Category Archives: Technology

Mind the gap: digital skills in the age of artificial intelligence

By Adriana Hamacher

Digital Skills Gap

Esther Animashaun was working as a sales associate for stationery retailer Moleskine when opportunity came knocking. Having dropped out of college uninspired by what she was learning, Esther still refused to give up on a career in IT. But she was after something different and one day she found it via an apprenticeship provider. Esther is now working to plug a gaping hole in the UK’s IT skills pipeline, the result of burgeoning demand for artificial intelligence technology. AI investment is gaining momentum; 42 per cent of companies are planning to ramp up spending over the next five years and one in five has recently done so, according to a new survey by the Confederation of British Industry in association with IBM.

The benefits are irresistible. AI technologies promise to improve operational efficiency and reduce costs, they also upgrade legacy IT systems, improve data and analytics, enhance client services and, as a result, increase revenue generation.

Experts estimate that over the next six months business leaders plan to hire more programmers, project managers and apps developers. And within the next three years the emphasis will be on finding data analysts, cyber security experts and artificial intelligence and automation specialists.

The only problem is that workers like Esther are thin on the ground. According to MPs, the UK will have a shortfall of 745,000 workers with the necessary digital skills by the end of the year and looming immigration controls are doing us few favours.

Highly prized

Digital skills are generally understood to be the ability to use computers and digital devices to access the internet; the ability to code or create software and to critically evaluate media. The Tech Partnership, the UK’s vehicle for action on digital skills also highlights information management, communication, problem solving and creativity. These, they say, are the skills most highly prized by employers.

What’s meant by artificial intelligence also needs definition. AI is often used very loosely to describe various technologies capable of addressing operational efficiency and other needs. They fall — broadly — into three business categories:

  • Robotic Process Automation: to replace manual handling of repetitive and high-volume tasks.
  • Machine Learning: using vast amounts of data to train a system and fine tune it (Deep Learning is a specific method of machine learning and has been a game-changer in this space).
  • Cognitive Analytics: making deductions from vast amounts of data, using processes that mimic the human brain.

Unusually for someone working in a field as specialised as AI, Esther has no university degree. She and four male colleagues have been hired by back-office solutions company Voyager to bolster its Robotic Process Automation (RPA) development team, in response to competition from offshore service providers. RPA is, in the short term, expected to account for a large slice of AI spending, particularly within the financial sector where Voyager operates. The apprentices are learning to model business processes and training robots to interact with a wide range of systems. They work for the company for four days a week and study for the remainder.

Insurance provider Aviva is another example of a company that’s investing heavily in AI and associated technologies. Aviva’s technology hub for product development has radically streamlined customer services, but it’s also meant changing skill set requirements for the firm; rather than recruiting for actuaries, Aviva now can’t hire enough data scientists.

Increasing requirements

Aviva’s experience reflects what is likely to be a common pattern: a focus by future thinking employers and employees on those areas which the machines won’t replace. In the age of AI, machines won’t take over the digital world (studies indicate that only 5% of jobs can be completely automated), but the scope of that world will radically increase.

The financial sector is a pertinent example. Management consultancy Opimas forecasts that, by 2025, AI will lead to around 230,000 less jobs in the sector. Asset management will shrink the most, with around 90,000 people being replaced by machines. On the other hand, close to 30,000 new jobs will be created for technology and data providers, in response to the financial industry’s increasing requirements and demands.

Thus AI can be viewed as a building block for digital skills. Job candidates, like Esther, who have passion and a desire to learn (rather than those with highly-defined technical skills) may be the best way to bridge the gap and to avoid job automation for tech roles in the future, with training on the job increasingly prevalent. A survey by recruitment agency Mortimer Spinks indicates that 33 per cent of new tech and digital workers enter the sector through cross-training via unofficial means, such as shadowing or learning in their own time. Paul Church, director at Mortimer Spinks, warns: “If you don’t have a desire to learn, you are going to get left behind.” The research also found that 76 per cent of non-technical or non-digital workers would consider a career in tech or the digital sector, which indicates a willingness to re-skill.

The UK government is also plugging the digital skills gap by introducing new training measures. Five international tech hubs in emerging markets are being created to develop partnerships between local tech firms and UK companies, encouraging collaboration on skills, innovation, technology and research. The government’s digital strategy, introduced earlier this year, promises four million free digital skills training opportunities. The government has partnered with a number of leading companies such as Lloyds, Barclays and Google pledging to provide face-to-face training for individuals, charities, small and medium businesses and children.

