Arguably, one of the biggest barriers to effective reskilling of the workforce is the lack of centralized support. This article delves into this issue in depth through a comparison of the private and public sectors. It then looks at previous government-driven reskilling, and unearths why the private sector is nevertheless the main driving force behind AI-motivated reskilling initiatives.
The key differences
The main distinction between the private sector and the public sector is that the former is driven by profit whereas the latter focuses on the delivery of a service that benefits society. For this reason, the public sector is less affected by market fluctuations than the private sector. This also means it typically moves at a slower pace, because it does not have to compete for an edge in the market.
The main public sector industries are education, law, and healthcare. It is interesting to note that it is these industries that are often at the forefront of debates over the ethical use of AI.
The private sector encompasses a far broader array of industries, and is where the majority of employment is. In the UK, the private sector accounted for 27 million employees in 2020, which was over 5 times more than the public sector. Certain industries, such as fashion, retail, and hospitality are only private sector, but many industries span both the public and private sector.
While it can be generalised that the public sector moves at a slower pace, one area that it typically takes the lead in is the provision of training and upskilling opportunities for current or future employees. For example, councils often work with schools and colleges to provide training schemes that address their skills gaps. Nevertheless, training opportunities can be quicker in the private sector if they relate to a gap in the market where skills are needed.
The public sector falls behind
Currently, with a predicted skills mismatch in the market, the private sector has so far shown greater initiative in driving reskilling initiatives. 49% of public sector organisations anticipate that they will respond to the changing demands of the corporate world through AI integration. Large private sector firms almost double this rate of AI adoption, with 90% reporting the current or planned use of AI.
A recent Crunchbase report found that investment levels have peaked in private companies which provide resources for reskilling such as Guild, Workera, Articulate, and Degreed. This confirms that there is significant financial interest in reskilling, although many investors are likely to be interested in the economic benefits reskilling could bring from widespread adoption in public sector industries such as the NHS.
More strikingly, a survey conducted by PWC found that public sector employees are less likely than private sector employees to believe that the skills needed to do their jobs will change in the next 5 years. Employees also have less clarity on how AI will affect their jobs, and are less confident that their organisation can help workers develop capabilities. Furthermore, public sector focus is not currently tech-oriented, with employees viewing the development of soft skills such as collaboration, critical thinking and being flexible as more critical than tech skills such as digital aptitude, data analytics or green skills.
Overall, while stock market trends and skills gaps are pushing private sector companies to invest in reskilling their employees, the public sector as of yet shows a lack of direction in AI-focused reskilling, and less certainty about the impact of AI and automation on its industries.
Slow and steady wins the race?
The seemingly slow initiative of the public sector when it comes to reskilling is not because of the government’s inability to implement effective training schemes. Previously, several successful reskilling initiatives have been launched to combat various challenges facing the employment industry. This has been showcased most recently by the government’s response to the Covid-19 crisis.
In 2020, the Lifetime Skills Guarantee was launched to mitigate the disruption to employment caused by high levels of furlough, redundancy, and businesses ceasing to trade. The government promised £95 million in funding to the scheme, which set out to transform the adult education system by providing free access to Level 3 qualifications for all adults who do not already have A-levels or advanced diplomas. Previously, this was only funded for candidates under 24 years of age.
The main motivation for the scheme was to enable increased agility and flexibility in employment, during a period when many people were re-evaluating their career paths. This trend was exacerbated by the pandemic which gave many employees time off work to evaluate their career goals. It also increased general awareness of job instability, as businesses began implementing technology and AI software to facilitate remote working during the lockdowns.
Importantly, the Lifetime Skills Guarantee was not just intended as a short term measure to mitigate of the impact of Covid, but as a long-term measure to combat forecasted permanent changes in desired skillsets, with 64% of employers anticipating the need to develop the skills of their employees in 2019. Indeed, further commitment has been pledged to the scheme, with the Skills for Jobs whitepaper in 2021 setting out further plans for reskilling that focuses particularly on technical qualifications to address the impact of AI on the business sector.
