72 | César Hidalgo on Information in Societies, Economies, and the Universe

Episode Summary

Executive Summary: Sean Carroll and Cesar Hidalgo explore information as a physical, biological, and social organizing principle: order that can be created, preserved, and computed on. Hidalgo argues that life, cities, firms, and economies grow through collective learning, tacit knowledge, and communication technologies, which reshape wealth, inequality, and fame. The conversation links physics, evolution, trade, and modern data tools into one framework.

Main Topics: Information as order beyond matter and energy (Priority: 5/5): Hidalgo defines information as the arrangement of things—distinct from matter and motion—and distinguishes raw Shannon information from meaningful communication. He uses DNA and deck-of-cards analogies to show that sequence/order can change function without changing physical quantity. Life, entropy, and dissipative structure (Priority: 5/5): The discussion uses Prigogine’s far-from-equilibrium systems to explain how complexity arises and persists on Earth. Life is presented as an energy-consuming, information-preserving process sustained by low-entropy flows, stable molecules, and path dependence. Knowledge, computation, and collective learning (Priority: 5/5): Hidalgo separates information (encoded structure) from knowledge (the ability to make/transform it), arguing that computation is the capacity to turn one configuration into another. Teams, firms, cities, and nations scale by accumulating collective learning and division of knowledge. Economic complexity, trade, and tacit knowledge (Priority: 5/5): Economies differ by how much knowledge is embedded in products and industries. Complex goods require many specialized contributors and tacit know-how that is difficult to move, explaining why knowledge clusters in places and why some regions are more competitive than others. Communication technologies as historical inflection points (Priority: 4/5): Hidalgo frames major historical eras around communication tech—language, writing, printing, film/radio, television, and internet/TikTok—because each changes how knowledge is created, diffused, monetized, and remembered. He emphasizes that new media often first look trivial before becoming transformative. Data visualization, measurement, and urban perception (Priority: 4/5): Hidalgo describes building platforms such as the Observatory of Economic Complexity and Data USA to integrate many datasets into stories and visualizations. He also explains research using crowdsourced and computer-vision-based ratings of street images to measure perceived safety and urban activity. Inequality, cities, and policy (Priority: 4/5): The conversation links economic complexity to equality: complex economies tend to be more equal at the country level, while within-country city concentration can raise inequality. Hidalgo argues for building infrastructure and dense, livable cities that can accommodate more people and knowledge.

Key Arguments: Information is not just meaning; in a technical sense it is arrangement/order, like DNA sequence or a shuffled deck. Entropy increases toward equilibrium, but life and technology persist by consuming energy to maintain order and complexity. Knowledge is different from encoded information: it is the experiential ability to make, recombine, and reproduce things. Complex products and industries require distributed tacit knowledge that cannot be easily codified or relocated. Economic development is driven by collective learning at nested scales: individuals form teams, teams form organizations, organizations form cities and industries. Communication technologies reshape both economic structure and collective memory by making certain kinds of knowledge cheaper to store, transmit, and monetize. Knowledge clusters are hard to create from scratch because tacit know-how diffuses slowly; migration is a major channel for importing it. More complex economies tend to be less unequal across countries, but within countries larger cities can appear more unequal because they attract talent and migrants. Modern urban growth requires infrastructure that lets cities absorb more people without making commutes and housing unaffordable. Data platforms can turn fragmented public/private datasets into accessible narratives that help governments, researchers, and businesses make better decisions.

Data Points: Years working on economics-related topics: 14–15 years - Hidalgo says he never earned an economics degree but has worked on economics-related topics for this long. Universities/cities platform scope in Data USA: 70,000 census designated places - He says Data USA provides profiles for nearly every U.S. census designated place. Visualizations per profile: More than 70 - Each place profile on Data USA includes dozens of visualizations and generated text. Website traffic: Over 1 million people per month - Hidalgo says the online properties receive this many monthly visitors. Academic share of Data USA users: 35–40% - Share of visitors who are academics, including students and professors. Street image dataset size: 4,000 images rated by over 100,000 people - Place Pulse crowdsourcing study of urban perception. Manhattan street segments: About 80,000 - Used to explain why crowdsourcing alone was too slow for citywide perception mapping. Language translation dataset: Over 2 million book translations - Used to build the global language network. Biographies dataset: Over 70,000 famous biographies - Used to study how communication technology changed collective memory and fame. Global PhD migration share to the U.S.: About 50% - Hidalgo says roughly half of globally migrating PhDs go to the United States. Migration rate without college degree: About 1% - From Bill Kerr’s global talent discussion. Migration rate with college degree: About 5% - Used to show migration is strongly skewed toward the educated. Migration rate for inventors with patents: About 10% - Illustrates increasing mobility with talent/achievement. Migration rate for Nobel Prize winners: About 31% - Shows extreme global concentration of top talent. Share of U.S. Nobel Prize winners since the 1970s who are immigrants: 60%+ - Hidalgo notes a majority are foreign-born. Printing press printer density: Stabilized after about 50 years - Cited as evidence of rapid commercialization of printing in Europe. Ecuador Yachay budget: $1 billion - Government attempt to build a science city and technology hub. Yachay share of GDP: 1% of GDP - Hidalgo emphasizes the scale of the investment for Ecuador. Yachay student count: About 1,000 - Used to illustrate extreme cost per student and the failure to recreate knowledge ecosystems by fiat. Per-student implied cost at Yachay: About $1 million per student - Calculated from the stated budget and student count. Music monetization window: Short historical window - Hidalgo argues musicians could monetize recordings only during the era when music was trapped in physical media.

Pivotal Quotes: "I focus on collective learning." — Cesar Hidalgo: He gives the 30,000-foot description of his research agenda across economics, data, and innovation. "Information as those sequences." — Cesar Hidalgo: He defines information in the technical sense as ordering/sequence rather than meaning. "The ability to make." — Cesar Hidalgo: He distinguishes knowledge from information, defining knowledge as the capacity to transform encoded instructions into products or outcomes.

Implications: The episode suggests that future prosperity will depend on institutions that attract talent, enable tacit knowledge transfer, and build dense, inclusive cities. It also implies that new media and data tools will keep reshaping work, fame, politics, and how societies remember themselves.