But experts warn that, despite their increasing availability, public and private incentives may not be enough to plug the gap without a great deal more funding, and current training and learning systems will not match needs within a decade. There are also people who are incapable of or simply uninterested in self-directed learning.

In fact, alarm bells are ringing about the disappointing number of children, particularly girls, signing up to do the UK’s new computer science GCSE. A couple of years ago, in response to concerns about the changing technology landscape, the government made it mandatory for children aged between five and 16 to learn computational thinking as part of the computing curriculum, but many say this has not been as effective as hoped, pointing to an unimaginative syllabus and poorly equipped staff.

Consensus is growing that what the IT sector needs is nothing less than a make-over, a marketing campaign portraying a career in tech as something that is fun and inclusive, emphasising soft skills — creativity, analytical thinking, problem-solving, multitasking, verbal and written communications — to attract people who can then be trained in the technical aspects of the role. Especially for girls, who often view tech as a male-dominated and uninteresting sector, showcasing those who have taken an alternative route into technology would provide encouragement and inspiration.

As a young, black, female working in a male-dominated, highly-lucrative and rapidly-changing sector, Esther can anticipate yet more career changes. She’d make an ideal STEAM ambassador; a super role model.


Robots need not apply: a future-proof guide to jobs in the automation era

By Adriana Hamacher

I’ll kid you not, it won’t be easy. Companies looking for fail-safe strategies for the coming years will need to create specialised work environments for jobs that don’t yet exist, in sectors that have not yet been created. A recent WEF study found that 60 per cent of the jobs that will be most in demand over the next decade have not even been invented yet. What’s more, according to some analysts, a large portion of core academic curriculum content is already out of date by the time students graduate. Skills instability is on the up in all industries, with many current roles hard to recruit for.

desktop robot

Image by Matthew Hurst/Flickr

It’s not helpful that the experts disagree on whether automation will have a devastating effect on human employment or not. What differs from previous waves of upheaval, many say, is that the pace of change is greater and its effect is broader; the automation era demands that displaced workers in routine, unskilled jobs graduate to non-routine, skilled jobs to stay ahead, instead of moving to similar-level jobs in other industries as before. Early indications suggest the employment market isn’t evolving fast enough to keep up with this change.

Others argue that automation increases productivity which leads to economic growth and new jobs. In the developed world, 3-D printing will drive companies to bring their manufacturing back to their home countries; self-driving vehicles will give people more time to consume goods and services, boosting demand. Humans and machines will also increasingly partner to great effect. To highlight an example: autopilot didn’t put pilots out of a job; instead it foreshadowed collaboration between human and machine on complex tasks. The increasing popularity of collaborative robots –cobots– is further evidence of this trend.

Capitalising on our humanity

It’s no surprise that, in a technological age, most new jobs will be in specialised areas: computing, mathematics, architecture and engineering. Technology also has a habit of obsoleting itself at an increasingly accelerated pace, so we need more people to create new tech, maintain it and help others use it. We need expertise in design, testing, implementing and refining smart automated systems. AI firms are said to be busy hiring poets to write dialogue for chatbots.

Some jobs are always likely to be better done by humans, especially those involving empathy or social interaction. Research by Deloitte, in the UK, finds that the future workforce will benefit from a “balance of technical skills and more general purpose skills such as problem solving skills, creativity, social skills, and emotional intelligence.” Jobs that fall into these categories – nurses, trainers, entertainers and more – will probably fare well in a more automated world. That’s not to say that AI and robots won’t eventually be capable of performing these roles (in some cases better than humans), but the recent resurgence of artisans in cities worldwide shows that just because something can be automated, it doesn’t mean it will be.

Survival of the most adaptable

But the reality is that in order to keep up-to-date with the latest technological advances, people will need to consistently retrain. Thus the future of work will soon become “the survival of the most adaptable”, to quote Paul Mason, emerging technologies director for Innovate UK. Holding a job for life will rarely be an option.

AI will also require big changes in the way education is delivered, just as the Industrial Revolution demanded in the 19th century. Industrialisation simultaneously transformed both the need for education and offered a model for providing it, prompting the introduction of universal state schools on a factory model. AI could well do the same.

But surfing the automation wave will likely demand more of humanity: a shakeup of our core beliefs surrounding work and its value may be long overdue. “In our fast-changing world where innovation and adaptation are more and more the critical success factors, another increasingly important measure of the effectiveness of an organisation is not just how productive it is but how intelligent it is”, writes Thomas Malone, director of the MIT Center for Collective Intelligence.
“Intelligent organisations will be better able to adapt rapidly to changes in their environment, better able to innovatively take advantage of new possibilities, better able to be flexible and sense and respond to the world and not just do more efficiently what worked yesterday.”

