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Whitehall could save 2.6 billion with automation.
250,000 public sector employees could be replaced by robots over the next 15 years, according to a report by Think Tank Reform.
The report, which addresses the creation of a public services workforce organised around the needs of its users, advocates the reduction of staff in favour of automation and digital technology.
Citing analysis by Oxford academics Frey and Osbourne, in which the academics said that admin roles have a 96% chance of being automated by current technology, the report applied their calculations to current public sector numbers. The report found that, over the next 10 to 15 years, central government departments could further reduce headcount by 131,962, saving 2.6 billion from the 2016-17 wage bill.
The report sells automation as the new approach which is needed, saying:
Public services should deliver outcomes that matter to users, and meet expectations of interacting via technology. This approach would see services designed around users and render at least 248,860 administrative roles redundant. The accuracy of decision-making can be further improved by using artificial intelligence to make complex decisions and by understanding why mistakes that, for example, cause 10 per cent of hospital patients to suffer from medical error, are made.
Further calculations found that the NHS could automate 91,208 of 112,726 administrator roles (outside of primary care), reducing the wage bill by approximately 1.7 billion. In primary care, a pioneering GP provider interviewed for the paper has a clinician-to-receptionist ratio of 5:1, suggesting a potential reduction of 24,000 roles across the NHS from the 2015 total. In total this would result in 248,860 administrative roles being replaced by technology.
These findings were further bolstered by the success HM Revenue and Customs (HMRC) has had in recent times in regrads to automation. Over the last decade, HMRC has reduced its admin staff from 96,000 to 60,000 through expanding its online services and providing real-time information.
Including all types of roles, not just admin, the report said that even the more complex roles in public services stand to be automated. The report said:
Even the most complex roles stand to be automated. Twenty per cent of public-sector workers hold strategic, cognitive roles. They will use data analytics to identify patterns improving decision making and allocating workers most efficiently.
The NHS, for example, can focus on the highest-risk patients, reducing unnecessary hospital admissions. UK police and other emergency services are already using data to predict areas of greatest risk from burglary and fire.
Some technology, will not replace humans, but enhance the work humans produce, with the report stating that some technology will improve public-service delivery. Artificial Intelligence, drones and facial recognition technology should be evaluated by various public services, specifically policing, as alternatives to current practices.
Experts were quick to criticize the report, with many saying that the stark figures overlooked the human cost of such automation. Other critics, like Redwood Softwares Neil Kinson, pointed out that the obsession of humans vs robots would actually hinder the development of robotics and AI.
The implementation of robotics across the public sector will ensure that efficiencies will be gained, simply by taking the robot out the human. That is, freeing staff up from repetitive manual tasks to allow them to focus their efforts on more value-add, strategic activities. However, as long as we remain fixated on the idea that robots replace humans, or narrowly define the sets of tasks to which we can apply robotics, the true potential of robotic process automation will be overlooked. Robotics brings the opportunity to completely re-imagine how the entire process is executed e.g. cash to billing, record to report, procure to pay as well as the interdependencies between these processes.
Its time for a shift in language on how the robotics revolution is defined and explained.
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