AI Versus Me

‘Humans Need Not Apply’ - a video that recently went viral describes the future of intelligent machines and how they will disrupt human employability. (https://youtu.be/7Pq-S557XQU)

Famous inventor and futurist, Ray Kurzweil, predicts that exponential increase in computing power will see artificial intelligence (AI) surpassing human intelligence in 2045. He describes this as the ‘Technological Singularity’, because by then, Kurzweil postulates, self-improving machines will think, act and communicate so quickly that normal humans will not even comprehend what is going on, and this will forever change the course of human history.

The rate at which machines are replacing jobs that require physical labour has gone up significantly since the Industrial Revolution. Automation and mechanisation has led to replacement of humans with machines – number of people employed in agriculture has dropped drastically (while farm production has increased), robots now work on the assembly line, vending machines are replacing shopkeepers, ATMs have replaced bank tellers, you find self-check-in kiosks at airports, tele-marketing is becoming automated, at home we use vacuum cleaners and dishwashers instead of employing domestic help and so forth.

As machines replaced human labour, the complexion of the economy changed and knowledge in a domain became the key ingredient for employability in a services-dominated economy. An engineering, accountancy, or medical degree almost guaranteed lifelong employment.

Now intelligent machines are replacing jobs that were earlier available to humans because we had mental or cognitive abilities that the machines lacked. As this is happening, many 20^th century jobs are disappearing. You now buy an airline ticket from a website bypassing the travel agent (disintermediation), machine-based diagnostics is lowering the employment potential in fields like radiology (big-data analysis), banks are closing branches as banking moves online, with more and more banks toying with the idea that their future branches will only offer life stage and life style financial consultancy.

In this scenario, closer than we think, what we’ll see is ‘academic inflation’, not necessarily in the form of degrees but in the ability to have and exhibit deep knowledge and profound understanding in a domain. Only those who can do that will be ‘employable’.

Artificial Intelligence (AI) – the ability of machines to analyse, reason and learn is once again changing the complexion of the global economy. And, Artificial General Intelligence, that is a machine capable of performing any intellectual task a human being can, which may well become a reality in the next few decades, is going to change it even more dramatically.

What technology does is that it makes it possible for fewer humans to do the same amount of work. This leads to a widening income gap between those who can thrive in a technology driven world and those who can’t. A person develops an app that can do your taxes and that person becomes a millionaire while thousands of tax consultants become unemployed. Thus, technology can skew the income distribution – what economists call a ‘winner-takes-all-market’. You need to make sure you have the right skills so that you don't end up a tech- created have-not.

The more important question here is - will an intelligent machine replace you, or will it amplify you?

As in the past, the answer will depend on what skills and competencies you learn. Most experts agree that creativity, empathy, compassion, leadership, diplomacy, adaptability, focus, emotional maturity, mentoring, nurturing, self-directed learning, deep thinking, ability to solve complex problems, invention and entrepreneurship are some skills and competencies that will be much sought after in the age of intelligent machines. In addition, the ability to make the most of the intelligent machines themselves will be essential to enhance both the quality and scale of what you do.

For example, highly competent artisans, writers, musicians, life coaches, personal trainers and nurses will have a job even in the age of intelligent machines (there will be intense competition, and hence the high competence as an imperative).  However, to enhance the quality and to scale their businesses, these professionals will need to know how to best deploy intelligent machines in their vocation.

And, those who can imagine new products, new services and new industries, then have the ability to commercialise their idea will definitely flourish in the fast approaching future. Think about it - before Airbnb and Facebook, did you ever think you needed such services? And now we can’t imagine life without them.

Uber offers employment possibility to millions but what impact will driverless cars have on Uber? If you can crack such problems, your future is secure!

To flourish in the emerging future, you should not think of the argument as the conundrum of ‘AI vs Me’ but rather the empowering possibility of ‘AI and Me’.

The Idea Ecology

Ecology is the study of interactions among organisms and their environment. Ideas too have their ecology.

When the environment is VUCA – volatile, uncertain, complex and ambiguous, a lone genius is unlikely to find the most elegant solution to a complex problem. A network of curious people, with deep knowledge in different domains, has a higher probability of finding optimal solutions.

Brian Eno calls such a network scenius – scenius is genius embedded not in the gene but in the scene or the environment. It is collective genius. Just like diversity is important in an ecological system it is also essential in the Idea Ecology.

Stuart Koffman has postulated the theory of the Adjacent Possible – biological systems morph into more complex systems through incremental steps and not big leaps, because in a given configuration only certain types of next steps are possible. You can’t jump straight from Big Bang to Humans. Evolution is a story of a long series of adjacent possible steps.

