Tag: AI

Remote control – AI and hybrid working

This decade is likely to see the biggest transformation of the workplace since the widespread adoption of the personal computer. Hybrid and remote working patterns adopted during the pandemic appear to be sticking, and a wave of disruption from artificial intelligence (AI) and large language models (LLMs) is following rapidly behind.

London is at the epicentre of these twin “workquakes”. The capital has persistently had the highest levels of home-working in the UK, with two thirds of Londoners saying they worked at home at least one day a week last summer. This reflects hybrid working’s dominance among professional and managerial staff, who make up 63 per cent of London’s resident workers, compared to 50 per cent of all England’s.

These people enjoy the flexibility, work-life balance and personal productivity that working from home can offer, though the impact on organisational or inter-organisational productivity is more contested. Nonetheless, speakers at a London Assembly meeting last week said that the era of “five days a week in the office” had gone for good, and that the task was to adapt central London to new ways of living, working and playing.

The accelerating pace of AI adoption looks likely to add turbulence. A recent UK government report found that workers in London were twice as exposed to AI as the UK average. This was not because of LLMs’ appetite for the diversity and vitality of the capital, but (like the prevalence of home-working) is largely a result of London’s occupational make-up. Unlike previous waves of automation, which affected manufacturing and routine clerical work, AI is coming for the professionals.

The report suggests that the most affected occupations include management consultants, financial managers, psychologists, economists, lawyers, project managers, market researchers, public relations professionals, authors and, perhaps surprisingly, clergy. The “safest” are jobs are those of such as sports professionals, roofers, plasterers, gardeners and car valets. The former occupations are over-represented in London, the latter are not.

However, before soft-handed metropolitan knowledge workers like me rush to retrain, ignoring our lack of aptitude, there are some caveats. The first is that the government report’s projections make no distinction between jobs that are augmented (those where workers can deploy AI to dramatically enhance their productivity), and those that are likely to be substituted (replaced, sooner or later, by new technology).

The second is that the analysis takes no account of the new jobs that will be created. We can see those that are at risk, but it is harder to identify the opportunities that will arise. A year ago, few people had any idea what a “prompt engineer” was. Today, demand for them is booming. And we can be re-assured by historical experience: the majority of jobs that Americans do today did not exist in 1940.

In any case, most professional jobs involve more than one activity, which is where the interaction between working from home and AI gets interesting. A management consultant, for example, may spend time meeting clients, preparing pitches, interviewing workers, analysing data, workshopping ideas and writing reports. A PR professional may write press releases, manage staff, research markets, pitch to clients and journalists, develop concepts, devise guest lists, plan and host events.

Some of these tasks are intrinsically social and best undertaken face-to-face. Others are more easily undertaken remotely, away from distraction and other people. Those in the latter group are also those that can be most easily supported by AI.

From this perspective, AI adoption and hybrid working will complement each other. Hybrid working has already accustomed us to working remotely with less social interaction; AI can provide a sounding board for ideas and be an orchestrator of collaboration, without the hassle and cost of a commute. Similarly, intelligent use of AI can boost productivity, improve co-ordination and reduce the “digital overload” of online meetings, emails and collaboration spaces that built up during lockdown.

But there may be a sting in the tail. Over time, people working remotely with AI support may find themselves edged out by their machine collaborators. Cost-conscious employers are already exploring whether some jobs undertaken remotely might be outsourced internationally. A task that can be completed in Leamington Spa rather than London can also be exported to Lisbon or Kuala Lumpur. Over time, it may also be undertaken by an AI.

Oxford University professors Michael Osborne and Carl-Benedikt Frey, who published a highly influential analysis of the potential impact of automation on the workforce in 2013, recently wrote a (very readable) update reflecting on the explosive growth in AI and how it may affect their original projections.

In 2013, they argued that tasks requiring social intelligence were unlikely to be automated. Now, they write, AI has challenged that “bottleneck” to automation: “If a task can be done remotely, it can also be potentially automated.” However, for sensitive tasks and relationships, face-to-face would retain primacy:

“The simple reason is that in-person interactions remain valuable, and such interactions cannot be readily substituted for: LLMs don’t have bodies. Indeed, in a world where AI excels in the virtual space, the art of performing in-person will be a particularly valuable skill across a host of managerial, professional and customer-facing occupations. People who can make their presence felt in a room, that have the capacity to forge relationships, to motivate, and to convince, are the people that will thrive in the age of AI. If AI writes your love letters, just like everybody else’s, you better do well when you meet on the first date.”

What does this all mean for cities like London? To start with, while we do not know precisely what new jobs will be created by the AI revolution, London is already one of a handful of hotspots for AI start-ups, so it is likely to be the location for many of the new jobs too. The capital is already home to Google Deepmind and many other high growth AI firms, and OpenAI have announced plans for their first international outpost in London.