Overall, we can see that the government is capable of taking action to prepare for the impact of AI and the resulting changes in sought-after skills. Indeed, a holistic review by CIPD finds that the government has prioritised a digital learning and reskilling agenda through a variety of schemes and financial investments. So why is it that the private sector is surpassing the public sector in the reskilling race, and the outlook of public sector employees is so different to that of private sector employees?
You don’t gamble to win…
The answer to the above question is surprisingly simple: risk. Looking at the high stakes involved in AI’s application to public sector workplaces can explain why this sector is taking a slow and steady approach to reskilling and AI integration. The stakes are higher in the public sector than the private sector for 2 main reasons.
The first reason is that public sector industries involve greater risk both in terms of data protection and in terms of the damage that could be caused if the AI system made a mistake or was hacked.
In terms of data protection, the risk is greater in public sector companies because they typically have larger datasets that contain more sensitive information about people. A good example is the legal sector, which collects personal and often sensitive information (i.e. criminal record, family history, witness statements, etc) about many individuals in the UK. The repercussions of a data leak here would be far more severe than the leaking of data from a private sector retailer that had collected non-sensitive data (e.g. age, gender, purchase history) about its clients.
In terms of AI technology making a mistake or being hacked, the potential amount of damage that could be caused is particularly alarming in the public sector. In the NHS, for example, the high stakes are human lives. This is why, for the most part, AI is being integrated into public sector industries in low-level, low risk ways, such as automating admin based tasks, or as an assistance mechanism which can provide extra verification services to human workers.
Mark Hitchman, from Canon Medical Systems, explains the need for cautious and monitored use of AI in diagnostic healthcare:
“The rising adoption of AI for diagnostics will require an increase in the section of the workforce in healthcare that is directly involved with IT. For AI to be used safely, there will need to be governance platforms and constant monitoring as we know that AI accuracy can drift in certain circumstances.”
Mark Hitchman, Managing Director at Canon Medical Systems
The second reason the stakes are higher in the public sector is because it is accountable to the public, being funded by taxpayers’ money. This increases the risk factor in terms of its impact on public sentiment towards AI. Public opinion not only has a lot of sway over AI’s future use, but is also the government’s most highly valued commodity. Therefore, public sectors are likely to hold back from risky and innovative use of AI for fear of public criticism, which could lead to a broader condemnation of AI’s use in public services.
While these two considerations explain why the public sector is more cautious with integrating AI technology in general, you might still be left wondering why it is not embracing reskilling. After all, isn’t one of the most crucial reasons to reskill to ensure the safe and effective integration of AI into the workplace? It could be that with the current and foreseeable applications of AI being limited to low-risk tasks, there is not much need for employees in many public sector occupations to be reskilled, since AI will not be used for complex tasks that require advanced knowledge and training for quite some time.
Indeed, according to Asa Whillock, VP of software company Alteryx, there may not be as much need to reskill in the public sector as anticipated, especially with the development of increasingly user-friendly applications.
“Every public sector organisation already has a large pool of talent with the right combination of essential knowledge and interest in the technology and soft skills suitable for generative AI to be unleashed to its full potential. Empowering this talent through access to data and self-service, low-code/no-code analytics removes the complexity of data science, while cloud computing provides the scale and agility needed to break down barriers and remove the isolated intelligence currently hindering many organisations.”
Asa Whillock, VP and General Manager Machine Learning at Alteryx
Nevertheless, even with increased ease of access and usability, AI’s integration into the public sector still faces the issue of high cybersecurity risks. For this reason alone, it looks like the private sector will be the guinea pig when it comes to AI integration, gambling with higher risks alongside higher rewards. This will mean that the public sector can watch and learn, and ensure that its integration of AI is as risk-free as possible.
