We are at what technology enthusiasts like to call ‘peak robots'. You need to look no further than the recent headlines to spot the prevailing narrative about robots being a force for bad - whether stealing jobs or in the words of Stephen Hawkins at last week's Web Summit "destroying humanity".
There's no question that artificial intelligence (AI) and machine learning are having a transformational effect on our world - especially our workplace. However, much of the debate around automation to date has focused on just one part of the story: its implications for the workplace and jobs, rather than its impact on job seekers themselves.
The first wave of the digital revolution saw the internet give unprecedented access to job opportunities and democratise the job search process; but with millions of jobs online, the process of separating wheat from chaff and finding the best-fit job or the best talent is a cause for headache for candidates and companies alike.
The key here is to draw on the power of that data - whether from job search behaviour; analysing CVs; or studying reviews to train algorithms to overcome some of the complex challenges with job searches today. Done correctly, that data can not only be used to predict which jobs are most relevant - it can also personalise the job search results, and protect job seekers from fraudulent ads.
By overlaying historical behavioural data with insights into labour market trends, the task of matching searches with specific jobs can be made much easier. Working together with human supervision, algorithms can fill in the blanks that often exist in the job descriptions. Such a system can predict salaries, classify unusual job titles and make many other predictions to display only relevant jobs. For example, using historical pay data to predict salaries pushes employers to be more transparent about their wage practices and removes the age-old smoke and mirrors around pay for job seekers.
Other forms of AI, such as natural language processing, can extract critical information that paints a personal picture of what a candidate desires, or can make the requirements of a job description computer-friendly. By processing these contextual clues, AI can generate bespoke search results that match the job seeker's goals and experience. In this way, algorithms are helping the almost of half of job seekers, who currently find job searches overwhelming and time-consuming.
Looking beyond the CV
However, CVs don't necessarily paint the full picture of the job seeker. Integrating automated assessments into the application process offers the opportunity to see how a candidate can perform a job; for example, a large contact centre in the EU uses AI-powered language proficiency assessment to source seven different languages in one location. At one of the hiring stages, applicants talk to an AI conversation agent in the target language for about 10 minutes. This gets automatically analysed for ease of communication and fluency, providing a vastly better experience for those looking for a job and employers.
Encouragingly, our recent study showed that, far from fearing the rise of robots in the workplace, jobseekers are starting to recognise the value of AI to overcome the common gripes with finding the right role. In fact, they don't see machines as career limiting. Instead, the perception now is that robots could act as ‘smart career coaches', helping to break down common barriers around discrimination. They also place more trust in machines helping with their job search than driving their cars or carrying out medical assistance.
The opportunity for AI to help tackle the challenges facing the labour market is clear. However, if we want to make full use of it across all industries, we need more than the technology; we need a skilled workforce with the right expertise.
AI can widen the net to address the UK's skills shortage
It's a well-known fact that the UK is suffering a chronic STEM skills shortage. Although there's a need for talent across all these sectors, among the most pressing is the demand for skilled experts, particularly those who understand AI. Our data shows that senior roles are proving tricky for employers, with nearly half of the hardest-to-fill roles being seen in experienced developer positions.
It doesn't take a computer scientist to work out that for post-Brexit Britain to be an economic success, it's going to need to continue to be an attractive place for diverse tech talent.
This issue is also being recognised and highlighted by the UK government, having recently published a major review of the UK's AI industry to better understand the scale of opportunity to the economy. The review makes several recommendations around talent, from increased diversity through to industry-funded academic programmes.
To achieve that goal, industry, policy makers and academics must all work together to establish a clear framework for tech education that nurtures the next generation of developers, data scientists and machine learning experts.
If we stop there, though, we won't ever solve the problem. Tech employers need to be smarter about how they identify talent. Too often, companies go fishing in the same, limited pool of people that graduate from specific universities. This can leave behind some high-quality individuals who learned their skills elsewhere.
As employers, we need to keep challenging ourselves to think differently about how we find the talent that can power our businesses. But recruitment has never been a one-way street. Job seekers themselves have a role to play. That's why they need the tools that can help find the best role of them. This is where AI can be a game-changer.
Raj Mukherjee is SVP of product at Indeed
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