Incentives, Rationality, and Game-Theoretic Thinking: A Dialogue with Nobel Laureate Robert Aumann

In 2020, I represented Zhejiang University International Business School (ZIBS) in its "Meet the Author" lecture series, interviewing Professor Robert J. Aumann, the 2005 Nobel Memorial Prize in Economic Sciences laureate at the Hebrew University. This dialogue spanning Israel and China revolved around three central themes — "incentives," "rationality," and "artificial intelligence." With his signature gift for making the complex accessible, Professor Aumann revealed the most fundamental thinking frameworks of economics and game theory — insights that continue to profoundly shape how I think about policy design, global governance, and educational innovation.

I. "Incentives Are at the Heart of Everything" — From the Failure of Socialism to the Wisdom of Splitting Chocolate

When I asked Professor Aumann to summarize the essence of economics and game theory in a single word, he answered without hesitation: "Incentives." This ninety-year-old scholar then proceeded to illustrate this abstract academic concept with two vivid examples.

The first example was the rise and fall of socialism. Professor Aumann candidly acknowledged that the socialist ideal of "from each according to his ability, to each according to his needs" is inherently beautiful — "I fully agree with this idea; it is beautiful." But the problem is that it does not work. When everyone knows the state will meet their needs, the incentive to work hard disappears. He noted that China shifted toward a market economy in 1979, a full decade ahead of the Soviet Union — "The Chinese were smarter." This remark drew knowing smiles from the 22,000 online viewers, but the underlying economic logic is thought-provoking: a market economy works precisely because it provides the correct incentive structure.

The second example was even more elegant. Professor Aumann recalled how, during his childhood, his mother dividing chocolate between him and his brother would invariably spark disputes — "Mine is smaller!" So his mother invented an ingenious mechanism: the younger brother (Aumann himself) would cut the chocolate, while the older brother had first choice. This way, the cutter had every incentive to divide as evenly as possible, and the chooser had no grounds for complaint.

"My mother was a game theorist," Professor Aumann said with a laugh, "and this was before game theory had even been formally published."

This seemingly mundane family story is in fact a precise demonstration of the core logic of mechanism design — good institutions do not rely on moral constraints but rather on carefully designed incentive structures that enable each participant, in pursuing their own interests, to naturally arrive at fair outcomes. This is precisely the core contribution for which the 2020 Nobel Memorial Prize in Economic Sciences was awarded to Paul Milgrom and Robert Wilson (both close friends of Professor Aumann) — using incentive mechanisms to design more optimized auction systems.^[1]

II. Redefining "Rationality" — From Black Cat Superstitions to the Logic of War

The most striking moment in our dialogue came when Professor Aumann redefined "rationality." He stated explicitly that rationality in economics is not what most people understand as "scientific thinking" or "logical reasoning," but rather: "Doing the best you can to achieve your objectives, given the information you have."

To illustrate the profundity of this definition, he cited an excellent case from one of his students: a person who sees a black cat cross their path and spits to ward off bad luck. By the commonsense definition, this is obviously irrational superstitious behavior. But by the economic definition, this is entirely rational — because the person genuinely believes that black cats bring bad luck and that spitting can dispel it. They are taking the action "most beneficial to their objectives" based on "the information they possess."

The revolutionary nature of this definition lies in liberating "rationality" from value judgments and transforming it into a purely analytical behavioral tool. Under this framework, Professor Aumann further demonstrated that three seemingly "irrational" phenomena are in fact "rational":

1. Gender discrimination can be rational — when employers make hiring decisions based on statistical information they possess (for example, that young women may leave work due to pregnancy), this is rational from an economic perspective. However, Professor Aumann emphasized that the solution is not to deny this rationality, but to change the information environment and incentive structure so that the "rational basis" for discrimination ceases to exist.
2. Strikes can be rational — he used his own experience of a faculty strike at Hebrew University as an example. When the strike continued until mid-February and faced the crisis of losing the entire academic year, the professors voted by an overwhelming majority (approximately 480 to 6) to continue striking. Two days later, the university administration capitulated completely. "The function of a strike is to demonstrate your side's resolve to the other party," Professor Aumann explained. "This resolve cannot be conveyed through words — it can only be demonstrated through action."
3. War can be rational — this was the most powerful passage in the entire dialogue. Professor Aumann used the Korean War as an example: North Korea attacked because the United States had failed to clearly signal that it would defend South Korea, leading North Korea to "rationally" conclude that an invasion would meet no resistance. America's military counter-intervention was equally rational, as losing South Korea would have produced a domino effect in the Cold War.

He then offered a deeper analysis using the Munich Agreement before World War II: in 1938, British Prime Minister Chamberlain's appeasement of Hitler led Hitler to "rationally" infer that the West would yield to whatever demands he made. Therefore, invading Poland in 1939 was a perfectly rational decision for Hitler. "I think it was not Hitler who brought about World War II, but Chamberlain — it was his capitulation in 1938 that led to the catastrophe."

