Tag: skills

Movin’ on up

London’s universities are big players in the capital’s economy as well as a visible presence on its streets. They account for 85,000 jobs – more than in the advertising, and architecture and engineering sectors, and almost as many as in accountancy and law – and their economic impact has been valued at £27 billion every year.

Our leading universities are truly global institutions: University College London (UCL) and Imperial regularly feature in global “top ten” rankings, and foreign students make up a large proportion of London’s student population – a success in terms of exports and soft power.

But London’s universities also have a good story to tell about their local impact, and in particular their offer to students from less advantaged backgrounds. Two recent exercises, which I reviewed for University of London, have sought to evaluate how the UK’s universities compare in terms of supporting social mobility by attracting and boosting the careers of students from poorer families or places.

Two years ago, the Sutton Trust and the Institute for Fiscal Studies (IFS) analysed how well universities did in attracting students who had been on free school meals at age 16 and how many of these were in high-earning jobs at age 30. The ten highest-performing universities by these measures were all in London, with Queen Mary University of London, University of Westminster and City University of London taking the top three slots.

A slightly different approach was taken by Professor David Phoenix from London South Bank University. His English Social Mobility Index, which has now been published for three consecutive years, looks at how well students from deprived places perform in terms of access to courses, continuation and completion rates, and then earnings and “graduate employment” one year after graduation.

The 2023 index shows Bradford and Aston universities in the top spots but five of the top ten are London institutions: City, King’s College London, London School of Economics and Political Science (LSE), Queen Mary and UCL.

Neither approach is perfect. No, graduate earnings are not the only measure of the value of higher education. Yes, London is at an advantage because graduates who stay in the city will earn higher salaries (even if most of those evaporate in rent and travel costs). And, yes, focusing on the deprivation of places rather than people does not reflect the differing geographies of poverty inside and outside London.

However, the indices do seem to show London universities – both established institutions with global brands and newer former polytechnics – doing relatively well. This is partly because Londoners from poorer backgrounds are more likely to go to university: 44 per cent of London pupils on free school meals go on to university compared to 27 per cent across England, and eight per cent go to more demanding “high tariff” institutions, compared to four per cent across England.

This is partly a tribute to the performance of London schools, which have shifted from being the worst performing in the country to the best over the past 20 years, particularly for pupils from poorer backgrounds.

The reasons for this have been intensively debated, with some analysis pointing to the investment and focus that came with the London Challenge, and others arguing that it is the ethnic make-up of London’s young population that is driving success – put bluntly, white British pupils drag down the results in other parts of the country.

Some of London’s most successful universities certainly have an intake that reflects the high levels of aspiration in many minority communities: Queen Mary, City, LSE, Imperial and Westminster all have disproportionately large intakes of students from UK Asian backgrounds, though fewer universities (East London, West London, London Met and Middlesex) do so well in recruiting UK Black students. These broad categories also gloss over any differences within different groups, for example between Indian and Bangladeshi, and Black Caribbean and Black African students.

But London’s universities also do well in offering courses that attract students from poorer backgrounds, particularly those looking for a stable and well-remunerated career. Pharmacology, computing, law, economics and business offer the strongest social mobility dividend, according to the IFS/Sutton Trust research.

Nineteen of the 20 top courses in these subjects are in London, with Queen Mary and City universities in the vanguard. And universities work to tailor their courses to student circumstances: in interviews for University of London, teaching staff at Queen Mary emphasised the flexible approach they took to timings and teaching approaches to support students with caring responsibilities, of whom they have a relatively high number.

High participation rates in London show how far university attendance has been normalised here for young people from all backgrounds (in contrast to apprenticeships, where the capital has the lowest take-up of any English region). This may partly result from the widespread presence and visibility of universities, but is also driven by the demands of London’s job market: in 2016, 53 per cent of jobs in London were held by someone with a degree, compared to 30 per cent in the rest of the UK; for senior managerial jobs, the proportions are 64 per cent in London and 38 per cent elsewhere.

But it’s not just the managers. People working in administrative or elementary manufacturing roles are also more highly qualified in the capital. These graduates working in such “non-graduate” jobs may account for London having the lowest proportion of graduates saying that their work was meaningful, fitted with their plans and used the skills they developed in university. Scores were particularly low for those graduates who had lived in London before going to university.

