Many innovations have improved the COVID-19 response and could be key for future-proofing against pandemics. What are the governance and privacy concerns?
Overview of change
Automation and the greater use of digital technologies have long been seen as key factors that will influence the way we work in the future.1 Advances in robotics and digital technologies (including AI) are continuing to enable the automation of a greater range of tasks. This includes automation of physical tasks (such as using robotics in factories to operate production lines) and knowledge-based work (such as report writing and language translation). Industrial robotics are already being used across a range of sectors, including food and drink, pharmaceuticals, and cosmetics.2,3 AI technologies are increasingly being used for customer service roles, for example, the use of AI chatbots to deal with customer queries.
Many organisations have turned to robotics and digital technologies during the COVID-19 pandemic to aid social distancing, help meet increased demand for certain goods and services, and minimise the need for people to work in environments that may put them at risk.4,5 For example, robotics and automated systems have been deployed for tasks including cleaning hospitals, warehouses and public spaces; and delivering food shopping to people at home.6–9 A July 2020 global survey by McKinsey found that 67% of companies that responded had accelerated their deployment of automation and AI during the pandemic.10,11
Challenges and opportunities
Automation of routine and administrative tasks could cut costs and increase productivity. In some cases, automation may also improve safety by keeping humans away from hazardous environments.12–14 Many experts also suggest that technology will increasingly be able to perform certain tasks with more accuracy than humans and offer better outcomes. For example, AI-based diagnostic technologies may perform more accurately than a clinician, leading to better health outcomes.15
While there are numerous benefits to automation, there are associated challenges. These include concerns about how it will impact the labour market, uneven distribution of its benefits, and whether the future workforce will have the appropriate skills needed to work alongside technology.16 Estimates of the impact of automation on the labour market vary.17,18 A 2018 analysis by PwC found that, by 2030, 30% of UK jobs will be susceptible to automation by AI and robotics.17 However, it also found that many new jobs are likely to be created, with a net positive impact on the economy. Some experts have highlighted that it is important to consider which activities within job roles can be automated, as in many cases it is likely that only certain aspects will be automated rather than the entire role.19,20 Human capabilities required for some roles cannot be easily automated with current technology (for example, social and emotional reasoning).19
Automation is likely to be spread unevenly across different industries and occupations, meaning its impact will vary across different sectors, locations and demographic groups.21–23 Evidence suggests that automation is likely to disproportionately disadvantage young people, low earners, women and those with lower levels of education.5 Many stakeholders have highlighted the need to ensure that automation does not reinforce existing inequalities in the workforce.2 Future jobs are likely to require new and different skills. These include the skills required to work alongside technology, such as those needed to supervise and maintain automated systems, and more specialist skills needed to develop new technologies, such as engineering and coding. Concerns have been raised that digital skills training and education may not keep pace with technological developments, leading to a wider digital skills gap in the labour market. Research published in 2019 by the Royal Society found that demand for workers with specialist data skills had more than tripled over the previous 5 years, and that more action was needed to address this demand.24
Further challenges associated with automated technologies in the workplace include the technical feasibility of introducing them into different settings and the cost for businesses. There is also debate around what safety standards are required as they become more widespread.25,26 Some experts have also highlighted that, while technology can support existing roles and allow people to spend more time on more fulfilling tasks, it will also create the need for more workers in roles that involve managing these systems, such as data labelling and moderation of content. There are some concerns about the quality of such jobs and the risk that they may be undervalued.27,28
While digital technologies and automation are forecast to disrupt a wide variety of sectors, it is difficult to predict the pace at which technology will be adopted. Factors that are likely to affect the speed of adoption include the cost, regulation and public opinion.25 Adoption is also likely to depend on developments in other areas, such as battery technologies and edge computing (POSTnote 631).
It is currently unclear what the full impacts of automation and digital technologies will be on jobs and employment, and how this may have changed as a result of the pandemic. Some businesses expect that the rapidly deployed technological and digital innovations they have put in place during the pandemic are likely to remain in place,29 however this is likely to differ between sectors.
Key questions for Parliament
- What type and level of government support may be needed by those whose jobs are at risk of automation?
