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Problem at work? You’ll be hearing from my chatbot

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People say nothing funny ever happens on LinkedIn and in my experience, people are right.

But the other day, a colleague showed me a post on the site from a man named Chris who said he had started joining online meetings 30 seconds early, all the better to be discreetly recorded by the AI note-taking assistants now used to transcribe virtual meetings.

He then starts screaming that he is on the Titanic, which has just hit an iceberg, and needs help pronto, before carrying on normally for the rest of the meeting.

“When the meeting ends,” he wrote, “everyone gets an emailed transcript where the AI summary is: ‘Chris hit an iceberg, is trapped on a sinking ship, and general Q2 pricing updates.’”

I enjoyed this story and hope it travels far on the grounds that finally, someone may have found a good use for AI in the office.

Obviously I hear constantly about the latest “use case” in the “AI space” that is going to make working life more productive, efficient and streamlined.

I also realise that scientists at Google DeepMind were joint winners of last year’s Nobel chemistry prize for an AI model that is already helping to speed up work on intractable problems such as antibiotic resistance and plastic pollution.

In the right hands, artificial intelligence can clearly be a force for great good. It’s just that I keep coming across people like Sarah Harrop, who know how dire it can be in the wrong hands.

Harrop is an employment partner at the Addleshaw Goddard law firm in London, which means she deals with claims of unfair dismissal, discrimination and other forms of mistreatment.

Since the arrival of ChatGPT, she says there has been a distinct rise in the number of vastly more detailed, lengthy and outwardly credible correspondence to HR departments and employment tribunals.

The documents often contain references to legal precedents and other references to the law that don’t always turn out to be accurate but take hours to sort through.

“We have seen examples where there are dozens and dozens of pieces of correspondence sent to the employment tribunal,” she told me. The length of the documents and the speed at which they are generated suggests they are almost certainly produced by robots rather than humans, she said, adding this causes “significant pressure” for employers and tribunals.

I can well imagine what a tedious and costly burden this can be for employers, and I am sure they are not alone.

I mentioned Harrop’s observations to a few people last week and quickly learnt that employees are by no means the only ones using AI to turbocharge complaints.

A man who has been a school governor for many years said the volume and intensity of what were almost certainly AI-assisted complaints from parents had skyrocketed in the past 18 months.

The complaints were often well crafted and included convincing references to legal precedents that made them hard to ignore, he said, even though the longest ones invariably turned out to be specious.

I do not see this situation easing any time soon. The internet is now awash with sites offering to harness the power of AI to generate powerful, well-written complaints.

I tested one designed for employees by telling it I wanted a letter about the extent to which male lavatories outnumbered female ones in a large office I recently visited.

Within seconds, it spat back a brisk, grammatically correct and unnervingly persuasive indictment of what it called an unfair and discriminatory arrangement that “presents a negative and potentially unprofessional impression” to female guests.

I’m not going to deny that this induced a surge of gratitude, and the realisation that there must be many times when an AI-aided complaint is fully justified. Shoddy products, unfair parking tickets and malevolent employers are doubtless all grounds for a souped-up grievance letter.

But a world in which those charged with handling complaints are buried beneath an avalanche of AI-generated verbiage of questionable legitimacy is not a good one.

How tempting it must feel to stop diligently wading through the crud and go over to the dark side by simply using AI to respond. 

I don’t suppose we will ever reach the point where we leave it to the bots to fight it out and get back to us once they are done. But then again, can we say for sure that we won’t?

pilita.clark@ft.com



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US stocks: rally or overcorrection?

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The S&P 500 is up more than 20 per cent since mid-April



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On-the-job learning upended by AI and hybrid work

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Jamie Dimon is unequivocal about the impact of remote working on training new bankers. “It doesn’t work in our business,” the chief executive of JPMorgan Chase told Stanford’s Graduate School of Business this year. “Younger people [are] left behind.”

He has previously spoken of the importance of “the apprenticeship model . . . which is almost impossible to replicate in the Zoom world”.

In many workplaces, that apprenticeship model is as simple as sitting near a more experienced colleague or joining a client meeting to watch how it is done, while also learning the ropes by taking on often more repetitive and basic tasks.

