Robots in the Workplace

Quinn Voboril

The Problem

       There is an active rise in workplace automation which can threaten the US national Economy. More people will be out of jobs, and cannot contribute to paying taxes and reintroducing cash into the market. Workplace automation stands to take nearly 121 million jobs face the chance to be replaced by robots, and nearly 29.5 million are already at stake.

Figure 1:

What Jobs can be lost?

       According to reports written by USA Today, jobs that are predictable are in jeopardy due to automation. Think factory workers or meat packers. With the advancement of Artificial intelligence, even jobs with some form of unpredictability can be replaced. Jobs in the Automotive Service Industry, and in the textile industry are now of major concern due to automation.

What Jobs aren’t in Jeopardy?

Logically, jobs with unpredictability, or those with the demand for a human are the least likely to be replaced. They aren’t all just high-end engineering or business jobs too. Teaching, preforming, and jobs that demand human opinion are in fact the farthest from jeopardy. Ambulance drivers need to be quick thinking, and must be able to process several hundred random components at any given time. Teachers must identify issues in the classroom, grade fairly, and maintain good moral among students. Think of any job that needs a human brain, and the randomness of the human brain to operate for humans, and that job is nearly resistant to automation.

Why Game Theory?

Workplace automation can be handled with game theory to find the projected outcome for a worker in a certain field of work. In a basic sense, We can play a “game” between a workforce, and a government, who plays deciding how much jobs are taken by robots. Game Theory deals a lot with Matrix based games, and in the game I am about to present, there will be a few details to point out.

The Matrix


Job Force

Subsidize robots at 100 % automated jobs




Subsidize robots at 75 % automated jobs




Subsidize robots at 50% automated jobs




Subsidize robots at 25% automated jobs




 Manufacturing Worker

( or similar jobs )

            (-29.5 , 740222 )               (-22.25 , 555165)               (-14.75 , 370111)              (-7.375,185055 )

IT Specialist Managers

( or similar jobs )

             (-41 , 5395600)             (-30.5, 4046700)                (-20.5, 2697800)                (-10.5, 1348900)

Pest Control Officer

( or similar jobs )

              (-23.6 , 708000)              (-17.7 , 531000)              (-11.8 , 354000)               (-5.9, 177000)

Pipe Fitters

( or similar jobs )

              (-38.1 , 1672000)              (-28.7 , 1254000)              (-19.05 , 836000)              (-9.525 , 418000)

To layout some vocabulary:

Orange – Strategies. Each player has the choice to utilize a selection of strategies. Depending on how their employer plays, the payout goes to the intersection port. 

Green– Payouts to the players. Shown as (x,y) x applies to the work force, and y applies to the government. payouts for the workforce are the loss of jobs in each field, and payouts for the government are cash going directly to companies that don’t need to pay employees.

Blue – The Blue refers to the government, who has the  four strategies which utilize certain robots at different percentagesIn this case, the government plays for an equal pay to themselves and to help some workers. but rather its decision is based on the likely hood of replacing that job with automation.

Red – The red applies to the work force, who is choosing to go into a certain field. 

So why the payouts? 

In order to visualize the severity of the situation, every payout to the college student, either +x or -x, is the amount of jobs secured in their percentage range. Payouts to the workplace are the millions of dollars companies stand to save or lose, so +y or -y.


The government, if they were not playing for the greater good of society, would play strategy 1(subsidize 100%). But, in logical scenarios the government cares for all of its people while still maintaining profit for businesses, which we can see by displaying the chances someone plays a certain option.

If the job force would play a job with the least likely to be automated(IT Specialists at 67% play rate) and the government was testing the results of each of their strategies(playing each one randomly with the same chance), we can calculate the value for the game.

Calculating the payout for the job force:

When government plays 100%:

-23.9*(0)+(-41*(.67))+(-23.6*(.23))+(-38.1*(.1)) = -36.708

When government plays 75%:

-22.5 *(0) + (-30.5*(.67)) + (-17.7 * (.23)) + (-28.7 * (.1))  = -27.37

When government plays 50%:

-14.75 * (0) + (-20.5 * (.67)) + (-11.8 * (.23)) + (-19.05 * (.1) = -18.35

When government plays 25%:

-7.375 * (0) + (-10.5 * (.67)) + (-5.9 * (.23)) + (-9.525 * (.1)) = -9.3445

Taking these values we then arch them over the chances they actually happen:

(-36.708 * (.25)) + (-27.37 * (.25)) + (-18.35 * (.25)) + (-9.3445 * (.25)) = -22.94

Thus the expected payout to the job force is to lose 22.94 million jobs


Calculating the payout for the government:

When the Job force plays factory workers:

(740222 * .25) + (555165 * .25) + (370111 * .25) + (185055 * .25) =46263 

When the Job force plays IT specialists:

(5395600 * .25)+ (4046700 * .25) + (2697800 * .25) + (1348900 * .25) =3372250

When the job force plays Pest control officers:

(708000 * .25) + (531000 * .25) + (354000 * .25) + (177000 * .25) =442500

When the job force plays pipefitters:

(1672000 * .25) + (1254000 * .25) + (836000 * .25) + (418000 * .25) = 1045000

Taking these values we then arch them over the chances they actually happen:

(462638 * 0) + (3372250 * .67) + (442500 * .23) + (1045000 * .1) =2465682

Thus the expected payout to the government is 2465682 million dollars

What this means is that when both players play with their current decisions, many games over, it will result in (-22.9, 2465682). That means 22.9 million jobs will be lost, only in testing automation at different levels. If the government were to only play 100%, 121 million jobs would be lost(assuming all fields were automated).



A possible solution:

Support your local workers unions. Most unions that house Industrial workers are fighting to cap the legal amount of jobs that can be replaced by robots. By doing so, and hoping that automation opens up enough doorways into new fields of expertise to house those who will lose their work. Many things you can do are go to local government to make demands to change income tax to consumption tax, by signing this petition. by doing so you can help make lives with robots easier because of the many advantages of consumer taxes for people that have jobs that pay lower amounts.

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