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Archives for June 2016

My TEDx talk: Jobs of the future and how we can prepare for them

28 June 2016 By Avinash Meetoo 5 Comments

On 21 May 2016, students of the African Leadership University in Mauritius organised a TEDx event. They invited me to speak about jobs of the future and how we can prepare for them.

20160628-jobs-of-the-future-slide-0

Here is a transcript of my talk. Enjoy 😉

Robots are taking our jobs

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I remember, when I was a kid, traveling to my cousins’ place by bus, seeing a lot of men and women cutting cane. I was big enough to understand that, even though this was not a very easy job to do, these people had to do that in order to earn some money. I wonder what most of them do now?

I guess most of them are jobless. They have been replaced by machines which are more efficient at cutting canes, which cost less, which work on Sundays and do not need any vacation.

And this phenomenon is happening all over the world: more and more jobs, which used to be performed by human beings, are being automated. People are being replaced by machines in various industries such as transport (think about Uber and automated vehicles), retail and logistics (look at what Amazon and Alibaba did to physical stores), sales (there are more and more automated cash registers in supermarkets abroad), travel (there are no travel agencies anymore in the USA), etc. Even education is being radically disrupted because of technology (take for example massive e-learning courses).

In the near future, a lot of people, who have jobs, will lose these jobs because of technology and automation. This is happening all over the world and Mauritius and Africa will not be spared.

Driverless vehicles

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Of course, it’s easy to say that only low-level jobs are going to be replaced. We’ll all keep our cosy offices, won’t we? Or will we?

This will all depend on how advanced computer programmes can be.

Take professional drivers for instance, those working as lorry drivers or taxi drivers.

We love to believe that only humans can drive. Yet, we are very bad drivers causing thousands of deaths every year. What If we had automated vehicles? Self-driving cars need not be perfect. They just need to be better than humans.

Right now, companies like Google, BMW and Tesla are actively working on autonomous vehicles. According to Business Insider, there will be 10 million of them on the road by 2020, in just four years! IEEE has estimated that by 2040 75% of all vehicles on the planet will be autonomous. The transport and logistics industry will be completely disrupted with potentially millions of professional drivers in the world losing their jobs.

Better than humans?

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I am sure that some of you are thinking “I am not a professional driver. I won’t ever be replaced by a robot.” Maybe yes. Maybe not.

Robot of previous generations were programmed to do one task and one task only. This has drastically changed now. Robots are now capable of learning. An artificial intelligence which can learn at the speed a computer operates can potentially start performing better than humans.

An excellent example is AlphaGo, a Google Deepmind supercomputer, which learned to play Go (a game thousands of time more complex than chess) by observing human players initially. Once it understood the rules of the game, AlphaGo started playing millions of matches against itself.

Two months ago, AlphaGo played against Lee Sedol, the best Go player in the world and, as you know I guess, AlphaGo easily beat him. On 15 March, the Korea Go Association awarded AlphaGo the highest Go grandmaster rank: an Honorary 9 Dan. It was given in recognition of AlphaGo’s sincere efforts to master Go and, wait for it, for having reached a level close to the territory of divinity. In other words, the Korea Go Association were saying that AlphaGo had become better than human beings.

Beating Go was just the start though. The supercomputers at Google DeepMind are now learning to solve practical big real-world problems in healthcare, robotics and AI…

Creative Arts

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All is not bleak though. Thanks to massive automation, we will probably work less hours and have more free time on our hands. And we will want to be entertained during our free time.

In the same way, I can foresee a lot of additional demand for entertainment such as music, videos, video games, mobile and web apps, etc. Those who can create such things will not be jobless. In fact, they will thrive as demand is bound to increase as time passes.

Remember how the cinema and music industries took off during the industrial revolution?

Of course, these creative artists will have to be more than just artists. To be able to generate income, they will have to be business people capable of creating valuable entertainment products which other people will want to pay for. Artists who succeed in creating valuable products will have opportunities to reach worldwide audiences and generate more revenue thanks to the magic of the Internet.

If you think about it, this is already happening. Consider the YouTuber for example, a one-person media company using technology to reach potentially millions of people.

But you need to realise that we are here talking about a relatively small portion of the population.

Skills needed in 2016

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Before you start thinking that I am talking about the distant future, here is a study that was done by LinkedIn at the beginning of this year. After analysing all the recruiting activity that occurred through LinkedIn in 2015, they came up with the 25 top skills needed by employers right now. What I have done is to group those 25 top skills in distinct categories and this is what I found.

As you can see:

20160628-jobs-of-the-future-slide-5-detail

35%, that is 1 out of 3 of the top 25 skills in the world right now is about software development.

30% are related to IT infrastructure which is basically to make sure that technology 24/7.

15% of these top skills are about data analysis, which is basically about making sense of vast amount of data in order to make good business decisions.

An additional 15% of the top 25 skills are about digital marketing, which is how to leverage technology to do promote and sell products.

Electronics, economics and law are the only non IT skills in this list of the 25 top skills of 2015-2016 and they only represent a tiny percentage of new jobs.