The combination of AI and hybrid working may ironically strengthen London’s role as one of a few genuine global centres for face-to-face interaction. If remote work is increasingly dispersed or automated and in-person workers with social skills remain in demand, then diverse, globally-accessible, sociable cities such as London will provide the ideal setting for their relationships and collaborations.

There is a bigger picture too. A recent paper by Richard Florida and others talked of the rise of “metacities” based on long-distance networks of collaboration and intermittent commuting. This identified London and New York as the world’s two leading “superstar” hubs, sitting at the heart of networks of talent and interaction. London’s network, as measured by talent flows, includes Manchester, Birmingham, Edinburgh and Bristol, but also Dublin, Paris, Lagos and Bengaluru.

Florida and colleagues argue that the constellation of satellite cities will shift over time, but the importance of superstar cities will persist. This suggests that in coming years London will need to plan for growth in housing, in offices and in new forms of collaborative and social spaces.

The city will also need to be open and welcoming to global talent while helping local workers adapt to change, and to work more closely with its satellite cities to ensure that economic transformation can deliver prosperity and economic growth across the UK.

This is likely to be a turbulent decade for London’s economy, but it could also be one in which the capital’s national and global profile increase.

First published by OnLondon.

Talkin’ about AI Generation

A year after OpenAI’s ChatGPT was launched, we are starting to see the outlines of generative artificial intelligence’s potential impact on our lives.

While the recent Bletchley Park Summit focused on existential risk and misuse by extremists, debate in universities has focused both on technocratic issues (such as automated marking and plagiarism) and more recently on the potential of AI to transform and enhance learning and research – see, for example, the recently published Russell Group principles on the use of generative AI in education.

But there’s a more fundamental question for universities too. How will AI change our economy, and what will this mean for the role played by universities in readying the workforce of the future? The AI Generation: How universities can prepare students for the changing world, a new report for Demos and University of London, draws together what we know about how universities support students’ employability today, and speculates about how this might change as technology advances.

Within our GRASP

The good news is that there is a reasonably strong consensus about the critical employability skills needed today. As computer use and the internet have transformed the knowledge economy, it is not specific technical skills that are most prized. More important are the broader skills of listening to and persuading clients and colleagues, analysing and communicating information to solve problems, and having the ability to manage your own workload, your career and your professional development – the GRASP (general, relational, analytical, social and personal) skills.

Most of these skills are expected to rise in importance in coming years and will remain important in working with AI. Even if generative AI can produce text and images, workers will need critical and ethical judgement to assess what it produces and what it is asked to produce, as well as the relational and social skills to intermediate between technology and humans. So, it appears that the GRASP skillset, with adjustments, will still be relevant.

The less good news is that there is not much evidence on how well universities help students acquire these skills even now, how well these translate into good employability outcomes, or even precisely how they should be defined. Based on a review of academic and policy literature, The AI generation finds that generic “employability” content is unpopular and largely ineffective for students, but material tailored to subject matter and likely career paths much more valued. Active learning approaches – project assignments, collaborative work, peer assessment – seem to work better in developing most employability skills as well as leading to better outcomes, than traditional lecture-based learning.

But it is what happens outside the classroom – work experience, placements, membership of clubs and societies, studying overseas – that has the most impact, whether based on students’ self-assessments, or longitudinal studies looking at graduate employment rates and types. The complication is that these activities are not available to or taken up by all students equally. Students from poorer backgrounds are less likely to participate – partly a matter of cost, but also a matter of feeling, or being made to feel, that you don’t belong. In this way, there is a risk that the very activities that best boost employability are least accessible to those who need them most.

Murky paths

Growing use of AI may intensify some of these risks. At the moment, a degree still acts as a minimum entry requirement for many personally and financially fulfilling careers. Early studies suggest that AI can particularly help less competent workers achieve better outcomes in standardised professional services tests, suggesting that degree holders may need to do even more to stand out from the crowd than they do at the moment, and that lower-level cognitive work may be automated first and fastest.

This also makes the pathway into graduate careers less clear. Currently students who want to pursue careers in most professions have a clear path ahead of them, with employers keen to diversify traineeship schemes. But AI may quickly automate some of the basic trainee tasks – preparing pitch decks and presentations, summarising arguments, working up architectural details, researching legal precedent – calling into question our whole model of professional development.

These are big societal issues, and universities cannot solve them alone. The AI generation recommends research and analysis of what works best in developing employability skills and a more systematic and fair approach to career-boosting activity such as work placements. But universities can also take the lead as civic institutions, convening government, employers, professional bodies and civil society organisations, to consider what AI will mean for our working lives, and what education and training future generations will need in order to thrive.

First published by WonkHE.