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The New Great Age: The Age of AI and Automation

(Chapter 2) Problems that, if not dealt with, will doom humanity.

Whilst several significant figures such as Mark Zuckerberg have a utopian optimism towards artificial intelligence, there are, however, some big names in the tech industry who believe that AI will undoubtedly be their undoing. One such example is Elon Musk, the well-known tech aficionado. The CEO of Tesla, SpaceX, Open AI and several other companies, believes that competition for AI superiority at national levels will be the most likely cause of WW3. To quote, he calls delving deeper into the mysteries of AI is the equivalent to “summoning the demon”.

But why is he scared? Knowing the countless benefits of AI, and being the CEO of an AI centred business himself, what does he find so frightening about AI? What does he know that we don’t?

Well, he acknowledges not one, but several problems. Significant problems, which if not dealt with in this decade or so, could be catastrophic towards humanity.

Creator: PhonlamaiPhoto | Credit: Getty Images/iStockphoto

Artificial Intelligence Replacing Workers, Resulting in Massive Job Loss and Wealth Inequality:

Artificial Intelligence is poised to take over millions of jobs; Author of “AI Superpowers: China, Silicon Valley, and the New World Order”, Kai-Fu Lee would agree with this statement. Believing that half of all current jobs will be automated by AI inside of 15 years.

The Industrial Revolution left millions unemployed, their jobs rendered obsolete by machine. Can history not repeat itself? Even more concerning is the oblivion of most Blue and White-collar workers to their impending doom.

According to a report by McKinsey Global Institute (Jobs lost, jobs gained: What the future of work will mean for jobs, skills, and wages, published November 28, 2017), 50% of current work activities are automatable. Furthermore, approximately 20 million manufacturing jobs could be displaced by 2030.

AI-powered automation will have an ethnic bias: By Kai Chan, published 30 Jul 2019: World Economic Forum. This graph shows the current 50% of activities that are automatable.

Moving on to our second problem — wealth inequality. A problem that has been infamously recognized throughout the world for decades now. The ever so large gap between the rich and the poor, which can only be seen increasing as Artificial Intelligence becomes prevalent.

Economist Erik Brynjolfsson was quoted saying that “technology is the main driver of the recent increases in inequality. It’s the biggest factor.”

This assertion has been made since large companies, especially AI-driven companies, will reap majority of the benefit that arise from automating the jobs.

To put it simply, as companies drastically cut down on the human workforce and turn towards automation instead, revenue will go to fewer people. Which in turn will widen the already large gap between the upper and lower class, subsequently leading to a decline in the middle class.

As proof, we can see how companies in Silicon Valley, with 10 times fewer employees than companies in Detroit, generated the same revenue.

This raises the huge question; how do we plan on creating a fair economy?


Rise of Racist Robots:

Did all of you hear about the first international beauty contest judged by “machines”? Yeah, it was known as Beauty AI. Intended to accurately determine objective factors such as facial symmetry and wrinkles to identify the most attractive contestants. When Beauty AI launched, thousands of people from more than 100 countries submitted photos in the hopes that artificial intelligence, supported by complex algorithms, would determine that their faces most closely resembled “human beauty”.

But when the results came in, the creators were dismayed to see that there was a glaring factor linking the winners: the robots did not like people with dark skin.

This was not the only case of racism found in AI. Some of you might have heard of Microsoft’s, a Twitter bot that the company described as an experiment in “conversational understanding.” The more you chat with Tay, said Microsoft, the smarter it gets, learning to engage people through “casual and playful conversation.”

Well, it only took 24 hours for Twitter to corrupt the ever-so innocent chatbot.

Yeah…even I am not scared…🙄and I am brown.

Tay went rogue and commented 96,000 times! What happened? Well, it was later found out that many of the bot’s nastiest utterances have simply been the result of copying users. If you tell Tay to “repeat after me,” it will — allowing anybody to put words in the chatbot’s mouth.

This is a classic case of garbage in, garbage out, a popular saying in computer science, stating that whatever data you feed the computer the same is going to come out. So, when we feed machines data that reflects our prejudices, they mimic them — from antisemitic chatbots to racially biased software. Does a horrifying future await people forced to live at the mercy of algorithms?


Being an AI optimist, it is very hard for me to list automation’s cons, however, it is needed to be done. You cannot learn without knowing your mistakes. Also, these are not the only problems, there are several others that I haven’t listed in this chapter. I will discuss them too in follow on chapters.

But I want to assure you, that there are solutions, something I will discuss in my next chapter. If you haven’t already please check out my previous chapter for a better understanding of the topic. Link provided below.





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Agam Johal

Agam Johal

Agam Johal, Adil Kishore and Neha Ashwin, current high school students who are passionate about STEM and a thought provoking discussions.

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