Series Order
Part 1 | What Should Humans Do When AI Expands the Limits of Thought?
By Im Byung-min (IBM), Columnist
Having worked in information technology for nearly 50 years, I have watched successive waves of technology expand what people can do. Two years before ChatGPT emerged, I began explaining the difference between human and artificial intelligence through the analogy of travel speed. If human thought and information processing move at 15 kilometers per hour, AI can be compared to an aircraft traveling at 800 kilometers per hour.
An aircraft can cover in minutes a distance that would take a person all day to reach on foot. That speed does not make the aircraft greater than the person who built and operates it. It remains a tool whose destination and route are determined by people. AI likewise performs within the problem, information and instructions given to it.
People absorb information through experience, reflect on it and make judgments. AI can scan vast amounts of material, compare patterns and reorganize information into new forms within a short period. The figures of 15 and 800 kilometers per hour are not scientific measurements. They illustrate the widening difference between the ways humans and AI process information.
The central issue is how that speed is used. An aircraft flying in the wrong direction moves away from its destination faster, not slower. If the goal or premise given to AI is flawed, the system can amplify the error and produce large volumes of plausible but misleading output. Greater speed therefore increases the importance of setting direction and checking progress along the way.
As Output Becomes Abundant, Judgment Becomes Scarce
People do not need to compete with AI in calculation, information retrieval or large-scale classification. AI can efficiently handle document summaries, translations, preliminary analysis, first drafts and other repetitive tasks. The human role lies in deciding which questions deserve attention, identifying the underlying problem and judging which option best serves the intended purpose and values.
Consider someone preparing to launch a business. Market research, competitor analysis, customer assessment and business-plan preparation once required considerable time and labor. AI can organize relevant information, compare market trends, examine several business models and identify potential risks. Preparatory work that previously took weeks can sometimes be reduced to days or hours.
A rapidly generated market analysis, however, does not guarantee a viable business. The underlying data may be outdated, geographically narrow or disconnected from how customers behave in practice. Statistics may also fail to capture local conditions and unusual events encountered in the field. AI can produce options, but people must decide which problem to solve, whom the business should serve and what level of risk is acceptable.
As AI develops, the cost of producing content continues to fall. Reports, images, software code and business ideas can be generated rapidly and in large quantities. Organizational performance will increasingly depend on the ability to select useful results, reject weak ones and explain the reasons for those decisions. When production becomes widely accessible, verification and judgment become the scarcer capabilities.
Human oversight cannot be reduced to a final approval step. People must examine the assumptions behind an AI-generated answer, verify its sources and factual accuracy, and identify the stakeholders or consequences the system may have overlooked. In areas such as law, medicine, finance and journalism, the consequences of error can be substantial. Accountability for the result matters more than the speed at which it was produced.
The same shift is taking place in education. A student who submits an answer produced by AI may complete an assignment quickly while bypassing the process of reasoning. A student who first develops an argument and then asks AI to challenge it can use the technology to broaden the scope of thought.
Students can ask, “Where is my argument logically weak?” “How would someone with the opposing view approach this issue?” “Which questions have I overlooked?” or “How has a similar problem been examined in another field?” Used this way, AI becomes a mirror that reveals gaps in thinking. The ability to formulate strong questions and evaluate the answers will become increasingly important in education.
In the workplace, AI can assist with drafting documents, summarizing meetings, classifying materials, analyzing data, translating content and managing schedules. People can then spend more time communicating with customers, collaborating with colleagues and setting priorities when interests conflict. Strategy, negotiation and decisions carrying real responsibility remain grounded in human judgment.
There is an important condition. Time saved by AI does not automatically become time for deeper thought or more creative work. If an organization simply demands more reports, meetings and outputs, AI may increase the volume of work without improving its quality. The value of AI adoption should therefore be measured not only by tasks completed, but also by better decisions, fewer errors, stronger customer engagement and more time spent identifying new problems.
How Should We Use the Time AI Gives Back?
One of AI’s greatest contributions may be its ability to return time to people. Human limitations involve more than knowledge or capability. People also lack sufficient time to reflect. When most of the day is consumed by repetitive work, there is little room to question, observe or develop new ideas.
AI can process routine work and create space for people to examine root causes and consider longer-term consequences. Whether that space is used well depends on individuals and organizations. Productivity gains acquire lasting value only when saved time is redirected toward more thoughtful work and better decisions.
Combining human experience with AI’s computational capacity is essential. People directly experience joy and loss, success and failure, conflict in relationships and the exceptional circumstances that arise in the field. AI can identify patterns across vast collections of data, but it does not experience what those findings mean in a person’s life or within an organization. Humans must provide context and decide what significance should be attached to an analysis.
The relationship can also be understood through the analogy of a car. The person sets the destination, while AI serves as a powerful engine and navigation system. It can calculate alternative routes, assess traffic conditions and recommend a faster path. The person must still determine whether the route is safe, who should travel with them and whether the destination is worth reaching.
AI will continue to understand more forms of data, perform multiple tasks simultaneously and collaborate with people more naturally. The capabilities required of humans will change in response. The ability to memorize large amounts of information will matter less than the ability to define a problem precisely, test AI-generated results and make responsible decisions when values and interests conflict.
If AI is an aircraft traveling at 800 kilometers per hour, humans are more than its pilots. They design the route, select the destination and decide whether the journey should continue. They must also know when to slow down, change course or reconsider the departure itself.
As AI expands the limits of human thought, human work does not disappear. Its center of gravity shifts from producing answers to defining problems, verifying results, making choices and accepting responsibility. The decisive measure of AI will not be how quickly it generates an answer. It will be whether people can use that answer to see more accurately and decide more responsibly.