HR’s shopping list for the automation era

This is a snapshot of what’s to come in the next five years, rather than the long-term (for that, see http://www.futuristspeaker.com/business-trends/55-jobs-of-the-future/):

  1. Machine Learning Specialist: Developing algorithms that can “learn” from or adapt to data and make predictions is a job likely to stay hot for some time. Lots of maths, preferably a PhD, needed.
  2. Interface Designer: Increasingly crucial as systems get smarter, robots become part of our lives and interfaces become more natural, incorporating gesture and speech.
  3. Nano-degree Developer: Traditional apprenticeships typically involve five to seven years of training, which doesn’t make sense if the skills you need are constantly changing. A nano-degree (perhaps in data science or website programming) can be completed in a few months, alongside a job.
  4. Industrial & Organisational Psychologist: the U.S. Bureau of Labor Statistics, says this sector, concerned with the study of human behaviour in organisations and the work place, is expected to grow by 53 per cent from 2010 to 2020. In fact, psychologists will be increasingly necessary to help us adapt to automation in every sphere, from trusting a self-driving car to counselling remote military operators.
  5. Neo-generalist: less about “doing all sorts of work”, and more about “connecting everything”. A manager, strategist or system designer.

 


Meet your new co-worker: a ‘cobot’

By Adriana Hamacher

Screeching, scary headlines along the lines of “Robots are taking our jobs!” mask a real trend that is emerging: collaborative robots, AKA cobots, which augment, rather than remove, human labour. Compact and highly-flexible, cobots are designed to work safely alongside humans, as opposed to behind a barrier or inside a cage. They are among the fastest growing segments in the robotics market and global sales are expected to reach $3.3 billion in just five years, according to one estimate. So we’ll be seeing a lot more of them very soon.

So what are the implications for the humans who have to learn how to work with these cobots? Continue reading


11 ways to empower the self-directed learner

By John Helmer

Graphic ident for research report Me Time: Empowering the Self-Directed Learner Recently our Head of Transformation, Rachel Cook, contributed a piece to this blog about how changes in the pattern of employment are shaking up the employer/employee relationship. One of the most interesting aspects of Rachel’s work for us was how these changes ­– momentous enough to get analysts talking in terms of a ‘fourth industrial revolution’ – are highlighting the phenomenon of the self-directed learner.

Aware that this is a source of much debate for the learning and development clients we work with, and in many cases a pain point, we wanted to know more.

We reached out to our research partners, Towards Maturity, for help in investigating this phenomenon, and commissioned a report written by Peter Williams, editor of e.learning age entitled Me Time: Empowering the Self-Directed Learner that you can download for free. The findings were fascinating. Continue reading


The challenge of mobile learning content

By John Helmer

Illustration of happy learners using mobile learningResearch from Towards Maturity shows that two out of three learners find accessing mobile learning essential or very useful, and 57% like to be able to access learning on the go.

Meanwhile in the US, where 50% of the US workforce holds a job that is compatible with at least partial telework and approximately 20-25% of the workforce teleworks at some frequency (according to GlobalWorkplaceAnalytics.com) learning solutions that support mobile learning are increasingly being seen as essential.

67% of organisations in the Towards Maturity sample now offer mobile learning in some form, but many struggle with getting the right content in place for this channel.

The options can seem bewildering. Should you build or buy for a start?

Then, if you’ve decided to buy off the shelf e-learning content, where can you find mobile content that really works on mobile devices?

On the other hand, if you’ve decided to build your own, what are the important design principles you should follow – and which is the best content authoring tool to use?

Because we know these are troublesome issues for many of our regular readers, we recently put together a webinar that brought together the key experts within Lumesse Learning on mobile content. Between them they span the key fields of knowledge about

  • OTS content for mobile
  • Learning design for mobile
  • Technology for mobile authoring

To watch a recording of this lively roundtable session  – click the link below.

Webinar: Mobile learning content. How to get it, how to build it ­– and how to make it fabulous


Is L&D ready for learning analytics?

By John Helmer

Graphic to illustrate Learning Analytics theme with graphs, etc. in a thought bubbleLearning professionals are reaching out beyond their traditional data sources and methodologies to embrace a new world of learning analytics. However, innovation is sporadic and held back in many organisations by a historical culture of not evaluating effectively (if at all).

