The raging debate today in 2019, as it has previously been during the ‘Automatic Teller Machines (ATM) replacing bank tellers’ controvert, is the concern whether artificial intelligence or machine learning will result in computers becoming so advanced that people will lose their jobs?

When personal computers were first invented, people produced movies that machines are going to have a mind of their own (kind of similar but not the same as self-learning computers) and take over the world. Computer chips embedded in robots, like in that robot-cop movie; fighting crime. Yes, very futuristic.

We can quote statistics of projections done by researchers that show numbers and whatnots, but that is all that they are; projections. No one can tell you for sure that it’s going to rain tomorrow much less about your promotion or demotion chances due to computers. There are simply too many moving variables in these matters.

So, what is important? What point do we take note off?

Well, for one thing, we can look at what the printing press did for the world and what computers did. The printing press meant dissemination of knowledge became faster and wider. The personal computer meant increased productivity through word processing software. The Internet meant content produced by that software gets discussed and distributed globally, – and instantly.

Productivity went up, wages went up and even if they did not, our standards of living went up because now people have access to better knowledge and healthcare. A simple illustration of this is that if you are sick and you are new in town as a tourist, you can simply Google, “top 24 hours clinic in Austin, Texas” and you’ll be well on your way to recovery from cold or more serious health issues.

A more current example is if you upload your video of singing, you have a chance of becoming a recording artist; the next John Mayer.

Or if you are a writer, the next JK Rowling, if your ebook sells like pancakes.

JK Rowling had her life changed upside down for the better with the help of word processor.

 

Capital and Data Analytics

With due respect to other strategic enablers such as a vibrant reading culture/country, her “capital” was mostly intellectual capital.

And this is where I go into my point about data analytics. If you think about it, you can look at data or more precisely meaningful information (which is the equivalent of solutions) as capital. There is financial capital (money), social capital (your network) and intellectual capital. Data falls into that last one I mentioned.

When a consumer research company (or research company like Nielsen) or financial information services company like Bloomberg broadcast financial news or provides “insights”  through Bloomberg Terminal, the bankers who extrapolate or interpret their information is trading on/making a living off data, i.e. intellectual capital.

This is connected to an interesting concept that arises in this 21st century that we live in. Because information is so abundant on the internet: curating and organizing information becomes a lucrative business/profession. We don’t have to be a writer or inventor to make money. By becoming a proficient user of  Bloomberg Terminal or other software, we can become a technical analyst or financial analyst using data provided by data providers.

An extension or another level of that is data analytics whereby it is about data analysis to drive business decisions and contribute to wealth creation or profits. What is the best way to reach 40-year-olds with high disposable income driving on highways if you operate a golf course resort? Is it electronic billboards with creative ads while looking at data such as how many cars use the Kuala Lumpur MEX highway? Or we look at the traffic on the ‘highway’ of the Wall Street Journal where business decision-makers in their thousands read to get informed, to get content… to make decisions where to go golfing.

In all seriousness, these are all important questions.

And these questions translate into jobs for people: data analyst jobs in banks, government, advertising companies etc.

 

Leverage

By now, we can see that the conflict is NOT us against them in this so-called age of man versus machine, it is about leverage. Some may think leverage is a dirty word. It implies taking advantage of someone or something, i.e. abuse.

But it is not about that.

As a famous writer once said, it is best to look at relationships as interdependent. This means just as we need each other to have a good work life at work, we must strive to form mutually beneficial relationships with computers. Learn how to use them to be productive without becoming addicted to mobile phones or computer games. So this “conflict” is really more imagined than real.

Of course, job losses due to technology are real, but so are job creation by computers. Those who can’t walk and are in a wheelchair have the opportunity to work because they can work from a desk now. That’s ‘a good creation’ due to machines.

 

Conclusion

Think positive about (disruptive) changes and try to take advantage and turn the tables in your favour. That could mean taking a short course, learning new software…or starting an entrepreneurial venture with the help of computers. Becoming a wedding video editor/photographer…?

Or more in tune with the trend, becoming a digital marketer leveraging on data analytics. Using social media for business.

Last message to advocate before I sign off: thinking positively is the only way to live life.

 

Author’s Note: This author wishes everyone a Happy Chinese New Year and continues to enjoy coffee, in moderation.

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