So, London universities play an important part in London’s success as a “social mobility hotspot”, showing how access to higher education can be widened for all classes. There may be opportunities to widen the hotspot: universities from across the UK have opened outposts in London; perhaps London universities could work with local partners to open satellites elsewhere. However, low job satisfaction levels for London graduates also suggests that more needs to be done outside universities, to make work fulfilling for all and to help young Londoners to access a diverse range of post-18 education and training.

Originally publcished by OnLondon

AI: reskilling for the rough beast

I’d like to say that I asked ChatGPT to write me a first draft of this blog, but a) it’s a tiresome cliché, and b) the platform was overloaded when I started writing, so I couldn’t. I’m not surprised. Even over the past couple of months, talk about and use of large language models (LLMs) such as ChatGPT and Bing seems to have been growing exponentially. LLMs will render essay-writing at universities obsolete, hugely accelerate the production of first drafts, and automate the drudge work of academic research.

I am undertaking research on the skills that we will need in the future, and it feels difficult to get a handle on how LLMs and their artificial intelligence (AI) successors will affect these, given the speed at which innovation is advancing and use cases are multiplying. But it also feels careless going on negligent not to do so. So, what might it mean to work with this rough beast, as it slouches towards our workplaces?

Robert Reich’s The Work of Nations

AI will, I think, transform what we currently call the ‘knowledge economy’. Thinking about this sent me back to Robert Reich’s The Work of Nations, and its analysis of the ‘three jobs of the future’. ‘Routine production’ jobs, he wrote, were poorly valued jobs in everything from manufacturing to book-keeping, often moved overseas when he was writing, but also increasingly vulnerable to automation. Many of Reich’s second category, ‘in-person service’ jobs, are less vulnerable to moving overseas (although many are still low-valued by society): even if some shopping has gone on-line, there are still jobs – from brain surgeon to hairdresser, and from bartender to care assistant – that are defined by the need for proximity. The third category, Reich slightly awkwardly describes as ‘symbolic analysts’, comprising everyone from consultants, software engineers and investment bankers, to journalists, TV and film producers, and university professors. These are the elite tier of the global knowledge economy:

“Symbolic analysts solve, identify and broker problems by manipulating symbols. They simplify reality into abstract images that can be re-arranged, juggled, experimented with, communicated to other specialists, and then, eventually, transformed back into reality… Some of these manipulations reveal how to deploy resources or shift financial assets more efficiently, or otherwise save time and energy. Other manipulations yield new inventions – technological marvels, innovative legal arguments, new advertising ploys for convincing people that certain amusements have become life necessities.”

Reich was writing 30 years ago. Since then, the offshoring and automation of routine production has gathered pace, while the rewards accruing to symbolic analyst jobs have increased. But Reich’s description of symbolic analyst jobs underlines how the very features that protected them from routine automation (the combination of analytical skill, a reservoir of knowledge and fluency in communication) may now expose them to a generation of technology that will become increasingly adept at manipulating symbols itself, even if it cannot (yet) ‘think’ or ‘create’. From an architectural drawing to a due diligence report, to an advertising campaign, to a TV show script, to a legal argument, to a news report – there are very few symbolic analyst outputs that LLMs will not be able to prepare, at least in draft.

Revisiting Osborne and Frey

Another way of thinking about the potential impact of more advanced AI on the knowledge economy workplace is to revisit Michael Osborne and Carl Benedikt Frey’s hugely influential analysis. Writing in 2013 Osborne and Frey identified the ‘engineering bottlenecks’ that have held ‘computerisation’ back from specific tasks, and were expected to do so for the next two decades. These included complex perception and manipulation activities, creative intelligence tasks (from scriptwriting to joke-making), and social intelligence tasks (such as negotiation, persuasion, and care).

The growth of LLMs chips away at the second of these, as machines draw on extensive databases to generate coherent content, though their joke-making skills are still a bit iffy. LLMs are also starting to make inroads into the third, as they are deployed as companions or therapists, even if their empathy is performed rather than felt. Engineering bottlenecks still constrain automation, but some are widening much faster than Osborne and Frey predicted. Indeed, one recent assessment suggests that the use of LLM technology will have an impact on around 80 per cent of US workers, with the impact greatest for higher-qualified and higher-paid workers.