This was just one of a number of fascinating insights that arose from our latest Think Tank dinner.

We assembled an invited group of L&D leaders to discuss these issues in a three-part discussion held under Chatham House rules. Contributing to the debate were delegates from the worlds of finance, logistics, FMCG, mining, pharmaceuticals, professional services and commodities trading.

Download a highlights report of the discussion.

But for those who want a deep dive into the first part of this fascinating discussion, read on, as we address the following question:

Part 1: What examples can we see of organisations using learning analytics and insights in new ways?

Continue reading


Automating CV screening results in 15% more women hired

By Harriet Croxton

Business man and woman at a window togetherA professional services organisation that implemented an automated CV screening process to handle the 250,000 job applications they received every year were worried that the automation might undermine their efforts to achieve a healthy gender balance. In fact, the opposite happened. The number of women who successfully passed through the automated process increased by 15% compared to the manual process.

This and other revelations were reported in a recent article from McKinsey, People analytics reveals three things HR may be getting wrong.

Advances in data analysis are helping organisations identify, onboard and reward the best talent, however when analysing this data the results observed are often counter to expectations.

Continue reading


How adaptive pathways make digital learning more elastic

By Nicholas Murphy

Close-up elastic band to illustrate making digital learning more elasticOne of the key challenges for digital learning design is creating solutions that meet the needs of all learners. Risk often drives decision-making when it comes to content: if we don’t know how much people already know, we create content that tries to teach everybody everything, regardless of their level of expertise. This is particularly true for any training that is driven by a regulatory or compliance motivation.

Challenging this approach has become a key driver for us at Lumesse in moving, with our clients, towards a more personalised, learner-centric dynamic.

Typically, courses teach and then test: it’s the foundation of most e-learning. But that model is founded on an assumption that the audience will have a low baseline of understanding. The reality, however, is that most learner populations will already know quite a bit about a given topic (even if some of that ‘knowledge’ comes from hearsay, myth or legend!).

One sure way of making the learner switch off is to make them sit through a lot of material they know already. So reversing the teach-test structure and running an initial diagnostic has been a principle in learning for some time. Test me first, teach me what I don’t know, and then test me again.

However, both of these approaches are limited. They work for content you need to remember, but much less well for behavioural competency, where we need to feed the subconscious to drive behavioural changes.

Increasingly, we are beginning to use adaptive learning paths to increase the effectiveness of digital learning. Here’s how it works.

Continue reading


Learning analytics in the age of big data

By John Helmer

Graphic to illustrate Learning Analytics theme with graphs, etc. in a thought bubble What we can’t measure, we can’t manage, according to the business cliché. And suddenly, it seems we are able to measure a lot more than we could before: there has been an explosion in new data sources. So is this making businesses more manageable? It’s certainly having effects – in all parts of the enterprise, including learning. Learning analytics is becoming increasingly important for L&D. But do they know how to use the new learning analytics effectively?

Our latest Think Tank takes this as a subject, with a specific focus on how we can deploy actionable insights and analytics from data to fine-tune learning programmes.

As an introduction to the blog posts and reports that will come out of the Think Tank in the weeks and months to come, let’s take a look at this new data hoard, and the kinds of structured and unstructured data that are available to learning departments.

Highlights Report from the Think Tank is now available here 

Continue reading


Three mobile trends that are changing learner expectations

By Duncan Barrett

LG8_ident_300pxLast year we passed an important milestone. In 2015, more people accessed the internet through mobile devices than through desktop, laptop and other connected services combined. These are US figures for mobile trends, but the global picture is not much different – and what this tells us is that we are now beyond asking whether mobile is important. We know it’s important.

The more critical question for organisations is how to deal with this new situation – how they optimise the products and services they offer to meet the new expectations this rapid and enthusiastic adoption of mobile technology has produced among consumers.

And for ‘consumers’, read ‘learners’. Remember, learners are consumers too (they don’t automatically morph into some different type of lifeform when they slip on a corporate lanyard). Learners whose expectations are changing.

The expectation is they will be able to do everything they want to do online irrespective of their location, or the device they are using. And when it comes to content engagement, the giants of technology such as Facebook and Google have shaped expectations that make them more intolerant than ever of a poor user experience.

The result is, we are seeing behavioural and technological shifts that will have an increasing impact, going forward, on how and when an employee’s learning and development takes place.

So, to get more specific, what are the three key mobile trends that are shaping the way learners expect to interact with content?

Continue reading