Wilson Wong, the Head of Insight & Futures at the CIPD, has responsibility for scanning for drivers shaping the future of work. The aim is to provide insights on business models, employment relationships, individual and societal concerns as well as what is valued by business, society and individuals. These insights, in turn, have implications for the various professions and of course human resource management (HRM).
Throughout the interview, a constant theme was technology and people. Wong was interested to explore how and where automation, robotics, machine learning and all manners of artificial intelligence would impact the future of work (see OECD 2016a, OECD 2016b). While these technologies bring the promise of productivity and economic growth, the broader impact on jobs, skills, wages and the nature and role of work itself cannot be ignored. Many parts of many jobs can be automated which poses the question, should they? Meanwhile platforms like LinkedIn, Uber and Etsy are changing the way we look for jobs, think about work and monetise our skills. Globally, millions of working age people are unemployed or underemployed, millions more in mature economies have seen incomes stagnate, with technological advancement often cited as the cause.
He argued that this process isn’t inevitable. What matters is how and where these technologies are perceived to add value to individuals, organisations and society generally. Technology doesn’t exist in a vacuum. “Technology emerges because there’s a need, they do [the task] better and cheaper than humans, or because it’s a solution to something we already do,” he explains. This means for it to be adapted, then the technology needs to add value or convenience. The adoption of technology depends on economics, and the choices people make.
Wong offers the example of a technology that has not been universally adopted - Genetically modified (GM) foods. GM foods, also known as genetically engineered foods or bioengineered foods, are foods produced from genetically modified organisms (GMOs) that have had their DNA changed using a variety of methods of genetic engineering. An example is golden rice, a GM food that also produces beta-carotene (a form of Vitamin A).
GMOs promise better nutrition, better yield and stronger pest resilience and yet, in Europe, there is considerable public resistance to ‘Frankenfood’. Any food imported into the European Union (EU) containing more than 0.9% from GMOs has to be labelled and several countries have banned the cultivation of any GM food although the EU has authorised a few food crops. Technology adoption here is clearly not straightforward.
Core competencies of the future
When asked about core competencies of the future, Wong highlights the need for flexibility. Traditionally, this means the willingness to be flexible about working time, types of employment relationships and location. In the future, workers will need to be adaptable and able to learn new skills quickly. Automation of functions will be a constant. As the technology evolves, the way humans and machines interact will also change. To stay employable, we will have to have complementary skills, requiring lifelong learning and skills development.
Understanding data and the data economy is crucial. Global corporations, governments and regulators are using algorithms to gain insights into human behaviour, recruitment and selection of talent and so on. As data systems merge, user services will be more convenient and customised. Even purchasing decisions today are influenced by data collected from a user’s history. Examples include loyalty cards, credit card companies and Amazon shopping history. “Amazon is as much a data miner and a market consumer insights company as it is an online marketplace,” he says.
For HR, data literacy will be a core competency. The first generation of HR data analysts will look at organisational metrics generated from HR Information Systems for supporting workforce decisions. The next wave will see most compliance requirements built into automated systems, complemented by real-time data on the ‘mood’ and productivity of the workforce via sensors and presented on a visual dashboard. This will impact many of the current HR roles.
“Data overload will be managed by algorithms so that humans can cope,” says Wong but that raises thorny philosophical questions about the extent to which A.I. should ‘nudge’ or frame the choices people make.
How will AI influence our future?
Wong explains that AI ‘lite’ will be focused on “supporting human decisions like visualising data and crunching large amounts of data to make investments and people decisions.” He shares that self-learning algorithms like Siri and Google already have these capabilitie pre-selecting the options available to you; this happens often without the user ever realising that there are more options they never considered because A.I. has already sifted these out.
At an everyday level, we can see how AI can be deployed to solve today’s social issues. Japan with its low immigration and ageing-- but rich-- population is embracing technology. Elder care is being redefined with diagnostic toilets or Paro, the therapeutic robotic seal.
Then there is strong AI, which means a machine-learning capability that will make decisions for humans mainly because they are able to analyse vast quantities of data, assess and analyse these and present the ‘best’ or ‘optimal’ options. "Imagine the day we rely on AI to diagnose our medical conditions instead of a mere mortal of a physician who is limited to the experiences of his own working life," shares Wong. Some even argue that human civilisation will be faced with technological singularity – the moment artificial intelligence exceeds the capability of the human brain. While this is only theoretical now, questions will need to be asked of the agenda and interests served by these invisible algorithms. There are broader societal questions on power and ethics and what might we place our trust in this future of strong AI, says Wong.
The implications of these technological advances will need to be considered because there won’t be clear right answers but potentially many wrong ones. To evaluate choices and decisions when dilemmas are unclear and yet unknown, Wong predicts that the role of the organisational ethicist will be of increasing importance.
Thoughts to Leave with the Reader
Who should own the data we generate? Recently, data provided by Fitbit was used as evidence in a murder trial. In addition, some companies also hand out Fitbits to their executives to monitor stress and health.
Could health profiling be a new form of discrimination?
What will happen to the middlemen? As blockchain becomes more mainstream, traditional tertiary education might become more modular. Rather than a four-year degree, students may get an education through bits, or one-class-at-a-time.
To learn more about the CIPD's thinking on the world of work, visit the knowledge hub at www.CIPD.Asia
If this article leaves you with some unanswered questions, we recommend this further reading:
The Age of Enlightenment, Financial Times
The future us: The talks of Session 11 of TED2017, TEDBlog. Particularly the comments that Tristan Harris makes.