Disruptions are not new — whether technology or philosophical or political or others. These waves of transformations affect society in different ways but the impact is similar — it forces people to change the way they live and think and what they believe in. Often, these transformations come from unexpected sources of change and take decades if not hundreds of years to take place. In recent times, these transformations have quickened and taken a much shorter period of time to effect the changes in society. In other words, the pace of change has accelerated, resulting in ‘change being the norm’. For those who are able to manage the changes, resilience and resourcefulness develop. For the others, they shift into states of learned helplessness and disempowerment.
There have been many timelines by futurists (e.g. Russell Cook, 2017) for the changes that have taken place since the industrial revolution. Many of these changes are technological. There are other revolutions linked to political, labour or financial disruptions. Regardless of the cause, each disruption throws up new challenges and replaces some of the incumbents with new blood. This creates some churn, and along with that, energy and vibrancy, which can be useful to take our societies forward.
The next disruption, however, is different. It involves a myriad of disruptions combined and cuts across all sectors (not just agriculture or finance). It is both a technological, financial and labour disruption. It alarmingly duplicates many of the physical and cognitive functions that humans perform.
Just like how the industrial revolution released many families from performing agricultural, manual labour work into industrial ‘skilled’ work, the technology in the A2(Automation and Artificial Intelligence) revolution will replace many people performing jobs which are ‘low level’. What are the capabilities involved in the A2 revolution?
It is important to note that there are actually 2 waves of technological changes, closely overlapping:
1) Automation wave — physical movements and skills involving:
o intricate movements, facilitated by 3D printing and 5G transmission making these robots extremely fast and accurate e.g. manufacturing robots.
o remote operations e.g. robots working in atypical environments e.g. navigating in nuclear reactors and performing bomb disposal functions with humans manipulating them at a distance
2) AI wave — integrated cognitive, affective and social capabilities such as:
o visual recognition or semantic analyses e.g. categorising or sorting objects based on information — such as Amazon workers sorting parcels based on type of products and addresses or radiographers identifying tumours on scans etc
o application of cognitive understanding to solve problems e.g. collecting research / literature on past legal cases
o machine learning to correct their mistakes (without human intervention), all driven by the acceptance levels of the outcomes
The current labour disruption builds on the industrial revolution in the late 1700s, which focused on manual labour augmentation and incremental automation since the 1960s. Car factories are filled with robots as hardware coupled with scripted programming allows for routine physical jobs to be automated. See figure below for the human capabilities categorised into the various domains.
At the workforce skill levels, AI and automation have taken on much higher levels of capabilities beyond the industrial revolution.
See areas in red to note the automation levels during the industrial revolution, areas in purple for automation and green for AI respectively in our current A2 revolution.
Here, we can see how the industrial revolution in the 1800s impacted primarily basic psychomotor skills (with the invention of machines to replace human and animal labour), the automation wave in the 1970s with calculators and personal computers facilitated computations and communication along with machine interpretations of human emotions and conversations with humans. Again, this wave augmented human intelligence and capability since most humans (with basic education) would be operating at the intermediate or complex levels of cognitive capability. The A2 revolution beginning in 2020s will encroach on the capabilities that the majority of humans are operating in (click here for article by Choy, 2019). This is the biggest difference thus far compared with the rest of the revolutions. The industrial revolution displaced many of the agricultural and manual workers but it also seeded the current educational system which moved many people from purely manual work into cognitive (‘office’) work. It was the new renaissance for humankind as we discover new technologies and allow many of us to push boundaries and realise our potential. Essentially, schools moved many people from performing manual labour to higher order skills. Going forward, in view of this upcoming revolution, schools will need to move people again, this time into expertise. Being just competent in intermediate or basic skills will not be sufficient. It will be the equivalent of learning how plough a field using a hoe when there are machines to plough the fields a hundred times faster and more effectively.
By drawing up the diagram above, I have made the following observations and assumptions:
a) the progression of AI is relentless and is likely to cover all complex domains by 2050
b) not all humans can achieve the complex levels of processing across all domains
c) from single domain (psychomotor), the progressive technological revolutions are crossing domains and integrating skills resulting in multiple sensory inputs that give a more ‘intelligent’ response i.e. intelligent machines
d) only meta segments remain out of reach of intelligent machines in the next few decades but even with training, not all humans will reach this level of processing which then leads us to the question of what humans who are superseded in capability by intelligent machines will need to do.