Science, Technology, Engineering and Maths (STEM) and Computer Science

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Now, software development, IT infrastructure and data analysis form part of Computer Science. Therefore, it seems that computer scientists will be highly sought in the coming years. A good question then is how one can become a skillful computer scientist?

Well, everything starts with a good background in STEM that is Science, Technology, Engineering and Maths. Of course, here, I am not referring to learning the bare portions needed to pass an exam but rather becoming a rational, logical and methodical scientist capable of understanding extremely complex problems and coming up with creative yet feasible solutions.

In other words, we need real professionals. We do not need paper degree holders who don’t have a clue. Major countries like the USA, France, Germany, Singapore, China, India, etc. are putting a lot of emphasis on STEM development and this has been happening for years. Now, they are reaping the benefits by having a very skillful workforce with a substantial proportion of technology entrepreneurs.

Unfortunately, in most African countries, and this includes Mauritius, only few students choose STEM subjects at secondary level. Only a handful of the most capable ones then pursue higher studies in Computer Science. This is clearly not enough.

We need to find ways to encourage young people to chose STEM subjects at secondary level and embark upon Computer Science at university. This needs to be done or else we will lack skillful professionals in a few years.

STEM + Arts = STEMA

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In a certain way, I understand why some students are reluctant to choose STEM and Computer Science. Schools and universities are sometimes too academic and, dare I saw, boring. Teaching methods need to change in order to attract more of our brightest minds. Technology needs to be used to its full potential in class.

One way to make classes more interesting do that is to combine STEM with Arts. Instead of creating STEM people, let’s create STEMA people.

A STEMA curriculum might include, day, the creation of a video game. Someone who has been trained to be a STEMA person will be creative enough to design the video game and skillful enough to actually program it and market it.

If you think about it, those visionaries who have changed and are changing the world as I speak, people like like Bill Gates (who founded Microsoft), Steve Jobs (who founded Apple), Linus Torvalds (who created Linux, the free software which now powers the world), Mark Zuckerberg (of Facebook fame) or Elon Musk (SpaceX and Tesla) are all STEMA people. They are all Computer Scientists who are extremely imaginative and creative.

We need people who who can bring new perspectives, who can disrupt existing industries and change our lives. We need more visionaries.

We should stop confining young minds to classroom boundaries.

Knowledge Seven 2.0

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You have realised by now: I am passionate about fostering a new generation of STEMA people, Artistic Computer Scientists.

I have tried to do that in the various tertiary institutions where I have worked but I have only partially succeeded at this mostly because of reluctance to change. Eight years ago, I quit being a university lecturer to create my own training company, Knowledge Seven. The initial objective was to provide the best professional face-to-face training in IT in Mauritius. And we did it. But professional face-to-face training is not the solution. This needs to happen earlier and on a much larger scale.

This is why, at the end of last year, I took the decision to build an innovative online learning platform called Knowledge Seven.

We want to revolutionize the way people learn Computer Science by combining it with Artistry. We want learning to be online. We want people to learn together. We want people to have fun learning. And people need to be able to learn anytime, anywhere.

This is not a platform for young people only. It is for anyone, in Mauritius, in Africa and elsewhere, who needs to learn programming, so potentially everyone as computers are so prevalent now, in every field, whether you are in finance or in the media or whatever.

The first version of the Knowledge Seven platform will be ready at the end of 2016.

Let’s grow the future of Africa together!!!

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Our world has changed.

In the near future, most tasks will be automated and we need to adapt. Our lives will be impacted. Our jobs will be impacted.

We, Africans, do not want to be on the sidelines. We want to participate in this digital revolution. We want to build our own future.

Let’s encourage more young people, our kids, to embrace STEMA

Let’s create a new generation of Artistic Computer Scientists.

Thank you.

Filed Under: Art, Computing, Education, Future, Science, Society, Technology

How to Succeed Overnight in Ten Years

18 June 2016 By Avinash Meetoo Leave a Comment

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I just stumbled upon a very interesting article by Ramit Sethi: Why Successful People Take 10 Years to ‘Succeed Overnight’. Here are some essential quotes from the article:

The strategy that works over and over for successful people is the Domino Strategy. The Domino Strategy is simple:

First, start so small that you can easily knock over the first domino. Second, put the dominoes in just the right sequence so that each small step makes the next, bigger step possible.

That’s it.

He then explains that starting a business require one customer. Having thousands or millions of customers can come later (as a later domino). In other words, every successful company started small and took a lot of time (10 years) to become successful. They did that by doing one thing at a time, each subsequent thing larger than the previous one.

Those who dream too big (and waste years and years building their dream product or service) tend to fail spectacularly. In a certain way, this is related to the Lean Startup philosophy as exemplified by Eric Ries. He argues that companies tend to fail because of lack of validation from customers.

Ramit then asks why, given that the domino strategy is so compelling, only a few people use it (and, those who don’t, tend to fail)? He writes:

One of the biggest obstacles is invisible scripts, assumptions so deeply embedded in our [minds] that we don’t even realize they guide our behavior.

