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| Big tech firms' AI hiring frenzy leads to brain drain at UK universities | Big tech firms' AI hiring frenzy leads to brain drain at UK universities |
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| British universities are being stripped of artificial intelligence (AI) experts in a brain drain to the private sector that is hampering research and disrupting teaching at some of the country’s leading institutions. | British universities are being stripped of artificial intelligence (AI) experts in a brain drain to the private sector that is hampering research and disrupting teaching at some of the country’s leading institutions. |
| Scores of talented scientists have left or passed up university posts for salaries two to five times higher at major technology firms, where besides getting better pay, new recruits can take on real-world problems with computer power and datasets that academia cannot hope to provide. | Scores of talented scientists have left or passed up university posts for salaries two to five times higher at major technology firms, where besides getting better pay, new recruits can take on real-world problems with computer power and datasets that academia cannot hope to provide. |
| The impact of the hiring frenzy is revealed in a confidential Guardian survey of the UK’s elite Russell Group universities, which found that many top institutions were struggling to keep up with the demand from tech firms that are aggressively expanding their AI research groups. | The impact of the hiring frenzy is revealed in a confidential Guardian survey of the UK’s elite Russell Group universities, which found that many top institutions were struggling to keep up with the demand from tech firms that are aggressively expanding their AI research groups. |
| One university executive said AI researchers were courted by industry on a routine basis and that departments regularly missed out on the best talent when companies made better offers. “We need top quality staff to teach and research and the implications of not achieving this don’t need to be spelt out,” the executive told the Guardian. “There are no easy answers, but this is an issue with national implications.” | One university executive said AI researchers were courted by industry on a routine basis and that departments regularly missed out on the best talent when companies made better offers. “We need top quality staff to teach and research and the implications of not achieving this don’t need to be spelt out,” the executive told the Guardian. “There are no easy answers, but this is an issue with national implications.” |
| Universities exist, in part, to meet the needs of industry, but the fierce demand for skilled AI researchers is heavily outstripping supply, according to universities who took part in the survey. The picture is supported by data from the global job site Indeed, where the economist Mariano Mamertino said the number of AI jobs in Britain had soared 485% since 2014. It means there are more than two jobs for every qualified jobseeker, the company’s figures show. | Universities exist, in part, to meet the needs of industry, but the fierce demand for skilled AI researchers is heavily outstripping supply, according to universities who took part in the survey. The picture is supported by data from the global job site Indeed, where the economist Mariano Mamertino said the number of AI jobs in Britain had soared 485% since 2014. It means there are more than two jobs for every qualified jobseeker, the company’s figures show. |
| “This goes beyond the normal exchange of people between academia and industry,” one senior academic told the Guardian. “It already affects university research because of the difficulty of recruitment, and is definitely in danger of creating a ‘missing generation’ with consequences for future teaching and research.” | “This goes beyond the normal exchange of people between academia and industry,” one senior academic told the Guardian. “It already affects university research because of the difficulty of recruitment, and is definitely in danger of creating a ‘missing generation’ with consequences for future teaching and research.” |
| The Guardian’s survey was completed by leading research universities selected for their strength in computing and artificial intelligence, including Oxford, Cambridge, Edinburgh, UCL and Imperial College London. | The Guardian’s survey was completed by leading research universities selected for their strength in computing and artificial intelligence, including Oxford, Cambridge, Edinburgh, UCL and Imperial College London. |
| Maja Pantic, professor of affective and behavioural computing at Imperial, was not approached for the survey, but confirmed its findings. “We are losing the next generation of academics,” she said. “A lot of people believe this is a phase that will pass. To me, that’s like being the ostrich that puts its head in the sand. In the end society will suffer.” | Maja Pantic, professor of affective and behavioural computing at Imperial, was not approached for the survey, but confirmed its findings. “We are losing the next generation of academics,” she said. “A lot of people believe this is a phase that will pass. To me, that’s like being the ostrich that puts its head in the sand. In the end society will suffer.” |
| “The majority of top people who leave academia move to Google, Facebook, Amazon and Apple,” Pantic said. “The real problem is these people are not dispersed through society. The intellect and expertise is concentrated in a small number of companies.” | “The majority of top people who leave academia move to Google, Facebook, Amazon and Apple,” Pantic said. “The real problem is these people are not dispersed through society. The intellect and expertise is concentrated in a small number of companies.” |
| AI has become a boom industry on the back of new techniques that use algorithms and data to build statistical models of everything from speech and handwriting to shopping habits and objects such as cats and dogs. The technology underpins great swaths of modern digital services from Google’s language translation and Apple’s Siri voice recognition to Amazon’s product recommendations and the articles that appear in Facebook news feeds. | AI has become a boom industry on the back of new techniques that use algorithms and data to build statistical models of everything from speech and handwriting to shopping habits and objects such as cats and dogs. The technology underpins great swaths of modern digital services from Google’s language translation and Apple’s Siri voice recognition to Amazon’s product recommendations and the articles that appear in Facebook news feeds. |
