Online education has been on the rise. There are many advantages of eLearning. Often cited benefits are cost-saving, access to high-quality learning materials, and learning at your own pace. There are also disadvantages too. Like many other technology-led transformations, online education has been facing several drawbacks. Some of them are technological. Notable ones are limited access to state-of-the-art computers, smartphones, access to the internet, and the cost of mobile data packs. Other limitations are surfacing in the form of learning management systems and online proctoring. Of course, increasing screen time and smartphone addiction are also demerits. Let’s assume that all those disadvantages are addressed. Of course, they will be resolved. Does it mean that we should migrate to online education? In addition to commonly cited drawbacks, do the disadvantages of eLearning in the robot era suffer from the risk of ultimately making online classes useless?
To shed light on these two vital questions, we should look beyond commonly cited advantages and disadvantages of online classes. We should go back to the basics of education. One of the purposes of education and training is to prepare the workforce for the future job market. Despite the increasing investment, there has been a growing concern about the skill gap. What kind of capacities are needed for human beings to qualify for jobs that should be looked upon? Mainly, how are automation and robots changing the demand for knowledge and skill is an important area to investigate. By the way, robots are manifesting in the form of both software and cyber-physical systems. However, as opposed to physical robots working in the factory, robots in software form seem to be more capable to the future of work. By the way, the robot is a synonym for automation.
The comparative advantage of humans and machines to qualify for jobs
Profit-making firms in the competitive market are under constant pressure to offer higher quality products at lower costs. Furthermore, due to increasing compliance requirements for addressing safety and environmental issues, they also need to keep reducing emission, and wastage. In the UN’s sustainable development goals, several targets have been set in this regard. For example, reducing road accidents by half by 2030 is one of the 169 targets to meet 17 goals. One way to address the challenge of producing more economic value by consuming fewer resources and causing less harm to the environment is increasing precision, reducing wastage, and making fewer errors or causing less contamination.
Invariably, increasing precision leads to higher quality and less wastage. Invariably, human presence is the source of errors and contamination. For example, the major cause of road accidents has been due to drivers’ mistakes. On the other hand, human presence and touch are significant sources of contamination, particularly in food processing and handling, and pharmaceutical manufacturing. Hence, there has been a relentless journey of reducing the role of humans in production. Consequentially, the role of machines in production has been increasing. If machines can do the job better than humans at less cost, there is no reason to give those jobs to humans. Hence, the increasing role of machines in productive activities also changes the eligibility requirement of humans for work. The purpose of education and training is to build those capacities among learners to qualify them for future jobs.
Task execution capacity—knowledge, skill, and ability need
Every job or occupation is a collection of tasks. To execute each of these tasks, whether man or machine needs to have specific capacities. Human beings earn those capacities through three different means. The first one belongs to innate abilities. By born, a healthy human being inherits 52 innate abilities in the category of cognitive, sensory, physical, and psychomotor. Moreover, creativity for generating ideas belongs to innate abilities as well. Human beings earn additional capabilities by going through many years of education and training.
Through education and training, we earn Codified Knowledge and skill. Campus-based education also sharpens our innate abilities, and build certain capabilities like teamwork and motivation in tacit form. We also gather increasing task execution capacities through experience, often in tacit form, though. Therefore, human beings earn eligibility for jobs through three different means, and also in three different ways. As mentioned, along with the development of codified knowledge and skill, campus-based education also sharpens innate abilities, and develop specific tacit capacities.
Robots and automation for taking over codified knowledge and skill–disadvantages of eLearning in the robot era include the focus on codified capacity
We develop machines, automation, and robots for addressing our conflicting agenda of producing more with less. The purpose is to make them eligible to take over tasks or jobs from human beings. The robot making journey begins with inanimate material, which is devoid of knowledge, skill, and innate abilities. Designers develop necessary capacities in machines. We add computation and data storage capacities in robots. Subsequently, they qualify to store data and codified knowledge. We also develop and add software to make robots eligible to execute mathematical formulas to empower machines to have codified skills. It has been found that it’s quite easy to develop capacities in robots and other autonomous machines to automate the storage of data, knowledge, and codified skill.
More importantly, we are developing robots’ capacities in software form. As the cost of copying software is zero, we replicate such capability instantly at no additional cost. Hence, the role of education in developing codified capability among students for making them eligible for jobs has been falling. In fact, due to it, there has already been net job loss in the middle layers in the USA, Europe, and other advanced countries. One of the major disadvantages of online classes is high, perhaps sole, the focus is on developing codified capability. This reality has been at the core of the disadvantages of eLearning in the robot era.
