guidance,and Career Counsellors and Advisers(84%of time spent on low exposure tasks),Clergy (84%),Paralegals and Legal Assistants(83%),and Home Health Aides (75%).In addition to reshaping existing jobs,
the adoption ofLLMs is likely to create newroles within the categories of Al Developers,Interface and Interaction Designers,Al ContentCreators,Data Curators,and Al Ethics andGovernance Specialists.
-An industry analysis is done by aggregatingpotential exposure levels of jobs to the industrylevel,noting that jobs may exist in more thanone industry.Results reveal that the industrieswith the highest estimates of total potentialexposure (automation plus augmentationmeasures)are both segments of financial
services:financial services and capital marketsand insurance and pension management.Thisis followed by information technology and digitalcommunications,and then media,entertainmentand sports.Additional lists of jpbs ranked byhighest exposure potential for each major
industry category are compiled in the appendix.Similarly,a function group analysis revealsthat the two thematic areas with the greatesttotal potential exposure to LLMs are informationtechnology,with 73%of working hours
exposed,and finance,with 70%of workinghours exposed.As with the industry groups,additional lists of jobs ranked by highestexposure potential for each function groupare compiled in the Appendices.
These new findings connect directly to earlierwork done by the Centre for the New Economyand Society in the Euture of Jabs Report 2023.Many of the jobs found to have high potentialfor automation by LLMs were also expectedby business leaders to undergo employmentdecline within the next five years,such as banktellers and related clerks,data entry derks,and administrative and executive secretaries.Meanwhile,jobs with high potential for
augmentation are expected to grow,such asAl and Machine Leaming Specialists,DataAnalysts and Sdientists,and Database andNetwork Professionals.Together,these twopublications identify and reafirm salient themesin the connection between technological changeand labour market transformation.
The findings of this report shed lght on howimplementing LLMs could alter the landscape ofjobs,providing valuable insights for policy-makers,educators and business leaders.Rather than leadingto job displacement,LLMs may usher in a period oftask-based transformation of occupations,requiringproactive strategies to prepare the workforce forthese jobs of tomorow.
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