Assuming that the above observations and assumptions are correct, it will imply that the current revolution is not just technological but strikes at human resource and capability. Hence, unlike past financial, information or communication disruptions, this disruption will directly replace human labour and work.
What are the implications if all these are or will become true?
a) AI will basically take over roles that humans perform at the basic and intermediate levels including organising work that relies on visual recognition or text analysis, for example, sorting parcels at warehouses and scheduling appointments based on textual requests. Over the next 5 to 10 years, these job roles will diminish and disappear.
b) AI will have difficulties encroaching into domains that require decision-making based on values, beliefs and human ethics primarily due to the boundaries humans would draw up to prevent this, for example, in legal sentencing, pre-school education and medical decisions that affect a person’s chances of living.
c) AI will also find it difficult to get into expertise skillsets where deep innovation and creativity are required. Expertise also implies the capability to pre-empt errors and check assumptions. Most experts carry with them a high level of ownership and passion of the field they are in, driving change as well ensuring everyone and everything else plays by the rules as denoted by the practice.
d) To ensure that humans will have a pipeline of experts for every field of work, a different type of pedagogy will be required to drive development of experts (e.g. error-based learning). It will have to fast-track the development of complex skills and meta-cognition. The development of underpinning basic and intermediate skills will still be important, for a much shorter period of time (compared to current 5 to 10 years for internship and subsequent ‘moving up the ranks’). A protected space for these would-be experts to acquire these basic and intermediate skills is important. Schools to teach these basic and intermediate skills will need to be created for humans to learn and make mistakes even though AI can perform them at a fraction of the time and cost.
e) The entire educational system to build basic and intermediate competencies will have to be re-examined as it is premised on the 1800s industrial revolution where machines take on the heavy lifting while humans can focus on cognitive tasks. This has been true for several centuries now but it will not be true in a decade or so. Given that it does take about two decades to train a 3-year-old child to be work-ready, it is critical for educators to re-examine where today’s 3-year-old will end up if they remain in today’s educational system. Will they be out-competed by intelligent machines? Is the educational system going to prepare them to lose before they even started?
Update: What about the Covid-19 Virus?
With the pandemic hitting the global economy and specific industries (e.g. retail, tourism, transportation) in unprecedented ways and scale, the challenge is to decipher what remains as long-term impact and what will dissipate after a couple of months. It has also accelerated the digital transformation of enterprises and individuals at a pace unimaginable in the past. This has huge implications and impact on how we work and learn in the future.
In addition, the pandemic has exposed the underlying weaknesses of ‘people skills’ (under the Social Domain) which require a fair amount of interpersonal interaction, preferably not online but in actual physical presence. As people move their interactions and communications online, the preconceived ‘people or social skills’ which were supposed to be the mainstay of future human work (as compared to roles performed by machines) may potentially be muted going forward. There is only so much people skills that you can display in an online synchronous greeting and bonding, not to mention that a lot of these digital relationship bonding can be automated with well-created avatars with embedded AI.
Being cognisant of the underlying technological advancements and pandemic-induced transformations, governments and educational communities will have to embrace more technology for communication, work and learning at an even faster pace. The timeline is possibly shortened with more people and enterprises taking to A2 technology in order to innovate and for some, to ensure their survival. Many of these safe distancing, work from home and tech-enabled communication measures will stay for the mid to long-term. With the mass migration of the workforce in Singapore and globally to technology use at both the enterprise and individual levels, there now opens up new possibilities for human workers to expedite their education and shift to new skills.
With that, workers need to increase their ‘Technology Quotient (TQ)’ which basically implies a greater sensitivity to leverage on technology for increased productivity. TQ, as I coin it, is the person’s ability to sense and assess technology in order to manage, affect and leverage on technology to achieve an intended goal. The higher the TQ a person has, the greater the likelihood that the person is aware of how technology is used and more importantly, how he or she can use technology to improve his or her situation or work performance, for that matter. This (TQ) measure is likely to tap on concepts relating to Intelligence Quotient and Emotional Quotient with Technology Quotient being a measure of a person’s propensity to technology use. This measure will have implications downstream in the ‘re-education’ of the workforce as global communities move into new tech-immersed spaces for work and learning.
I liken it to the ‘swim or sink’ analogy where those in the workforce who are willing and able will excel while those who are unwilling or unable to pick up technology will flounder and may be overwhelmed by this new technology flood.