But on-the-job learning is now facing the double threat of hybrid working, which means junior staff spend less time observing and listening to more senior colleagues, and generative AI, which is making obsolete many of the routine tasks that have long been building blocks of professional knowledge.

The effect has been noted across professional industries, from auditors and law firms to the big investment banks. Last year, the Public Company Accounting Oversight Board reported that the pandemic and remote and hybrid work had affected audit firms’ “apprenticeship model for on-the-job training, dissemination of culture, and professional scepticism”.

Others see the format as ripe for reform, anticipating that greater changes will come from generative AI.

Employers are investing heavily in AI to assist with working practices. Tools such as those rolled out by law firm A&O Shearman to deal with antitrust and contracts or Goldman Sachs to summarise complex documents and analyse data, are designed to enhance productivity. AI start-up Rogo aims to automate some of the laborious tasks done by junior investment bankers. However, some argue that by eliminating repetitive tasks, junior recruits will fail to develop muscle memory, which is essential for critical analysis, as well as the ability to identify mistakes in AI.

The changes may mean employers have to be more structured and deliberate in the training opportunities they offer junior staff, while working out how to get the best out of generative AI to free up time for their employees to do more valuable work.

Yolanda Seals-Coffield, chief people and inclusion officer at PwC’s US division, says hybrid working means that there needs to be a much more proactive approach to on-the-job training

Navid Mahmoodzadegan, the newly appointed chief executive of boutique investment bank Moelis & Co, says he hopes junior bankers will be rewarded with more “intellectually stimulating” work. Patrick Curtis, chief executive and founder of Wall Street Oasis, an online community catering to the financial services industry, predicts “this shifting more dramatically in the next 24 months as these [junior] roles start leveraging AI more, with some getting displaced outright”.

To maintain the apprenticeship model, leaders at some companies have followed Dimon in mandating five days of office attendance a week. Others, including Citigroup, are continuing with various hybrid working arrangements. Clare Francis, a partner at Pinsent Masons, a law firm that does not mandate days, says that while “junior lawyers benefit from office attendance,” some work, such as research, can be more effectively done at home. She adds that “everyone learns in different ways” and the reality is that many meetings are held on Teams so juniors “can see how they work” just as easily outside the office.

Yolanda Seals-Coffield, chief people and inclusion officer at PwC’s US division, believes hybrid working means “we have lost a little bit of that” tacit knowledge. She sees the solution in junior and senior staff being “far more intentional” about mentoring and debriefing. “We have to be [in] a world post-Covid where people are hybrid, you’re no longer sitting next to someone in an office or on a client side or at a meeting.” Staff, including trainees, at PwC US are required to be on-site half of the time. The arrangement means new recruits need to be clear about saying, “I want to actually shadow this particular behaviour”, she says. This might mean a junior associate sits in on a virtual client meeting or reviews a recorded walk-through of a technical process, followed by structured debriefs to reinforce the learning.

Rather than “a passive experience”, says Seals-Coffield, it requires bosses to think about modelling behaviour such as through guided questioning and peer feedback. AI could start to help with this by, for example, flagging to a team leader that a scheduled interview might provide a shadowing opportunity for a graduate employee who has indicated they are looking for this skill.

I’m optimistic that the tools will enable juniors to think about the material critically

New graduates might also be more fluent in AI than their supervisors, potentially opening up new responsibilities for them to take on. Patrick Grant, project director of legal tech and innovation at the University of Law, says they have developed courses to encourage students to use tools such as ChatGPT critically and ethically in assisting with research, organisation and editing, and to spot “errors or hallucinated references”. They encourage students, for example, to compare drafts of clauses with AI outputs to understand the tools’ lack of nuance.

Francis points out that junior lawyers using generative AI for research is not that different from past generations switching from books to the internet. “Today, the workflow of junior lawyers is not yet fundamentally different [from] how it was before AI was a tool at the disposal of legal teams. Lawyers at the outset of their training continue to learn by verifying results.” The role will “adapt and evolve” alongside AI.