What’s the biggest invisible script? All or nothing, the idea that you need to go all-in or you should just not do anything at all.

He then explains that this is why people look for magic bullets or win at the lottery. As these never happen in general, people then become disappointed in what they are doing:

without realising that success is imminent:

His advice is to start small, focus on knocking down your first domino and be patient.

Peter Norvig, in his Teach Yourself Programming in Ten Years article, also mentions that mastery takes time. He says that anyone who wants to become a very good programmer has to be patient enough to wait 10 years while engaging in knocking down bigger and bigger dominoes:

  • 1st domino: Become interested in programming.
  • 2nd domino: Program (learn by doing).
  • 3rd domino: Talk with other programmers and read other programs.
  • 4th domino: Go to university (optional).
  • 5th domino: Work on projects with other programmers.
  • 6th domino: Work on projects after other programmers (and find remedies for their mistakes).
  • etc.

Knowledge Seven, my company, started offering training services in January 2009, 7 and ½ years ago. This means that I still have 2 and ½ years left in my 10 years plan.

I have an idea of what my next domino is going to be.

Filed Under: Computing, Education, Future, Society

Computer Science is not a Science

1 June 2016 By Avinash Meetoo Leave a Comment

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A few days ago, I drew the following and posted it on Facebook:

20160601-fields-of-computing

The discussion which then took place was very interesting.

Selven Cheenaramen and Pascal Grosset were in the opinion that Computer Science is not a Science. Selven referred to Jonah Kagan’s post Computer science isn’t a science and it isn’t about computers which states that:

Computer scientists are concerned with questions like: How do you find the shortest route between two points on a map? How do you translate Spanish into English without a dictionary? How do you identify the genes that make up the human genome using fragments of a DNA sequence?

There’s a difference between the question, “How do you identify the genes that make up the human genome?” and the question, “What are the genes that make up the human genome?” The latter, a question posed by biologists, asks for a specific fact, while the former asks for a procedure (an algorithm) which can produce that fact.

Consider any science: chemistry, biology, physics, or even one of the “soft” sciences like psychology. All are concerned with answering factual questions about the world around us. In computer science, the goal is not to figure out the answers to factual questions, but rather to figure out how to get answers. The procedure is the solution. While scientists want to figure out what is, computer scientists want to know how to.

Jonah Kagan then states that, given that Computer Science is not a Science, then it is Mathematics:

Since the problems solved by computer scientists are defined separate from the real world, we can’t use the scientific method to analyze their validity. We can only analyze procedures within the realm of abstraction in which we have created them. Luckily, this type of reasoning is exactly why we have mathematical logic. Mathematicians, too, are concerned with the idea of truth in the abstract. Instead of running experiments, computer scientists define problems and procedures mathematically, and then analyze them using logic. This is the fundamental reason why computer science is not a science.

Given that the correctness of procedures is proved using mathematical logic, it might seem like computer science is really just a branch of mathematics, which it is, in some sense. In fact, much of the “math” we learn in school is actually computation.

He then explains that computers are not essential in Computer Science:

[T]here’s nothing fundamental about procedures that requires the use of computers. Computers aren’t the only tools that can be used to execute programs. For instance, elementary school students are perfectly capable of executing the long division algorithm. We use computers instead of small children because computers are fast and reliable […]

Aha. We just use computers when doing Computer Science because they are fast and reliable. If computers did not exist, we would have done the procedures by hand but the whole process would have been much slower and error-prone.

So it looks like Computer Science is not a Science and is not about computers. But is it? Jonah Kagan acknowledges that:

While at its core, computer science really is the pure study of procedures in the abstract as I described, in reality, the field has grown to encompass a wide variety of pursuits. Some computer scientists are concerned mostly with designing intricate systems that rely heavily on the specifics of computer architecture. Others study human-computer interaction, which actually does use the scientific method to determine what types of interfaces work the best for computer users.

It would be easy to dismiss the outliers and say they are not true computer scientists, that their work falls under the umbrella of some related but fundamentally different field. But I think the breadth of study within computer science is not necessarily a bad thing. It doesn’t need to be strictly defined.

[…]

In the end, its the rate of growth of the field that makes all this definition business so tricky. Computer science is still young, and always undergoing new growth spurts.

In other words, Computer Science might become a Science in the future.

Hansley Chadee then offered this very interesting perspective:

Artificial Intelligence is the bridge between all of this (Computer Science) and the natural world, including philosophy…

Aha. My interpretation of this is that, once, we, human beings, invent Artificial Intelligence (and it seems that Google Deepmind has already done so…) then Computer Science becomes a Science as we would have explained the functioning of the natural brain.

Noorani Bakerally then finally stated (I am paraphrasing as I cannot find his post on Facebook):

Do not forget that we, human beings, with our limited capacity, can only understand a small portion of nature. So there is surely more than Science…

Given these compelling evidence (and while AI is not pervasive yet), allow me to update my initial drawing:

20160601-fields-of-computing-final

Filed Under: Art, Computing, Education, Science, Technology

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