AI Is Changing Jobs, Relationships, and Life Planning

This contains the prospect that 'suffering (受苦),' meaning pain, will become a new measure proving human value. As existing simple and comfortable tasks are replaced by AI, human labor and its value are being socially reevaluated.

In the past, 'working easily and comfortably' was the standard for a good job, but an analysis suggests that in the AI era, 'deep sweat' will be socially revered.

This is expected to elevate the value of handwork that adds aesthetics and precision, rather than simple assembly-line labor.

Writer Song Gil-young predicted that, unlike in the past, social gratitude for sweat-driven labor will grow.

The phenomenon of tile layers' labor costs approaching 1 million won becomes a trigger for society to begin developing immediate replacement technology.

Such technological development threatens the survival of certain skilled workers and carries the possibility of making those jobs disappear.

On the other hand, in areas requiring refined aesthetics, such as renewals, high-value-added human labor is expected to intensify.

As AI performs a significant portion of work, the relationship between team leaders and team members has faced fundamental change.

Team members assess the value of the 'experience and career' provided by managers, recognize the limited nature of the relationship, and tend to focus on immediate results. This change is leading to the reduction of middle managers' roles and the reorganization of hierarchical structures within organizations.

In the past, seniority and years of service within an organization led to rewards, but now the tendency to prioritize expertise in a specific role over experience in rotational positions has strengthened.

The era of expertise has arrived, in which one does a single type of work in many places, and accordingly, the standards for choosing a job and individuals' values are changing.

The era of doing many kinds of work in one place is passing, and it is now shifting to an era of doing one kind of work in many places.

Through the IMF foreign exchange crisis and the 2008 global financial crisis, the myth of the lifelong workplace was broken, and some views hold that the concept itself is only about 80 years old.

In Korea, companies borrowed it as they built large-scale organizations in the 1980s, but the myth of the lifelong workplace was broken through the IMF foreign exchange crisis and the 2008 global financial crisis.

Anxiety has spread in which even TOEIC scores in the 900s feel insufficient for getting a job at a large company.

As demands increase for additional certifications that did not exist in the past, such as Level 3 in Chinese characters and Level 2 in distribution management, job competition is intensifying.

This is similar to a 'game of stealing chairs' competing for a fixed number of seats, and correlations with rising social costs, reduced hiring, and population decline are working in combination.

In the 2020s, the spread of online services such as Baemin and Coupang caused demand for IT developers to surge.

IT-related occupations, referred to as 'Naekarakubaedang,' emerged as coveted targets, and because of exceptional treatment such as signing bonuses, the phenomenon of salary increases when changing jobs became clear.

As in the case of Andrej Karpathy, AI models directly generate coding results, raising doubts about the effectiveness of acquiring existing coding skills.

There is a prospect that demand for philosophy majors who deal with comprehensive thinking and fundamental questions will increase more than technical coding ability.

New foundation models have reached the level where AI derives coding as an output.

In future society, problem-solving ability and creative thinking emerge as even more core competencies.

Rather than blindly following trending jobs, an attitude of understanding the reason and cause behind their creation is required.

Careers must be prepared with a long breath, not short-term results of a month or two, and answers about changes caused by AI adoption should be sought in the causes of social trends rather than individual choices.

This means that to predict the future, efforts are needed to understand the fundamental drivers of change rather than focusing only on superficial phenomena.

Predictions of promising future jobs from 10 years ago show a gap with the present, and the reality that back dancers and pro gamers, which children dreamed of 25 years ago, are now in the spotlight proves this.

Parents' experience is limited, so we should not suppress children's dreams and must recognize that the future is ultimately an area children will create for themselves.

It was recommended to exclude, rather than include, occupations recommended by the parent generation from the list.

This is because there is a risk of projecting the unfairness and missed opportunities experienced by parents onto the next generation, and it suggests that children need the wisdom to listen to their parents' advice while exploring their own path.

As webtoons and web novels became sources of global IP, writers' economic achievements greatly increased.

Pro gamers have become leading figures in an official sport, enhancing national prestige and gaining social power. As in the case of player Faker, this has become an era in which gaming is recognized as professional achievement, unlike in the past.

This phenomenon shows that a new industrial ecosystem has formed in which individuals can gain great economic achievement and fame without being tied to an organization.

Companies attempt workforce reductions to survive competition, and as AI adoption lowers the need for organizational members, employment forms are becoming fragmented.

Writer Song Gil-young explained that the large-scale employment structure of the past is collapsing and the era is changing to one in which individuals must fend for themselves.

This leads to the analysis that the moment organizations try to shrink, individuals will be scattered from large organizations.

The existing concept of a lifelong workplace was protection only until one's 40s or 50s, considering retirement age and remaining life, but as life expectancy lengthens, a situation has arisen in which people must manage more than 60 years after age 60 on their own.

Since organizations cannot take care of an individual's entire life, awareness is spreading that individuals must build their own capabilities and prepare for the next stage.

Companies such as Meta turn all employee work processes, including keyboard input and mouse clicks, into data and use it for machine learning. As the entire process of work performed by an individual is recorded and learned, some jobs are replaced by machines.

As work efficiency progresses, the replaceability of people in specific roles increases and individuals' bargaining power within the organization deteriorates. The datafication of work results in transplanting an individual's skills and know-how into machines.