When Britain and France finally declared war on Germany, Hitler angrily told his Foreign Minister Ribbentrop: "They cheated me at Munich!" — he was genuinely surprised. This historical case perfectly illustrates Professor Aumann's core argument: most wars are not irrational madness, but the tragic consequences of information asymmetry and failed signaling.^[2]

III. Artificial Intelligence and Rational Decision-Making: Information Quality Determines Decision Quality

In the third segment of our dialogue, I steered the conversation toward artificial intelligence — after all, Hangzhou, where Zhejiang University is located, is the headquarters of Alibaba and Ant Group, and AI applications have permeated every corner of urban life. Professor Aumann's response was both cautious and forward-looking.

He began by using the breakthrough of Go AI as an entry point, elucidating the fundamental difference between deep learning and traditional algorithms: traditional chess programs evaluate the theoretical value of each move through "exhaustive search"; AlphaGo's deep learning, by contrast, "gropes its way" toward optimal strategies through vast quantities of real game experience — "You have no idea why it works, but it works."^[3]

Yet Professor Aumann's most profound insight about AI lay not in AI's capabilities per se, but in its logical connection to the definition of "rationality." He said:

"Recall my definition of rationality — doing the best you can to achieve your objectives, given the information you have. Then perhaps AI's greatest value lies not in making decisions for you, but in dramatically improving the quality of your information."

In other words, if the quality of rational decisions depends on information quality, and AI can break through the limits of human cognition to provide more comprehensive and accurate information, then AI can fundamentally elevate the degree of rationality in human decision-making. Using the black cat superstition as an example: "If you use AI, it will tell you — first, black cats do not bring bad luck; second, spitting does nothing to help. Then you can make truly rational decisions based on better information."

This analysis was profoundly illuminating for me. It implies that in the domains of policy design and global governance, AI's core value lies not in replacing human judgment, but in eliminating information asymmetry — and information asymmetry, as Professor Aumann demonstrated, is precisely the root cause of conflict and war.^[4]

IV. Advice for Young People: Do What You Truly Love

As our dialogue drew to a close — it was 2020, the height of the COVID-19 pandemic — I asked Professor Aumann on behalf of the audience: in this era of profound uncertainty, what advice would you give young people facing the future?

This nonagenarian scholar, who had lived through World War II, the Cold War, Middle Eastern conflicts, and multiple global financial crises, offered an answer that was both simple and profound:

"Do what you like. Not for the money, not because of your parents' expectations, not because of your teachers' guidance — but because you genuinely like it. Because when you like something, you do it well; and when you do it well, you like it even more."

He also offered a well-intentioned yet pointed observation about China's academic development: "Based on my more than ten visits to China, China excels at engineering and applied sciences, but invests less in fundamental science." He encouraged China's young people to devote more energy to basic scientific research — the kind of purely academic exploration that appears to have no practical application and cannot directly generate income. "Don't worry about whether what you do will improve people's lives — it only needs to interest you. That is enough."

This counsel perfectly echoes Professor Aumann's own academic career. The game theory research to which he devoted his life was regarded by many as an abstract mathematical exercise for its first several decades, until its applied value in auction design, conflict resolution, mechanism design, and other fields gradually became apparent, and the world came to recognize the far-reaching impact of basic research.^[5]

V. Reflections: The Lasting Inspiration of a Single Conversation

More than four years have passed since my conversation with Professor Aumann, yet its insights continue to ferment in my academic research and policy practice.

In policy design, Professor Aumann's exposition on incentives deepened my understanding that good policy relies not on prohibitions and penalties, but on carefully designed incentive structures that lead market participants to "voluntarily" make choices aligned with the public interest. This insight directly influenced my subsequent research orientation in fintech regulation — shifting from "command and control" toward incentive-compatible institutional designs such as "regulatory sandboxes."

In global governance, his "rational" analysis of war — particularly how failed signaling leads to catastrophic conflict — provides an extraordinarily penetrating analytical framework for understanding the current international landscape. In an era of escalating geopolitical tensions, Professor Aumann's theory reminds us that the key to avoiding conflict lies not in assuming the other side is "irrational," but in ensuring that both sides' intentions are communicated clearly and credibly.^[6]

In educational philosophy, his counsel to "do what you love" and "value basic science" aligns perfectly with the educational innovation vision I have long championed. Whether in building metaverse campuses or designing Cambridge-Zhejiang executive education programs, I have always believed that the highest purpose of education is not to impart skills but to ignite curiosity — precisely the driving force behind Professor Aumann's passion for sharing knowledge at the age of ninety.

When our dialogue concluded, over 22,000 people were watching simultaneously online — itself a vivid case study in "incentives." While COVID-19 severed physical movement, it created unprecedented digital connectivity incentives, enabling an academic dialogue between Israel and China to reach an audience that would previously have been unimaginable. As Professor Aumann put it: "This is a silver lining of the pandemic."