Developments in Artifical Intelligence technology (A.I.) are projected to impact the global market in an unprecedented way. In a few years, life and business could be vastly different because of A.I., similar to the way WWW or the Industrial Revolution did.

Profit is probably one of the most important parts of Business. Further, our globalised world has forced all producers and manufacturers to sell their goods or services as cheaply as possible. This means that businesses, no matter the size often emphasize reducing production costs. Insert the prospect of Artifical Intelligence and things get a whole lot more interesting. To be fair, as of the date of writing this article, the technology is still quite a ways away, but to quote Dr. Ian Malcolm:

Looking to a point 10 years in the future it may be difficult to ascertain the state of technology especially in countries like Guyana, which are typically behind the innovative curve. Nonetheless, we need to be prepared for the worst. A recent study at Oxford University estimated that about 47 percent of (US) employment is at risk of dissipating. In fact, a cursory google search should give about four pages of results showing exactly what jobs are already liable to performed by some incarnation of Artificial Intelligence.

A short list of the jobs that might be affected is as follows:

  1. Lawyers – it saddens my heart to say that the legal profession is bound to be affected, particularly in non-contentious work, by A.I.;
  2. Financial Analysts;
  3. Customer Service representatives;
  4. Engineers and Architects;
  5. Marketing and telemarketers;
  6. Drivers – Unless Skynet is an inevitability then it goes without saying that self-driving cars are the future;
  7. Assembly line workers;
  8. Restaurants and Chefs;
  9. Journalists;
  10. Medics;
  11. Construction workers and manual labour jobs – Machines like SAM (Semi-Automated Mason) can lay bricks twice as fast as human builders. You can see it in operation here; and
  12. Personal Assistants – speaking of Google, it recently demonstrated the leaps and bounds that its Google Duplex has made in convincing unwitting persons that they are speaking to real persons:


At this point, it is inevitable that we will become so obsessed with optimising performance that we won’t care if we replace hundreds of workers with machines and AI.  The question for a lot of persons is, how do I weather this storm?

The answer is a tricky one. But have no fear! I made a list –

  1. Pay attention to the news

    You should start keeping tabs on developments in Artifical Intelligence. In other words, if you are employed in a field likely to be affected by AI then you need to be looking out for the proverbial asteroid. This may mean subscribing to a few mailing lists (like Gadgetrave’s) or having sites send desktop notifications.

  2. Recognize the areas that AI is likely to thrive in

    As of today’s date, AI does exceedingly well with tasks that require repetition and data processing. It’s worth noting that Artifical Intelligence is getting better every day.  The list above isn’t a comprehensive one and there may be a more active way to track which areas AI has infiltrated: the so-called ‘automation risk’ test.

    Unfortunately, If you’re in a field that will be automated you may have to consider looking for a job in the near future. This depends on how well AI is integrated. Especially, in countries that aren’t at the forefront of the innovative curve.

  3. Git Gud!’ (Learn a new skill)

    Importantly, if your field is to be automatised then you must consider learning another skill. Whether this is a tech related skill or something new all on its own. You should consider taking a class even if it’s not certified. In fact, Harvard, in partnership with Edx has many free courses available in a wide range of areas, including computer science that you can take online!

    Google also offers free tools for learning how AI works and how to deal with it. Stanford University also has a similar programme. It starts with basics and takes you all the way to Machine Learning System Design and Unsupervised learning.