Part 1 gave an insight into my thoughts and understanding of AI and ML, and some developments that I found interesting. In this article, I’ll focus on and bring out some points to answer the question, “Can a robot be programmed well enough to completely replace a human in the job sector?”

Here is something else to think about: can a machine feel its own worth or the value of its work? Can a machine empathise with a situation to write a song or story based on that, or can it only generate Markov text if given enough data? Can a machine appreciate or understand the consequences of its actions? Given that it can never have a “conscience”, what will it base its decisions on?

Replacing humans with machines has not only reduced the errors in critical areas (probably), but the respect one has for humans also seems to have gone down, simply because it is a machine that’s now doing the job. Simple example, cricket. Earlier, the umpire used to have all the power in the world when it came to making decisions, and that’s how he earned his respect. Now, nobody cares about his decision; the moment you think he is wrong, you just ask a machine to do his job.

Going back to the other question that I brought up earlier, what are the jobs that humans need to focus on? Given below are two images. The first one depicts the kind of jobs that most people think will be popular – focused majorly on computing and data analytics. The list in the second image, in my view, is much more diverse and much more realistic, proving again that the future has scope for a lot more than just AI. Jobs like solar and wind energy technicians, as well as bicycle repairers (the last one is also my personal favourite) will become more prominent to fight the energy crisis in the world. I’m surprised that the list doesn’t mention doctors, but instead mentions a variety of jobs focusing on people’s health and wellness – physical and mental.

So some of the not-so-popular but crucial areas where we need expertise in the future are mainly energy management, waste management, medicine, psychology and the most underrated job of all, teaching. You can never have too many of these people.

I might not be familiar with the first four categories mentioned above, but the last one is something I have thought about. One of the biggest flexibilities as far as education is concerned is the concept of online learning i.e. the fact that you don’t have to go to a physical classroom to learn. Nevertheless, the teacher is still human. In Finland, people have tried something new: a robot teacher. Is this beneficial or is this nothing more than a small-scale trial run? That will depend on what we want a teacher to be. Someone who just lectures and grades? Yes, a robot can do that, probably better than a human. But if you see a good teacher as someone who motivates, guides and nurtures beyond what’s required of the position – or on a very simple scale, someone who is capable of getting the attention of five people in front of them – then only a human can do it.

I guess what I feel is that AI and machine learning and data science might end up being only a tiny fraction of the factors that shape human life in the next decade. Moreover, it’s not just jobs which are the concern. The entire planet is under danger of population explosion, global warming and other related phenomena. Whether or not jobs exist, humans will keep being born, at an alarming rate too.

Nevertheless, AI has numerous positive aspects too. It can help assist humans – even if not replace – in various ways; it may take away some jobs, it might bring in new ones. While there is a flock of people going gaga over these areas of interest, I feel that there are many more areas to explore which people are not aware of. So, will AI be absolutely indispensable or will it be actually insignificant? Time will tell. 

Twenty-five years ago, in 1984, James Cameron predicted a world in 2029 where machines would take over and humans would form a small army to fight against the machines. That’s ten years away. Of course, there have been dozens of films which showcase the Earth at different points of time in the future, each one more dystopian than the first, but I think in all our minds, there is the troubling question of “Where are we headed?”

While thinking about every possible aspect of the human race and planet Earth ten years from now is potentially an endless discussion, one topic that intrigues me most is that of artificial intelligence. First up, I must admit that I am a novice when it comes to the plethora of developments, advancements and subtleties of machine learning and AI, but as a novice, or as someone who has never been addicted to or sucked into ML and AI, here are some thoughts that go on in my head.

Two things are infinite: the universe and human stupidity; and I’m not sure about the universe.

Albert Einstein

Here is a quote we’re all familiar with. Why do I use it here? Because if you are an optimist, you will look at the scenario today and claim that machines are becoming more intelligent. If you are a pessimist – like me – you will claim that (the majority of) humans are becoming dumber. Of course, both cases could be true. At a time when most people are becoming increasingly lazy and incompetent, a small group of humans is training lifeless machines to take over.

This is my understanding of how machine learning works (Here is a formal definition by Wikipedia):

1. A machine must be able to collect or use data that’s fed to it about some task or scenario.
2. It must then be able to make a decision or act accordingly upon encountering unseen data in relation to the same task in the future.
3. Most importantly, a machine must be able to learn from the data to also be able to take the right decisions when it encounters situations that it hasn’t been trained against.

The first two points are more related to automation, while the third is the reason behind the “learning” in machine learning, more in relation with AI. Here is a definition of AI that I found interesting: “A system’s ability to correctly interpret external data, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation.”

Currently, the trending words and phrases everywhere include the words used above too. The first thing I started thinking was, “Why is there a sudden craze for automation and AI now? Starting with the assembly line, bit by bit, machines have been replacing tasks that only humans used to do.” Then it struck me (after glancing the cover of a book lying around at home, which reads What To Do When Machines Do Everything): the idea now is not to just replace humans with machines that can do repeated, mechanical tasks (which the advent of robots is taking care of); the idea is to make machines do… everything.

From our school days, we’ve been told that we humans are the “most advanced” species on the planet because of our capacity to think and the ability to show emotion. The other crucial features are, of course, the ability to take a decision and the gift to be creative. Suppose a machine can do all of these, what’s next? This makes us wonder what other feature is unique to humans that a machine cannot imitate.

The last point is the major factor in deciding which jobs humans will have left to do. Workers in factories are increasingly being replaced by robots. So are drivers and delivery men. So what are the areas which thrive on the decision-making capacity and creativity of humans? Law? Well, if decisions are going to be taken only by referring to past incidents and rules, then a machine can be programmed to do that.

There are fantasies which involve machines writing poems, authoring books, teaching, and feeling empathy. Here is a fun website to look at – one where you have to predict whether a given poem is written by a human or a bot. Will there be a time when a machine can direct a movie? Here’s an interesting article, about the first AI-made trailer for a film. Is this the first step or is this just an experiment with not much scope further? I, for one, believe that all of these fantasies are near-impossible to achieve. These are all areas which rely on one’s creativity and artistic sense. In theory, maybe, given enough randomised trials and enough data, a machine might come up with something that can be called a “poem”, but it will never feel “real”, to those who read it.

So far, I’ve given some of my ideas on how I understand the concepts of ML and AI and related topics, along with some articles which talk about the recent developments in the field. Part 2 will focus more on the jobs of the future, and whether or not a machine has all it takes to completely replace a human in certain sectors.