Steven Johnson, in his book Where Good Ideas Come From, proposes that ideas follow a similar adjacent possible trajectory. The perimeter of one idea needs to be pushed till you reach the next related or rival idea. If you want to innovate you need to expose yourself to the conversation and debate around an idea. As Johnson puts it: "Chance favours the connected mind."

To generate good ideas you need to have weak ties with an appropriate network in the idea ecology. Just like you have close friends and distant acquaintances, in the idea network you have strong ties and weak ties. The more weak ties you have the more widely connected you are in the network and there is a higher probability that you will receive more information that will help you refine your idea.

In an ecological system the inhabiting organisms compete, but they also cooperate. French sociologist, Emile Durkheim has called humans Homo duplex or the two-level man – one level of the ordinary individual and another level of the sacred united, where we feel collective anger of a war, collective joy of end of a war, or collective grief of a natural calamity.

To solve the complex problems we face today and to flourish as a species, learning how things work in an idea ecology - a right mix of independent and collaborative thinking, is an essential life skill.

From Solo Artists to Knowledge Jockeys – The Story of Human Learning

Learning is in our DNA. All creatures learn and adapt; it is at the very core of evolution. Psychologist James Baldwin suggested that an organism’s ability to learn new behaviours affects its reproductive success and therefore, over generations, through natural selection, becomes part of the genetic makeup of that organism. This is called the Baldwin Effect.

The crows in Tokyo are a good example of this. They found an ingenious way to get themselves a meal by using the city traffic to crack open walnuts. Realising that picking the walnut pieces in the midst of the traffic was too dangerous, the crows figured out a new trick – use the traffic crossing instead and swoop down to pick the open walnut when the traffic stops to let the pedestrians cross! https://youtu.be/_5_DuZ8WuMM

Applying the Baldwin Effect logic here, it may well happen that future generations of Tokyo crows develop a walnut-cracking gene in their DNA, but this is still not the most efficient way of learning. Why? Because it is time consuming – it happens gradually over generations. And it is not widespread – the crows in London, for instance, may never figure out the “delicious” potential of Oxford Circus crossing!

Homo discens or ‘the learning man’ may have started out much like the Tokyo crows – observing, tinkering, imitating, experimenting and learning by trial and error, but the big difference, as Prof David Christian, historian and creator of the famous inter-disciplinary course titled Big History explains, is our ability to learn collectively. Advent of language, writing and printing press allowed us to codify, preserve and disseminate knowledge with very little transmission loss. This allowed Homo discens to become Homo sapiens (the knowing man) because we humans could quickly learn and build on the knowledge created by our predecessors and peers.

We learnt not only to preserve knowledge but also to disseminate it efficiently. The printing press was a milestone in this story and when it was invented, knowledge was created by subject-matter experts and filtered by editors. As a result, as David Weinberger, author of the book Too Big to Know explains, knowledge was scarce, but it was settled. Perhaps this was also why knowledge came to be associated with loftiness and eventually led to putting “the knowledgeable one” on a pedestal. One strong theory of learning as transmission of information – wherein the teacher is a sage on a stage and the learners are passive recipients of knowledge – evolved from this.

Homo sapiens sapiens (those who know that they know) learn through guided doing, inquiry and reflection. Eventually, this led to creation of knowledge through guided discovery and exploration, in which the teacher is a coach and a co-explorer and the learners are active participants who construct their own meaning.

And now with internet transforming the knowledge landscape once again, our theories and processes of learning are in the midst of yet another evolution. Today, anyone can publish – which, as Weinberger explains, has made “knowledge” unbounded, overwhelming and uncertain. The very complexion of knowledge is changing and it is becoming more messy and uncertain. 

To deal with this abundant and fast-changing knowledge the way we learn also needs to change. The process of learning needs the added dimension of becoming social and participative besides having the conventional component of inquiry and reflection. Collective learning and sense making enhances the rate at which an individual learns and keeps the learners’ learning curve steep, which is imperative when knowledge is exploding.

Learners today are like performers in the Indian classical music tradition: they are bound by broad guidelines, but otherwise their music is all improvised. It’s up to the learner to figure out how a musical piece could be rendered – blending with the accompanying artists, sometimes taking the lead and performing a scintillating solo piece, sometimes stepping back to let others shine and sometimes performing a jugalbandi (a challenging duet).

In the 19th and 20th centuries learners were like solo artists but in the 21st century learners need to become knowledge jockeys who can take fragmented pieces of knowledge from different disciplines and blend them as a coherent whole that shapes a new synthesis.