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How Will AI Affect the Global Workforce?

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Temporary unemployment caused by the adoption of labor-saving technologies typically increases the US jobless rate by 0.3 percentage point with every 1 percentage point gain in technology-driven productivity growth. However the impact is usually fleeting—such job displacement tends to disappear after two years, Briggs and Dong write.

How will AI impact labor productivity?

Our economists estimate that generative AI will raise the level of labor productivity in the US and other developed markets by around 15% when fully adopted and incorporated into regular production. That would translate into a half-percentage-point rise in the unemployment rate above its trend during the AI transition period, though that impact could be higher if AI adoption is more frontloaded than they assume.

As part of their research, the team examined more than 800 occupations to assess whether AI productivity gains will translate into job displacement. The 6-7% estimate for job displacement from AI is the team’s baseline assumption, but they write that displacement rates could vary from 3% to 14% under different assumptions.

What could AI mean for unemployment?

There are two ways in which AI could hypothetically lead to an increase in unemployment. The first is if AI capabilities advance to a point where human input becomes redundant for many types of production, leading to persistent structural unemployment.

This outcome is unlikely, according to Goldman Sachs Research, because technology change tends to boost demand for workers in new occupations. That can take place either directly through new jobs that emerge from technological change or indirectly by triggering an overall boost in output and demand. Approximately 60% of US workers today are in occupations that didn’t exist in 1940, implying that more than 85% of employment growth since then has been from technology-driven job creation.

“Predictions that technology will reduce the need for human labor have a long history but a poor track record,” Briggs and Dong write.

However there could also be a period of higher unemployment while AI-displaced workers are looking for new jobs. “Frictional unemployment is not unique to AI and occurs during most periods of rapid technological change,” Briggs and Dong write. Historically, upheaval from technological innovation has proven to be temporary—after two years there is no noticeable impact.

Is AI already causing job losses?

Recent commentary by some public companies suggests the labor market is already experiencing effects related to AI. Executives from the technology and finance sectors say they are seeing efficiency gains from generative AI that are sufficient to slow their hiring, especially in operational and back-office capacities.

That said, AI adoption remains relatively low, especially among midsized and small enterprises. While adoption rates have accelerated recently, the vast majority of companies have not incorporated AI into regular workflows. In a recent US survey, only 9.3% of companies reported that they had used generative AI in production during the last two weeks.

To date, low adoption is limiting the overall labor-market impacts from AI, according to Goldman Sachs Research. Our economists found no significant statistical correlation between AI exposure and a host of economic measures, including job growth, unemployment rates, job finding rates, layoff rates, growth in weekly hours, or average hourly earnings growth.

What industries are being affected by AI?

Still, there are early signs of disruption in specific industries. Employment growth in industries such as marketing consulting, graphic design, office administration, and telephone call centers has fallen below trend amid reports of reduced labor demand due to AI-related efficiency gains.



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Researchers ‘polarised’ over use of AI in peer review

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Researchers appear to be becoming more divided over whether generative artificial intelligence should be used in peer review, with a survey showing entrenched views on either side.

A poll by IOP Publishing found that there has been a big increase in the number of scholars who are positive about the potential impact of new technologies on the process, which is often criticised for being slow and overly burdensome for those involved.

A total of 41 per cent of respondents now see the benefits of AI, up from 12 per cent from a similar survey carried out last year. But this is almost equal to the proportion with negative opinions which stands at 37 per cent after a 2 per cent year-on-year increase.

This leaves only 22 per cent of researchers neutral or unsure about the issue, down from 36 per cent, which IOP said indicates a “growing polarisation in views” as AI use becomes more commonplace.

Women tended to have more negative views about the impact of AI compared with men while junior researchers tended to have a more positive view than their more senior colleagues.

Nearly a third (32 per cent) of those surveyed say they already used AI tools to support them with peer reviews in some form.

Half of these say they apply it in more than one way with the most common use being to assist with editing grammar and improving the flow of text.

A minority used it in more questionable ways such as the 13 per cent who asked the AI to summarise an article they were reviewing – despite confidentiality and data privacy concerns – and the 2 per cent who admitted to uploading an entire manuscript into a chatbot so it could generate a review on their behalf.

IOP – which currently does not allow AI use in peer reviews – said the survey showed a growing recognition that the technology has the potential to “support, rather than replace, the peer review process”.

But publishers must fund ways to “reconcile” the two opposing viewpoints, the publisher added.

A solution could be developing tools that can operate within peer review software, it said, which could support reviewers without positing security or integrity risks.

Publishers should also be more explicit and transparent about why chatbots “are not suitable tools for fully authoring peer review reports”, IOP said.

“These findings highlight the need for clearer community standards and transparency around the use of generative AI in scholarly publishing. As the technology continues to evolve, so too must the frameworks that support ethical and trustworthy peer review,” Laura Feetham-Walker, reviewer engagement manager at IOP and lead author of the study, said.

tom.williams@timeshighereducation.com



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Amazon Employing AI to Help Shoppers Comb Reviews

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Amazon earlier this year began rolling out artificial intelligence-voiced product descriptions for select customers and products.

Now, the company’s “Hear the Highlights” feature has extended to all users, CNBC reported Sunday (Sept. 14), arguing this could replace user-created reviews as the main source of product information.

