Latest news with #YijiaShao
Forbes
21-07-2025
- Business
- Forbes
Stanford Analyzes Worker Preferences For AI
workers with AI getty Many of us have internalized this notion that we're soon going to be working side-by-side with robots, or at least AI agents and entities. So as humans, what do we want these digital colleagues of ours to do? How does delegation work? A Stanford study recently went into this where authors surveyed 15,000 workers in over 100 types of jobs, to see what they really thought about AI adoption. I thought this comment by one of the authors sums up the purpose of the report well: 'As AI systems become increasingly capable, decisions about how to deploy them in the workplace are often driven by what is technically feasible,' writes project leader Yijia Shao, a Ph.D. student in the Stanford computer science department, 'yet workers are the ones most affected by these changes and the ones the economy ultimately relies on.' In other words, it's the front-line workers who are going to be most affected by these changes, so we might as well hear what they have to say (in addition to doing all kinds of market research.) There's a reason why the suggestion box is a time-tested element of business intelligence. Technology has to be a good fit – it's not something you just implement carelessly, throwing darts at a wall, and then expecting all of the people involved to sign on and go along for the ride. Some Results In terms of actual study findings, the Stanford people found that a lot of it, as Billy Joel famously sung, comes down to trust: 45% of respondents had doubts about reliability, and a reported 23% were worried about job loss. As for the types of tasks that workers favored automating, the study provides a helpful visual that shows off various must-haves against certain danger zones of adoption. Specifically, Stanford researchers split this into a 'green light zone' and a 'red light zone', as well as a 'low priority zone', and an 'opportunities zone' featuring uses that workers might want, but that are not yet technically viable. Uses in the green light zone include scheduling tasks for tax preparers, quality control reporting, and the interpretation of engineering reports. Red light uses that workers are wary of include the preparation of meeting agendas for municipal clerks, as well as the task of contacting potential vendors in logistics analysis. There's also the task of researching hardware or software products, where surveyed computer network support specialists seem to prefer to do this type of work themselves. I thought it was funny that one item in the low priority zone was 'tracing lost, delayed or misdirected baggage,' a job typically done by ticket agents. It explains a lot for those legions of hapless travelers entering their faraway AirBnBs without so much as a toothbrush. As for opportunities, it seems that technical writers would like AI to arrange for distribution of material, computer scientists will largely sign off on technology working on operational budgets, and video game designers would like production schedules automated. Why Automate? I also came across a section of the study where researchers looked at reasons for automation desire on the part of survey respondents. It seems that over 2500 survey workers want to automate a task because it will free up time for other kinds of work. About 1500 cited 'repetitive or tedious' tasks that can be automated, and about the same number suggested that automating a particular task would improve the quality of work done. A lower number suggested automating stressful or mentally draining tasks, or those that are complicated or difficult. The study also broke down tasks and processes into three control areas, including 'AI agent drives task completion', 'human drives task completion' or 'equal partnership' (and two other gradations). You can see the entire thing here , or listen to one of my favorite podcasts on the subject here . One of the headline items is a prediction of diminishing needs for analysis or information processing skills. That connects with more of a focus on managerial, interpersonal or coordination job roles. However, how this will shake out is concerning to many workers, and I would suggest that 23% of respondents worrying about job displacement is a wildly low number. Almost anybody anywhere should be worried about job displacement. Regardless of what happens in the long term, many experts are predicting extremely high unemployment in the years to come, as we work out the kinks in the biggest technological transformation of our time. Anyway, this study brings a lot of useful information to the question – what do we want AI to do for us in enterprise?
Yahoo
16-07-2025
- Business
- Yahoo
AI may diminish demand for high-wage skills like data analysis, research finds
This story was originally published on HR Dive. To receive daily news and insights, subscribe to our free daily HR Dive newsletter. Dive Brief: As artificial intelligence and automation redefine work, today's high-wage skills — including data analysis and process monitoring where AI has demonstrated strong capabilities — may diminish in demand and dip in salary, according to research by the Stanford Institute for Human-Centered AI and the Digital Economy Lab. In contrast, skills requiring human interaction and coordination — such as prioritizing and organizing work and training, teaching and effective communication — will grow in importance and command higher pay, the research, publicized July 7, found. Researchers also identified a mismatch between AI's capabilities and what workers want, which may hinder AI's successful integration into the workplace, according to the report. What workers want, the study found, is to work collaboratively with AI. Dive Insight: For the study, researchers surveyed 1,500 workers about what they wanted from AI and compared this to insight from 52 AI experts about what AI is capable of doing. The findings identified significant mismatches, revealing tasks that warranted reconsideration for automation, a media release explained. For example, in 41% of tasks, including writing creative content and preparing meeting agendas, AI implementation was either unwanted or technically not possible, the researchers said. Other tasks, such as monitoring budgets and creating production schedules, fell into an opportunity zone — highly desired but not yet technically possible, the study found. 'As AI systems become increasingly capable, decisions about how to deploy them in the workplace are often driven by what is technically feasible — workers are the ones most affected by these changes and the ones the economy ultimately relies on,' Yijia Shao, project leader and a Ph.D. student at Stanford Computer Science Department, stated in the release. Bringing employee perspectives to the table is critical to building systems they will embrace, Shao said. It also helps reveal overlooked opportunities for AI and guides 'more human-centered innovation, which in turn benefits technological development.' Organizations that ignore human-centric factors could end up implementing AI and generative AI tools without being completely clear on strategy or business goals, AI leaders at Deloitte Consulting cautioned in an April op-ed for HR Dive. Instead of rushing to beat out competitors, organizations should first understand generative AI's best use case for their business, the consultants advised. This gives HR leaders a better idea of what the company's talent and staffing needs may be, they said. Ultimately, the result of a company's AI investment will depend on human capabilities like cognizance, curiosity and collaboration, the consultants emphasized. Employers are recognizing this, according to a June report from talent assessment firm TestGorilla. Among more than 1,000 U.S. and U.K. hiring decisionmakers surveyed, 3 in 5 told TestGorilla that soft skills are more important today than five years ago. More than 70% said evaluating candidates on both hard and soft skills leads to better results, the survey found. Employers want people who can think critically, adapt and collaborate, TestGorilla's CEO noted. Recommended Reading How companies are planning for AI disruption Sign in to access your portfolio