That is not to say that AI will ‘destroy jobs’. Like other technologies, AI will probably create new jobs and remodel others. For the moment, there is craft in minding these machines; you need to know how to give instructions, ask questions and evaluate answers. In this, LLMs are like the oracles of classical antiquity, whose riddling utterances contained truth but needed careful interpretation. LLMs can produce good drafts and their accuracy is improving, but they can also ‘hallucinate’ facts, and assert them with a delusional and sometimes aggressive confidence.

This task of interpretation and intermediation is not that far removed from how many professions operate today. Architects, doctors, lawyers, accountants, scriptwriters – even academics – are not pure symbolic analysts, working in an entirely abstract world. Part of their skill, maybe most of it at the top of their professions, is interpersonal – motivating and managing staff, pitching ideas and winning business, convincing clients and colleagues. For these professionals, the current crop of LLMs are best deployed as responsive and multi-talented assistants, which do not get bored, demand pay, or insist on meaningful career development.

Automating menial tasks will disrupt professional development

What does this mean for actual flesh-and-blood assistants and their career development? In many modern professions, life for new recruits is a slog of preparing legal notes, PowerPoint decks, due diligence, and audit reports. I get the sense that some of this is already ‘make-work’, designed to acclimatise a new graduate to the codes and the culture of their profession, but also to give them a chance to see and learn from interactions – in the courtroom, at the client meeting, at the pitch.

If it becomes ever easier and cheaper to commission material directly from machines, that will create a problem not only for future generations of graduates, but also for those at the top of the professions, who will not be able to rely on a stream of graduate trainees to step into their shoes. Even as automation boosts productivity, it will disrupt professional development and may, in the words of one economist, “have stark effects on the value of cognitive labour”.

Furthermore, in the longer term (and I am thinking years not decades), inaccuracy may be less of a problem than the erosion of doubt. A lot of work has already gone into stopping newer LLMs spouting racist opinions like their predecessors did; future models will likely be much clearer about the ‘right answer’ to any question and about the truth of different propositions. Much of this will be helpful, though the lack of transparency and contestability is frustrating.

Minority opinions marginalised and moral judgement at a premium

But as regulation strengthens the guardrails around AI, there is a risk that some minority opinions will be marginalised and eventually expunged. Many of these will be conspiracy theories, junk science and fake news. But they may also be the small voices of gritty corrective to the dominant narrative – the proponents of ‘lab leak theories’ of COVID-19, the dogged campaigners against over-prescription of painkillers, the investigative journalists who stick to the story in the face of denials and threats.

This has inevitably already become a new front in the ‘culture war’, with some media getting angry that ChatGPT refuses to promote fossil fuel use, sing paeans of praise to Donald Trump or say that nuclear war is worse than racist language. So far so funny. But the more the unified version of the truth promoted by AI squeezes out alternative understandings of facts, let alone alternative interpretations of how they should guide our behaviour, the more we will need the ability to challenge and debate that truth, the imaginative capacity to transcend guardrails.

So, what does this all mean for skills? A knowledge economy in which LLMs are increasingly widespread will require critical judgement, a basic understanding of how coding, algorithms and emerging AI technologies operate, the ability to work with clients and colleagues to refine and use results, and the diverse and creative intelligence to challenge them.

Perhaps above all, we will need sophisticated moral judgement. LLMs and their AI successors will be able to do many things, but there will be so many complex judgements to be made about whether and how they should. Who will be accountable for any errors? Is it for a machine to define truth? Should it do so by reference to a consensus, or its own judgements of correspondence to reality? At an existential level, how should we achieve the alignment of AI and human interests? How are the latter to be defined and articulated? What balance of individual and social goods should be struck? Where are the boundaries between humans and machines? Do the machines have rights and obligations?

Today we muddle along, reaching consensus on moral issues through a broad process of societal mediation, with horrible moral errors along the way. Tomorrow, we have the potential for a new age of turbocharged progress and moral clarity, a prospect that is at once scintillating and unsettling.

First published by LSE Business Review.