Among the advantages here, the report added, is that artificial intelligence (AI) won’t suffer from cognitive overload from combing through thousands of reviews. 

“It’s important to recognize where AI is currently strong, such as in automation and pattern recognition, and where it still falls short, like in judgment-heavy tasks,” said Ankur Edkie, co-founder and CEO of Murf AI, which develops AI voiceovers. “A key question is whether there’s a way to factor in customer context as an input while generating these summaries.”

The value of AI, according to Edkie, is determining the right “problem-capability fit.” Without that, he added, a sense of “gimmickry” is likely to filter through thanks to AI fatigue, which he says consumers are likely feeling by now.

PYMNTS has contacted Amazon for comment but has not yet gotten a reply.

The CNBC report also noted that the tendency of AI to focus on common themes can water down responses even as it summarizes them, taking out the detailed personal experiences found in human reviews.

“AI might overlook unique insights or niche needs that don’t align with the majority of responses,” said Brian Numainville, principal at consumer research firm Feedback Group. “Additionally, the ability to critically interpret reviews — like spotting biases or trusting certain reviewers — is diminished with AI summaries.”

Nauman Dawalatabad, a research scientist at Zoom Communications, offered his opinion that the technology is on its way to improving customer experience.

“I take it as technology helping us to make informed decisions,” he said, pointing to the mental fatigue and wasted time that can result from working through customer reviews.

Meanwhile, recent research by PYMNTS Intelligence shows that AI shopping adoption has begun to gain traction with younger and middle-aged consumers. The research found that 32% of all consumers said they have used or would use generative AI for shopping.

“Bridge millennials — older millennials straddling Gen X — lead the way, with 38% reporting AI use for shopping,” PYMNTS wrote last month. “Zillennials are close behind at 36%, followed by millennials at 35%. Gen X is next, at 33%, while Gen Z comes in at 31%. Baby boomers show some traction as well, with 28% using gen AI for shopping.”



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Nubank To Continue Leveraging AI To Enhance Digital Financial Services In Latin America

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Nubank (NYSE: NU) is reportedly millions of customers across Latin America. Recently, the company’s Chief Technology Officer, Eric Young, shared his vision for leveraging artificial intelligence to fuel Nubank’s global expansion and improve financial services.

During a recent discussion, Young outlined how AI is not just a tool but a cornerstone for operational efficiency, customer-centric growth, and democratizing access to personalized finance.

With a career that includes work at Amazon in the early 2000s, Young brings a philosophy of prioritizing customer experience.

At Amazon, he witnessed firsthand how technology could transform user experiences, a mindset he now applies to Nubank’s mission. “If not us, then who?”

Young posed rhetorically during the videocast, underscoring Nubank’s unique position to disrupt traditional banking.

Founded in Brazil in 2013, Nubank has positively impacted the financial sector by prioritizing financial inclusion and superior customer service, challenging legacy banks with its digital-first approach.

Under Young’s leadership, Nubank’s priorities are clear: enhance agility, expand internationally, and harness AI to serve customers better.

He emphasized the need for cross-functional collaboration, particularly with the product and design teams.

This includes partnering with Nubank’s recently appointed Chief Design Officer (CDO), Ethan Eismann, to iterate quickly on new features.

By fostering a culture of testing and learning, Young aims to deliver products that not only meet but exceed user expectations, ultimately capturing a larger market share.

This involves deepening engagement with existing users, attracting new ones, and venturing into underserved markets where financial services remain inaccessible.

Central to Young’s strategy is AI’s transformative potential.

Nubank’s 2024 acquisition of Hyperplane, an AI-focused startup, marks a pivotal step in this direction.

Young highlighted how advanced language models—such as those powering ChatGPT and Google Gemini—can bridge the gap between everyday users and elite financial advisory services.

These models excel at processing vast amounts of data, including transaction histories, to offer hyper-personalized recommendations.

Imagine an AI that automates budgeting, predicts spending patterns, and suggests investment opportunities tailored to an individual’s financial profile, all without the hefty fees of traditional private banking.

Young drew a parallel to the exclusivity of high-end services.

Historically, AI-driven private banking was reserved for the ultra-wealthy, but Nubank’s vision is to make it ubiquitous.

“We’re democratizing access to hyper-personalized financial experiences.”

By analyzing user data ethically and securely, AI can empower customers from all segments—whether a small business owner in Mexico or a young professional in Colombia—to manage their finances with the precision once afforded only to elites.

This aligns with Nubank’s core ethos of inclusion, ensuring that technology serves as an equalizer rather than a divider.

Looking ahead, Young sees AI as the engine for Nubank’s platformization efforts, enabling scalable solutions that support international growth.

As Nubank eyes further expansion beyond Brazil, Mexico, and Colombia, AI will streamline operations, from fraud detection to customer support chatbots, reducing costs while enhancing reliability.

Yet, Young cautioned that success hinges on responsible implementation—prioritizing privacy, transparency, and human oversight to build trust.

In an era where fintechs aggressively compete for market share, Eric Young’s insights position Nubank not just as a bank, but as a key player in AI-powered financial services.

By blending technological prowess with a focus on the customer, Nubank is set to transform money management, making various services more accessible to consumers.

As Young basically put it, the question isn’t whether AI will change finance—it’s how Nubank will aim to make a positive impact.





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