| A central goal of the field of artificial intelligence is for machines to be able to learn how to perform tasks and make decisions independently, rather than being explicitly programmed with inflexible rules. There are different ways of achieving this in practice, but some of the most striking recent advances, such as AlphaGo, have used a strategy called reinforcement learning. Typically the machine will have a goal, such as translating a sentence from English to French and a massive dataset to train on. It starts off just making a stab at the task – in the translation example it would start by producing garbled nonsense and comparing its attempts against existing translations. The program is then “rewarded” with a score when it is successful. After each iteration of the task it improves and after a vast number of reruns, such programs can match and even exceed the level of human translators. Getting machines to learn less well defined tasks or ones for which no digital datasets exist is a future goal that would require a more general form of intelligence, akin to common sense. | A central goal of the field of artificial intelligence is for machines to be able to learn how to perform tasks and make decisions independently, rather than being explicitly programmed with inflexible rules. There are different ways of achieving this in practice, but some of the most striking recent advances, such as AlphaGo, have used a strategy called reinforcement learning. Typically the machine will have a goal, such as translating a sentence from English to French and a massive dataset to train on. It starts off just making a stab at the task – in the translation example it would start by producing garbled nonsense and comparing its attempts against existing translations. The program is then “rewarded” with a score when it is successful. After each iteration of the task it improves and after a vast number of reruns, such programs can match and even exceed the level of human translators. Getting machines to learn less well defined tasks or ones for which no digital datasets exist is a future goal that would require a more general form of intelligence, akin to common sense. |
| The surge of interest in AI means that leading universities are facing a flood of applications from good students just as staff are leaving or moving to part-time roles. Some universities who responded to the survey said research was being hit not only by the loss of scientists, but the lack of computer power and datasets needed to run experiments on the scale now routine in industry. | The surge of interest in AI means that leading universities are facing a flood of applications from good students just as staff are leaving or moving to part-time roles. Some universities who responded to the survey said research was being hit not only by the loss of scientists, but the lack of computer power and datasets needed to run experiments on the scale now routine in industry. |
| A number of prominent AI researchers have recently moved to industry. In March, Zoubin Ghahramani, head of machine learning at Cambridge and one of the most respected AI researchers in the country, became chief scientist at Uber, the San Francisco-based ride-hailing firm. Neil Lawrence, professor of machine learning at Sheffield University, has moved his research group to Amazon in Cambridge. Murray Shanahan, professor of cognitive robotics at Imperial, along with Yee Whye Teh and Andrew Zisserman at Oxford, has taken a post at Google’s DeepMind, which now runs AI courses at University College London and Oxford. | A number of prominent AI researchers have recently moved to industry. In March, Zoubin Ghahramani, head of machine learning at Cambridge and one of the most respected AI researchers in the country, became chief scientist at Uber, the San Francisco-based ride-hailing firm. Neil Lawrence, professor of machine learning at Sheffield University, has moved his research group to Amazon in Cambridge. Murray Shanahan, professor of cognitive robotics at Imperial, along with Yee Whye Teh and Andrew Zisserman at Oxford, has taken a post at Google’s DeepMind, which now runs AI courses at University College London and Oxford. |
| For many universities the brain drain is most intense among early career researchers. While Indeed found the average salary for a machine learning engineer was £54,366, the Guardian survey found that some of the best younger researchers left academia for industry jobs paying £80,000 to £200,000. | For many universities the brain drain is most intense among early career researchers. While Indeed found the average salary for a machine learning engineer was £54,366, the Guardian survey found that some of the best younger researchers left academia for industry jobs paying £80,000 to £200,000. |
| Some academics believe the surge in demand will settle down, as happened in the telecoms and dotcom booms. But others want universities, companies and the government to take action. Many of those who responded to the survey said universities must allow more part-time positions and industry secondments, pay higher salaries funded by master’s courses and take on industry-backed research projects. | Some academics believe the surge in demand will settle down, as happened in the telecoms and dotcom booms. But others want universities, companies and the government to take action. Many of those who responded to the survey said universities must allow more part-time positions and industry secondments, pay higher salaries funded by master’s courses and take on industry-backed research projects. |
| DeepMind, Amazon and Microsoft would not discuss how many AI researchers they had recruited in recent months, but DeepMind has about 200 researchers drawn heavily from Oxford and UCL. Chris Bishop, lab director at Microsoft Research Cambridge, said the company had a long history of a two-way flow of researchers between itself and universities that was beneficial to all. “Attracting students away from their studies prematurely risks undermining the long-term health of our industry,” he said. “We instead aim to preserve and nurture new talent within academia in a way that is sustainable and mutually beneficial.” | DeepMind, Amazon and Microsoft would not discuss how many AI researchers they had recruited in recent months, but DeepMind has about 200 researchers drawn heavily from Oxford and UCL. Chris Bishop, lab director at Microsoft Research Cambridge, said the company had a long history of a two-way flow of researchers between itself and universities that was beneficial to all. “Attracting students away from their studies prematurely risks undermining the long-term health of our industry,” he said. “We instead aim to preserve and nurture new talent within academia in a way that is sustainable and mutually beneficial.” |