About the ability to identify problems, I have also written a related article before (The Future Workplace: Problem-Solving Skills Are Not Enough, the Ability to Identify Problems Is Important). However, at the beginning of this year, the astonishing performance of ChatGPT and other generative AI models has prompted me to reconsider the impact of new technologies on people's work and lives. In doing so, I have realized that AI reinforces the previous conclusion: the ability to identify and define problems is an indispensable skill for the future, yet it is also a skill that we currently lack the most.
The availability of solvable "problems" has ironically become scarce, and problems need to be uncovered and explored：
Firstly, the increasing importance of problem discovery lies in the scarcity of problems themselves. The era where opportunities were abundant and focusing on one thing could lead to success has passed. Prior to the year 2000, Taiwan's economy was in its take-off stage, and people's living standards were relatively low. As a result, ambitious entrepreneurs could specialize in a specific product or industry, solve production capacity issues, and lower costs to achieve success. However, as people's living standards improved and market demands gradually saturated, merely solving operational problems or improving efficiency was no longer sufficient to generate profits.
This phenomenon is not unique to Taiwan. If we look at the data, in all developed countries, the economic challenge is mostly "insufficient demand" rather than "insufficient supply." For example, in Japan, as early as the 1980s, people's basic needs were already met, leading to a decline in consumer spending and an inability to stimulate domestic demand. They had to rely on loose monetary policies and financial measures to stimulate the economy. Although Japan offered a wide variety of products, none of them were able to significantly boost the country's economy. In contrast, this situation is reversed in developing countries. Before the pandemic, China, with its young market and increasing wealth, had a strong demand for goods. Many companies were eager to sell their products in China. The former focuses on how to create demand (discovering and defining problems), while the latter focuses on how to meet unmet needs (solving existing problems).
This indicates that as the economy develops to a certain extent, the market gradually shifts from supply constraints to demand constraints. Taiwan is also gradually following in Japan's footsteps, where companies must shift their focus from mass production to marketing, high-level customization, or niche-oriented products. Successful companies that tap into new market opportunities can redefine problems and address issues that people have not previously considered. For example, Tesla redefined automobiles by shifting from reliance on fossil fuels to electric power consumption.
AI reduces the importance of problem-solving skills:
Next, let's consider the factors related to AI.
In the past, the advantage of knowledge workers lay in tasks that required human judgment and dealt with less coherent information, which computers were unable to handle. Therefore, there was a reliance on human-machine collaboration to complete tasks such as graphic design, creative writing, report writing, and other white-collar jobs. Previously, AI was not mature enough and lacked the ability to handle these creative and imaginative tasks. However, with the increasing computational power of computers, machine learning can identify patterns in these creative tasks, thus replacing human labor. ChatGPT is a prime example of this. In fact, there are some tasks that AI can even perform better than humans.
Looking at it from a different perspective, what knowledge workers spend the most time on is acquiring information from Google, organizing and synthesizing it, and producing reports or works based on that information. Take stock analysts or market researchers as examples; much of their work involves synthesizing and presenting information. However, if ChatGPT or Google Bard can gather all the data and organize it within seconds, the value of these white-collar workers diminishes significantly.
Solution: Tackle problems that AI cannot solve:
While AI possesses powerful capabilities, it is ultimately generated through learning from existing data. The problems it can solve are those for which answers already exist (perhaps hidden somewhere on Google), and it does not inherently explore new problems and seek their solutions. Furthermore, AI always addresses human problems and satisfies human needs. Without humans providing instructions on what problems to solve, AI cannot fulfill its value. Therefore, the value of humans lies in how they utilize AI to solve unresolved problems or unmet needs.
The above statement might seem abstract, so let's consider an example: Imagine that we live in a time before automobiles were invented, and only horse-drawn carriages exist, but we have ChatGPT and the internet. If we want to solve transportation issues, the answers provided by ChatGPT might focus on improving the efficiency of horse-drawn carriages. However, if Henry Ford conceives the abstract concept of an automobile and instructs ChatGPT to gather all the scientific and engineering knowledge, the necessary talent, and other resources required to materialize this concept, we would quickly develop a new automobile. This illustrates the value of AI—it can answer questions with existing solutions, but it is humans who can take those answers and create new value.
Conclusion: The successful individuals of the future will be those who can pose questions and utilize AI.
The powerful capabilities of AI are evident, and while many jobs may be replaced, it also frees up human intellectual capacity. If we only focus on how to enhance our work abilities and directly compete with AI, we are bound to lose. What we should do is to improve our powers of observation, gain insightful analysis of things, rethink the value of humans, events, and objects, and generate new ideas to collaborate with AI. This is the right path forward. However, as mentioned earlier, achieving this goal is more challenging in developed countries. Therefore, people should cultivate their abilities in this regard even more.
References:
Photo from Andrew Neel: https://www.pexels.com/zh-tw/photo/15863066/
Comments