Will AI Replace Humans in the Workplace

There has recently been a lot of conflicting information in the press concerning prospective employment losses due to artificial intelligence in the workplace. They vary from Bill Gates' hand-wringing claim that we should slow things development by taxing robots to Treasury Secretary Steve Mnuchin's illiterate statement. "In terms of artificial intelligence taking over employment, I believe we're so far away that it's not even on my radar." "I believe it's another 50 or 100 years."

But they aren't the worst of the conversation's extremes. There is almost little effort in the popular press to distinguish 'robot' from 'AI.'

AI-enhanced robots have received much attention in the media and are on the minds of many data scientists. So, would breakthroughs in deep learning (AI) or robots as they already exist be the primary source of future job loss? How many jobs will be replaced by AI?

Automation has Always Involved Shifting Job Requirements

Job loss, or more accurately, workload and skill redistribution due to automation, has occurred since water wheels displaced human work in ancient societies.

In 1779, Ned Ludd, an English apprentice, shattered two automated stocking frames in protest against the loss of human labor, eventually leading to the political organization and word "Luddite." (Remember that the mechanized stocking frame was created in 1589; therefore, the social outcry occurred about 200 years prior.) Then there's John Maynard Keynes' famous forecast of vast technological unemployment "owing to our discovery of techniques of economizing the use of labor outrunning the rate at which we can discover alternative uses for labor" (1933).

What hasn't changed is that they may not appreciate the abilities we gained as children for the rest of our working lives. This increases the risk for those who work. It has resulted in a transfer of labor towards higher-paying high-skill positions and a clearing out of monotonous industrial duties into predominantly lower-paying service sectors during the previous 20 or 30 years.

According to several previous academic research, the percentage of US employment threatened by automation ranges from 35 to 45 percent. Remember that these forecasts are based on the occupations available in the economy as of 2010 and do not account for how new employees or sectors may modify their employment demands considering a rapidly changing environment. Career opportunities in 2010 may easily be obsolete (due to automation or else) in 2020; the percentages will inevitably be exaggerated.

Is the Root Cause Robotics, Artificial Intelligence, or Both?

The prevalent image of robots is that they've been rapidly becoming sharper and more competent. Within data science, we understand that the present hockey stick curve in capabilities is mostly a product of deep learning approaches, often clubbed together as AI.

We also understand that people have only effectively implemented corporate deep learning applications since 2015. We chose that year when deep learning image classification eventually passed the human accuracy threshold (95 percent in the annual Image Net competition) and roughly the same time that speech and text analytics reached around 99 percent accuracy, enabling the massive proliferation of chatbots.

AI Will Create More Jobs Than it Destroys

The epidemic of Covid-19 has expedited the deployment of cutting-edge technology. Automation is profoundly altering, rather than just touching, every area of daily life, from contactless cashiers to welding drones to "chow bots" — robots that serve out salads on demand. Customers may be pleased with this possibility. They are giving up human stupidity in favor of algorithmic (and mechanical) perfection resulting in better, cheaper, and quicker service. But what might employees who used to supply these services anticipate? Can they profit from technical advancement as well? If so, how so?

Researchers frequently examine the impact of AI on future jobs through the prism of creating jobs or work destruction. Economists almost universally regard technology as either displacing or reinstalling labor. Jobs are lost as technology replaces workers. Jobs are produced when technology produces (or restores) work. The essential question in this duality is whether technology makes more employment than it kills. According to the World Economic Forum, by 2025, technology will have created at least 12 million additional jobs than it has destroyed, indicating that automation will be a net benefit for society in the long term.

Automation vs. Human Labor

Calculating The Cost of Automation vs The Cost of Labor

The most typical place to start in these considerations is cost. Begin by explicitly outlining your goals and determining the success indicators (for example, revenue targets, scrap rates, rework requests, or downtime/uptime ratios). These measurements are the most objective benchmarks to determine if an automated or human arrangement is ideal for your company.

Next, gather as much information as possible regarding automation and human labor expenses.


● Human labor costs:
● Wages and pay inflation
● Non-wage benefits and training
● Insurance for workers' compensation.
● Salaries taxes
● Auxiliary safety gear.

The prices listed above are pretty easy to calculate. Managers must also account for some indirect costs. These are more difficult to measure but equally important in your comparison:


● Human mistake poses a safety concern.
● Human error causes product loss and rework.
● Human work moves at a slower speed than automated procedures.
● The expenses of automated procedures are as follows:
● Initial gear and software purchases, as well as installation.
● Operator education and pay.
● Maintenance is ongoing.
● Stoppages caused by planned or unscheduled part replacements for
● Adaptable automation systems.

There are fewer unknowns and intangibles with automated methods. This does not always imply that they are superior, nor does it always suggest that they are the most cost-effective option. It can, however, assist you in reducing wasteful workforce maintenance costs (due mainly to employee attrition and repetitive training fees) and redirecting your personnel toward jobs where individuals thrive.

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