Robots are facing barriers to take over innate, and also tacit abilities
Unlike codified knowledge and skill, scientists and engineers find it extremely difficult to develop automation and robots with capacities that human beings have in tacit and innate forms. Of course, the progression and addition of sensors are making it easier to imitate cognitive capability. Nevertheless, it’s highly primitive in nature. There have also been some signs of progress to transfer tacit capacities into codified knowledge and skill. As a result, robots are taking over the tacit capabilities of experience people gradually. Particularly, software and network-centric process automation and knowledge management is translating individuals’ on-job learning as a set of policies, procedures, and standards. Moreover, job division is leading to separating high-level tasks into subtasks, predominantly requiring codified, tacit, and innate abilities. Subsequently, such job division is leading to automating the codified sub-task first, followed by the automation of Tacit capability.
Hence, increasing task execution capacity earned through experience is losing the market value. Consequentially,, ‘juniorization’ as a new phenomenon is surfacing in the corporate world. Due to the automation of tacit capacity, earned through experience, seniors are losing jobs to juniors. Therefore, knowledge workers operating in the middle layer are losing jobs to automation, and seniors are losing jobs to juniors.
Innate abilities pose the hardest barrier to Robots, and also to online education
In contrary to middle layer, jobs at the bottom layer demand high-level innate capabilities. These jobs require very little codified knowledge and skills. Most of the manufacturing, driving, and service jobs belong to this category. Even someone having no formal education qualifies for this type of job. For example, millions of workers performing apparel or shoemaking jobs in developing countries belong to this category. Due to the need for high innate abilities, robot makers find it extremely difficult to automate these jobs. Often, they are getting lost or abandoning such attempts upon spending huge amounts of money, effort, and time.
For example, upon running the R&D program for 32 years, Honda engineers figured it out extremely difficult, perhaps impossible, to develop human-like innate abilities in Humanoid robot ASIMO to qualify it for elderly care jobs. Hence, the management stopped further R&D on ASIMO in 2018 after spending $500 million over 32 years. Similarly, after spending more than $80 billion, researchers face insurmountable barriers in making autonomous vehicles eligible to drive by themselves in a busy city without the need for human drivers.
Jobs for humans and robots
A job is a collection of tasks. Some of the tasks are highly codified knowledge and skill intensive. Others require a high intensity of innate abilities. Creativity, imagination, and seeing clarity amid uncertainty often belong to innate abilities. Of course, knowledge and data help, but they are not sufficient to generate ideas and make rational decisions in the midst of uncertainty. As explained, robots and automation are increasingly taking over jobs with a very high intensity of codified knowledge and skill. On the other hand, jobs requiring a high level of innate abilities are for human beings. Most of the service, Innovation, and high-end management jobs belong to this category.
Therefore, education and training should focus on changing the eligibility requirement for human beings to qualify for jobs. On the one hand, they need to pursue innovation. For that reason, they need to know the existing body of knowledge and skill. That body of knowledge and skill should be fed into the process of creativity, imagination, and rational decision making. Therefore, along with the delivery of codified knowledge and skill, we should also sharpen relevant innate abilities.
On the other hand, to make learners to qualify for service jobs like healthcare service delivery, along with codified knowledge and skill, we should also sharpen their innate abilities. In the absence of innate abilities, they cannot make good use of codified knowledge and skill. Moreover, robots, both in physical and software forms, are taking over the codified capability part of jobs. Hence, the focus of online education in developing codified capability is among the major disadvantages of eLearning in the Robot Era.
Focus on delivery of codified knowledge and skill make online education not so useful in the robot era
It does not require much debate to make a point that online education is mostly delivering codified knowledge and skill. As explained, it’s quite easy for machine designers to automate the possession and execution of this capability. Without sharpening innate abilities, learners will keep losing the market value for having this codified capability. Even we address all the disadvantages of online education like knowledge retention or lack of attention span, online education cannot prepare graduates for the future job market. It is the most significant demerit or drawback of online lectures. Lack of the ability of online learning in sharpening innate abilities is among the major disadvantages of eLearning in the robot era.
Hence, instead of increasingly relying on online education, we should go back to basics to prepare the workforce for the future robot era. Therefore, in the debate about the advantages and disadvantages of online or distance learning, we should take this vital point very seriously. Otherwise, through eLearning, we run the risk of failing to develop the future workforce fit for the purpose. Such reality also raises the question: are we misinterpreting knowledge and skill requirements for facing the industrial revolution?
