Machine Learning; Surviving as an innovator or a surplus?

 

The Era of Great Pressure

American economists often refer to the 1950s and 1960s as the era of 'the great compression'.

This is because the income disparity between the classes has narrowed dramatically during this period.

In other words, it was a booming period. Everyone could be almost equally wealthy and economically equal.

How could this be?

There may be various reasons, but the most notable is the 'economic structure'.

The mass production and consumption system represented by 'Taylor-Fordism' blossomed after World War II.

The highly divided and standardized work system created numerous jobs. Also, laid the foundation for equal wealth for all.

However, starting in the 1970s and 1980s, the gap between the rich and the poor has widened.

It was only 20 times in 1965, but it is said to have exploded to 295 times in 2013.

Why did this happen?

The Shadow of the Information and Communication Revolution Mainstream American economists talk about changes in the economic structure.

The so-called information and communication revolution is destroying the system established by Taylor-Fordism. It's creating a unilaterally favorable working environment for a minority of workers.

MIT Professor Eric Brickjolfson in his book <The Second Machine Age> says:

“As computer performance improves, the number of employees a company needs will also decrease.

Computers take over. As a result, the contrast between workers is terrifying.”

“Now is the best time for workers who can control their technology.”

“On the other hand, these are the worst times for workers competing with technology.”

 

 

Foxconn group was founded in 1947, 47 years ago. Foxconn, the world's largest electronics producer, has automated a large part of its production system. And announced that it will introduce 1 million robots to further reduce its workforce.

So, Is your job replaceable?

In this regard, I want to talk about an interesting and creepy tech trend.

Recently, researchers are conducting research in the field of artificial intelligence. That is related to machine learning.

Machine learning is a technology that increases the ability to analyze data. This is done by repeatedly learning a specific topic according to a specific algorithm.

A data expert named Jeremy Howard said this in a TED talk:

“In most civilized countries, service industry accounts for 80% of employment”

“But the problem is that the skills required for the service are the ability to speak, read, see, and write.”

“It's a place the machine hasn't reached yet.”

“However, the recent advancement of machine learning is penetrating here. It's not in the distant future.”

“Simply put, 80% of employment could be lost.”

What does the future look like?

Looking at past cases, there is only a difference in implementation time. However, it cannot prevent technological development itself.

So, when we take an extreme approach, we can think of two scenarios.

Pessimistic future:

The current trend continues and 1% of technological leaders have all the production systems, power, and wealth. The remaining 99% live as surplus people who simply repeat consumption.

Once again, to express it to the extreme, it could be the appearance of the movie. <The Matrix>

 

Optimistic Future:

1% of technology leaders present an overall vision and trends. The remaining 99% are also functions that technology cannot access. Hence, improving all the problems facing humanity.

What technology does not have access to is innovation and creation.

Of course, sometimes we use technology.

This is in line with the concept of zero to one. The venture capitalist Peter Thiel is talking about.

If that happens, the race that covers the state of the not-too-distant future could become Earthlings.

In other words, it is not an exaggeration to say that we are all at a crossroads between whether to survive as innovators or as surplus humans.