- What are the implications of the disproportionate impact of automation on certain groups, including the impact of regional variation?
- What action is needed to ensure automation does not reinforce or worsen inequalities in the workforce?
- What upskilling and re-training is needed to ensure staff can work alongside robotics and autonomous systems in the future? Is current investment and focus on digital skills sufficient?
- Are changes in the curriculum needed to ensure that children and young people are prepared for future jobs?
- Are new policies needed to maximise the benefits of technologies in terms of improving workplace productivity and job quality?
- What standards of safety and efficacy will future automated systems in the workplace need to meet?
Likelihood and impact
High impact and medium likelihood in next 5 years.
- Points, L. et al. (2017). Artificial Intelligence and Automation in the UK.
- House of Commons Business, Energy and Industrial Strategy (BEIS) Committee (2019). Automation and the future of work. House of Commons BEIS Committee.
- Department for Business, Energy & Industrial Strategy (BEIS) (2017). Made Smarter Review. BEIS.
- Mims, C. (2020). As E-Commerce Booms, Robots Pick Up Human Slack. Wall Street Journal.
- Wallace-Stephens, F. et al. (2020). Who is at risk? work and automation in a time of covid-19. Royal Society of Arts.
- Tucker, I. (2020). The five: robots helping to tackle coronavirus. The Guardian.
- Zemmar, A. et al. (2020). The rise of robots in surgical environments during COVID-19. Nature Machine Intelligence, Vol 2, 566–572.
- Combs, V. (2020). Interest in autonomous vehicles and delivery drones grows during COVID-19 pandemic. TechRepublic.
- Lee, T. B. (2020). The pandemic is bringing us closer to our robot takeout future. Ars Technica.
- McKinsey & Company (2020). How COVID-19 has pushed companies over the technology tipping point—and transformed business forever. McKinsey.
- McKinsey Global Institute (2020). What 800 executives envision for the postpandemic workforce. McKinsey.
- Lu, X. et al. (2018). Design and analysis of a climbing robot for pylon maintenance. Industrial Robot: An International Journal, Vol 45, 206–219.
- Kas, K. A. et al. (2020). Using unmanned aerial vehicles and robotics in hazardous locations safely. Proc Safety Prog, Vol 39,
- Vaughan, A. (2018). AI and drones turn an eye towards UK’s energy infrastructure. ARPAS UK.
- Tankelevich, L. et al. (2018). Advancing AI in the NHS. Polygeia.
- Shepheard, M. (2020). Technology and the future of the government workforce. Institute for Government & SAP.
- PwC (2018). Will robots really steal our jobs? An international analysis of the potential long term impact of automation. PwC.
- McKinsey & Company (2017). Jobs lost jobs gained: workforce transitions in a time of automation. McKinsey Global Institute.
- McKinsey & Company (2017). A future that works: automation, employment and productivity. McKinsey Global Institute.
- Willcocks, L. (2020). Robo-Apocalypse cancelled? Reframing the automation and future of work debate: Journal of Information Technology, Vol 35, 286–302.
- PwC (2015). PwC UK economic outlook 2015. PwC.
- PwC (2018). PwC UK economic outlook 2018. PwC.
- Office for National Statistics (ONS) (2019). The probability of automation in England: 2011 and 2017. ONS.
- Royal Society (2019). Dynamics of data science skills. Royal Society.
- Royal Academy of Engineering and National Engineering Policy Centre (2020). Safety and ethics of autonomous systems. Royal Academy of Engineering and National Engineering Policy Centre.
- Studley, M. et al. (2020). ELSA in Industrial Robotics. Curr Robot Rep, Vol 1, 179–186.
- European Parliament. Directorate General for Parliamentary Research Services. (2020). The ethics of artificial intelligence: issues and initiatives. European Parliament.
- Chen, A. (2019). How Silicon Valley’s successes are fueled by an underclass of ‘ghost workers’. The Verge.
- Romei, V. (2020). Pandemic boosts automation and robotics. Financial Times.
Flexible working could increase wellbeing and productivity, but benefits are not equally distributed throughout the population and could increase inequalities.
Upskilling and retraining adults is key to addressing future challenges and benefits productivity, health and wellbeing, social justice and communities.