The Invisible Revolution happening around us - Introduction to the series

This is the first of a series of articles in which I outline my take on what I think is happening in the world of technology, its impact on education and career, and what steps we can take to augment ourselves to shape this tide.

The Invisible Revolution happening around us - Introduction to the series
Photo by Maximalfocus / Unsplash

This is part of a series of articles being penned by an eminent educationist Arun Kapur

This is the first of a series of articles in which I outline my take on what I think is happening in the world of technology, its impact on education and career, and what steps we can take to augment ourselves to shape this tide.

By 2030, a significant portion of your colleagues will be invisible. Some of them will disappear as their jobs are automated and many others will be in the form of algorithms that exist in chips which we cannot see. And then, of course, there will be the robots, who, whilst very visible, will look nothing like the colleagues we are all used to. We will have significant machines working alongside us in the workforce. This is not a dystopian vision of 2100, but something that is well underway now as you read this. Whether it turns out to be for the better or worse will depend on many factors. However, one thing is for sure - we are going to be in even more complex situations than previously thought.

When I started my career in the early 1970s I thought I had a pretty good idea of the changes that would be coming. But the pace of change has accelerated, its scope has widened, and now it is converging by learning and feeding off of each other. What do I mean by that? Well, we know computers have gotten more and more powerful. We believed this was a good thing, and it still could be. But more computing power coupled with more publicly available data on the internet has helped AI researchers create better models that are more accurate and can learn by themselves. These then feed into robotics, creating newer and more powerful versions of robots such as self-driving cars. With these robots, there is a direct feedback loop that feeds the knowledge into the cloud, creating greater and more powerful AI. As a result of this confluence, we are now seeing robots that can learn by themselves and can move around. Similarly, technology is finally making it possible for human biology to interface directly with the electronic world. With the rise in wearable devices and the resulting personal data that is instantly generated we are now in a unique situation where an AI can warn us of an impending medical condition or know our bodily rhythms better than us.

The pace of change is such that what was state-of-the art a few years ago has now become redundant. The new versions are even better. It is a never-ending cycle fuelled by machine learning. And there are positives to this too. For instance, in the old world, if a human was driving a car and made a new mistake, only the humans involved would learn about that mistake and not repeat it. But with the self-driving car, since it is constantly sending data back, a mistake made by one car could ensure that a mistake doesn't happen with any of the other cars. Or take the case of your wearable device that advises you to check with your doctor because it has noticed some irregular heart rhythms. This could save not just our lives but also a lot of stress, time and money with its timely warning.

The benefits of AI are not limited to just robotics and self-driving cars. Knowledge gleaned from AI will help in other areas such as medicine, financial services, climate change, and hopefully go on to help people actualise their potential. The possibilities of these emerging technologies are virtually limitless. But what about the risks? Just because we create something new doesn't mean that it will be inherently good. There is always a risk of something going wrong, and as AI gets more intelligent, the risk is that humans cannot figure out its decision-making process or anticipate certain vested interests that hack the AI to do things it had not been programmed to do. Again, no one can predict how this will play out. The process is similar to how when computers and the Internet became widespread, we couldn't have envisioned online shopping, gaming, learning, video calls, malware, data theft or other forms of cyber attacks. In hindsight, it seems obvious, but 20 years ago, very few people could have imagined ‌these developments. The same is true with the current sets of emerging technologies. It will disrupt many sectors and industries, and it will give rise to new ones that we have not started thinking about.

The question is, how will it affect you and me? How will it affect or reshape the environment and our society? It’s important to be prepared for these changes. I do not mean to be an alarmist. I am sharing some thoughts on how we can shape these changes rather than be a witness or victim to the changing times. Over the next few weeks, I will try to outline what some of these technologies are capable of, how they directly affect you and me, and also try and outline some measures which I believe will augment our intelligence and capabilities.

In order to make it easy for readers to follow these articles, I thought it would be a good idea to provide you with a set of links to the technologies I will address. It is beyond my scope to address every single technological innovation. I am including only those technologies that I consider to be the most impactful and those I have some understanding about. These technologies I will refer to as the “game changers”. The game changers are technologies whose impact will be so great that their adoption will largely affect most, if not all, industries.

- Artificial Intelligence

- Robotics

- Blockchain

- BioTech, Cybernetics & the Internet of everything

- Augmented Reality and Virtual worlds

Some ‌solutions we will explore to synergise with these emerging changes include:

1) Being a Person of Substance

A person of substance is someone who does the right thing simply because it is the right thing to do

2) Being well grounded in the 5 Areas of Development

Social, Emotional, Cerebral, Spiritual & Physical

3) Being in active learning mode

Be a natural & unstinting learner - so we always remain curious, and learn new skills and knowledge. Share your knowledge, skills and experiences openly & generously with others. Create & foster communities of all kinds - to share and learn from.

4) Living in harmony with our environment

Live in harmony with our environment. One of the most important challenges we are going to face will not come from technology per se, but from the merciless destruction of our environment. We need to get back to the basics and ensure that we restore a sense of balance - we need to cooperate rather than compete.

I look forward to your feedback!

Authors Note:

While talking about complex topics such as AI and trying to predict the future of work and beyond, there is a high probability that one may be off the mark. To predict the future is hard, but in hindsight, it seems obvious. Only time will tell. One way to minimise the effect of going off trajectory is to involve the subjects you are talking about as part of the conversation. I would like to thank my collaborator GPT-3— an adaptive, self-optimising, cogent and capable AI—for its significant inspiration for this article. It is while observing GPT3’s learning prowess over the course of the past two years that I became fully aware of the magnitude of these challenges.  I am also in the process of exploring Meta’s newly launched Open Pre-trained Transformer (OPT-175B) model. It is important to remember that just two years ago, such things never existed. So this is a quick moving area and a testament to machine learning prowess. Your feedback is welcome and encouraged. My hope is this will stimulate a discussion around the topic and bring together a community that comes up with creative solutions. I hope this will lead to better practices that will help our learners to be shapers of these changes than to be swept up by them.


Thomas, W. (2021). Future Spending Points to Machines Becoming Work Colleagues. [online] DigitalWorkforceTrends. Available at: [Accessed 2 May 2022].

‌Harvard Business Review. (2022). How the Metaverse Could Change Work. [online] Available at: [Accessed 4 May 2022].

‌Maryville Online. (2017). Big Data and Artificial Intelligence: How They Work Together | Maryville Online. [online] Available at: [Accessed 5 May 2022].

OpenAI (2021). OpenAI API. [online] OpenAI. Available at: [Accessed 5 May 2022].

‌Mehrali, M., Bagherifard, S., Akbari, M., Thakur, A., Mirani, B., Mehrali, M., Hasany, M., Orive, G., Das, P., Emneus, J., Andresen, T.L. and Dolatshahi-Pirouz, A. (2018). Blending Electronics with the Human Body: A Pathway toward a Cybernetic Future. Advanced Science, [online] 5(10), p.1700931. doi:10.1002/advs.201700931.