What are the new avenues for development?
1. Introduce Mass Re-Education
2. Spot Geminal Technology as part of Skills and TQ Development
To underpin the mass re-education process, potential geminal technology leaders should be identified and leveraged on for quick wins. Workers tap on these technologies to create new products and services. As with geminal cells, when the technology mutates, workers can transfer their skills to the technology variant with minimal re-training. For example, staff are now utilising live communication tools such as Zoom, Google Meet and Webex to facilitate online meetings and discussions. The general skillsets to manage cameras, microphones, backgrounds and chats are likely to remain stable and even if a new live communication technology emerges, these general skillsets are likely to be applicable within the new technology.
3. Restructure Work with AI and Government Playing the Matchmaker’s Role
The rationale for the government to provide a platform for peer-to-peer direct exchange of skills models after current business models for Airbnb, Grab and Udemy among other recent technology unicorns. The potential for peer-to-peer sharing is huge and more importantly, it empowers individuals (whether from the supply or demand side) to upskill themselves in a rapid and responsive manner. Underpinning this platform will be the Artificial Intelligence to pull people together for this mass coaching exercise. With a government-based peer-to-peer learning platform, the workforce will have a trusted marketplace to purchase and experience learning and assessment opportunities.
4. Supplementing Institutions of Higher Learning (IHLs) with Expertise-Driven Delivery
To meet the rapidly evolving demand for skills, a more responsive delivery system whereby industry practitioners and experts are incentivised to work with novices and beginners for skill development may be needed. Often, the difficulty is often getting them emplaced in a creditable delivery system or motivating them to share their skills. Hence, adding the validation process for these coaches to instruct and their learners to be recognised as having acquired the new skills becomes critical and needs to be managed at the national level for the skills validation to be recognised industry-wide.
When facilitated by the nation-wide peer-to-peer platform, the expertise-driven delivery approach brings the supply directly to the learners to pick up critical skills from the industry practitioners, literally in their homes, through synchronous or ‘live’ webinar sessions.
At the same time, IHLs should maintain the supply of high-quality tertiary education for post K-12 so that our graduates can have a stable and safe learning environment to prepare for work. With a dynamic and responsive coaching / learning delivery system to cater to the working adults looking for bite-sized upgrades coupled with IHLs undergirding the foundational work skill development, our workforce will be well equipped to manage the challenges in the coming years.
5. New Learning and Assessment Delivery Approaches
In an ironic manner, the pandemic has done what many years of governmental push did not quite achieve, which was to get the majority of the workforce onto online platforms for work and learning. With online ‘live’ communications such as Zoom, Google Meet and Messenger Rooms becoming ubiquitous tools, the government may not want to waste the experience gained by the workforce. Providing a seamless transition for these workers to go onto ‘live’ learning lessons with a Learning Management System (LMS) that has a webinar function could be a useful next step. There are a few platforms (e.g. Sharelookapp) which already have this function and these tools will facilitate the shift into synchronous and asynchronous online learning and assessment for learners.
In addition, nudging learners to pick up online courses for rapid upskilling should be considered. Adopt gamification and scoring systems e.g. learners can obtain points that can be exchanged for simple rewards (similar to the FitBit concept) as a means to make learning fun and engaging, especially after the Covid-19 season. With messaging apps becoming more popular than social media apps, the government may need to wish to adopt a conversational learning delivery to push content out in bite sizes but over a long and sustained period, along the lines of using chatbots for learning with push notifications.
In conclusion, we don’t have much time left to prepare our workforce for the upcoming A2 revolution.
We need to start discussing what areas we can move our workforce into and how we can leverage on technologies for the good of Singapore, enterprises and individuals. The pandemic has provided a window of opportunity for the Singapore government to re-educate the workforce at scale in order to move them into high value industries, with a good proportion of them attaining expertise levels. We need to inculcate into our training so that our workforce’s TQ, besides IQ and EQ, is also high. Exposure to geminal technology is key. Encouraging a vibrant IT industry will also help increase the society’s TQ.
There are areas which we can channel positive human endeavours into such as social communities and innovations and to do these well, we will need paradigmatic shifts underpinned by political and social transformations. The pandemic has done part of the work. We will need to do our part in order to create a brave new world as we journey together from here. In other words, our future is now in our hands.
Dr. Michael Choy is Director of TechTree Pte Ltd, a company that seeks to transform learn and work spaces through technology for our future.