Some argue that by eliminating repetitive tasks, juniors can progress more quickly by taking on more sophisticated and creative work earlier. Francisco Morales Barrón, a partner at Vinson & Elkins law firm in New York, is sceptical about the traditional model. “A lot of older generations will say you learn so much from reviewing thousands of contracts . . . somehow magically you learn through the process of repeating it hundreds of times. I’m optimistic that the tools will enable juniors to think about the material critically.” Francis agrees: “How much do you learn from a monotonous task?”

Seals-Coffield says employers need to get to grips with the desired outcomes of graduate training by separating the task from the skill: “If they’re not [going to] have the opportunity to do that task 50 times, they still need to be able to evaluate it, they still need to be able to provide the critical judgment and independent thinking that is important to evaluate the work that AI might be producing.”

This could include simulations in training, says Francis, “to develop, test and challenge the lawyer both on legal expertise as well as on soft skills such as communication and negotiation”.

Others suggest that any freed-up time will not be spent on more creative tasks, but on additional grunt work — or cutting the number of junior jobs.

According to Oxford Economics, a consultancy, “there are signs that entry-level positions are being displaced by artificial intelligence at higher rates”.

But in some organisations this could be a while off. “Analysts in my class are in a relatively favourable position in which we will have the aid of AI without it replacing us just yet,” reports one investment banking analyst.

Additional reporting by Anjli Raval and Sujeet Indap



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It’s a bad time to be a graduate

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As they trade the campus for the job market, fresh-faced graduates are quickly turning glum. From North America to Europe, university leavers are struggling to find suitable work. The unemployment rate for recent college graduates in the US has for the first time been consistently above the national level since the Covid-19 pandemic. In the EU, the employment rate of 15- to 25-year-olds has fallen over the past two years. Even the crème de la crème are struggling. The percentage of MBA students from Harvard Business School and MIT Sloan without a job offer three months after graduation has risen sharply since 2021.

The rise of artificial intelligence is a factor. In the US, entry-level tech jobs are coming under pressure as coding tasks are automated. The unemployment rate for computer engineering graduates is 7.5 per cent; the national rate is 4.1 per cent. In Britain, the Big Four accountancy firms have cut back on early-career hires in recent years. Economists and recruiters reckon higher costs are encouraging UK professional services firms to experiment with AI in more administrative tasks usually conducted by juniors.

But the plight of graduates predates the emergence of large language models in the workplace. Other structural developments are at play. As more young people around the world are choosing to go to university, competition for jobs has picked up. In Canada, a popular destination for young graduates, the unemployment rate for those under 25 with post-secondary education was 11.2 per cent in the first quarter. Last year in the UK there were an average of 140 applications per graduate job — the highest in three decades, according to the Institute of Student Employers.

As the supply of learned graduates has risen, demand has come under pressure. Research by Indeed, a job search site, finds that the share of US job postings requiring at least a bachelor’s degree has fallen over the past five years. As for the public sector, civil services are being squeezed across cash-strapped advanced economies. Multinationals with big graduate programmes have also been developing global capability centres in low-cost hubs such as India, where they are outsourcing more skilled roles such as data analytics, rather than just back-office functions.

The recent economic cycle has not been kind to recent graduates either. Many professional services and tech firms overhired in the post-pandemic years, assuming activity would bounce back faster than it did. Recruitment rounds have been subdued since. Demand for investment banking analysts and newly qualified lawyers has also been stunted by subdued global mergers and acquisitions activity. Global economic uncertainty makes it difficult for businesses to plan investments and hiring cycles.

Even if the economic environment improves, graduates will still be contending with the rise of AI in the workplace and competition for entry-level jobs. Ensuring students have a better understanding of post-graduation prospects would help them make wiser course choices. Universities and the private sector will need to collaborate more closely if courses are to evolve with the changing demands of work. Even so, businesses and governments will need to raise support for adult training and life-long learning; three-year degrees can quickly become obsolete. The travails of university graduates should also encourage more investment in non-degree vocational training and apprenticeship opportunities, as businesses have long been calling for.

A surfeit of underemployed elites is bad for society and the economy. To ensure it does not become a feature, education must evolve from being a ticket to a job to a toolkit of skills for a changing world.



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