Is A.I. Actually a Bubble? The narrative of boom and bust is familiar--but also out of step with the possibilities of a new technology. Over the past few months, I've introduced artificial intelligence into the hobby life of my seven-year-old son, Peter. On Saturdays, he takes a coding class, in which he recently made a version of rock-paper-scissors, and he really wants to make more sophisticated games at home. I gave ChatGPT and Claude a sense of his skill level, and they instantaneously suggested next steps. Claude proposed trying to recreate Pong in Scratch, a coding environment for kids.

Artificial intelligence is simultaneously transforming the production function of human capital in schools and the return to skills in the labor market. We develop a theoretical model to analyze the potential for misallocation when these two forces are considered in isolation. We study an educational planner who observes AI's immediate productivity benefits in teaching specific skills but fails to fully internalize the technology's future wage-suppressing effects on those same skills. Motivated by a pre-registered pilot study suggesting a positive correlation between a skill's "teachability" by AI and its vulnerability to automation, we show that this information friction leads to a systematic skill mismatch. The planner over-invests in skills destined for obsolescence, a distortion that increases monotonically with AI prevalence. Extensions demonstrate that this mismatch is exacerbated by the neglect of unpriced non-cognitive skills and by the endogenous over-adoption of educational technology. Our findings caution that policies promoting AI in education, if not paired with forward-looking labor market signals, may paradoxically undermine students' long-term human capital, such as by crowding out skills like persistence that are forged through intellectual struggle.

This paper examines how institutional belonging shapes long-term development by comparing Spain and Uruguay, two small democracies with similar historical endowments whose trajectories diverged sharply after the 1960s. While Spain integrated into dense European institutional architectures, Uruguay remained embedded within the Latin American governance regime, characterized by weaker coordination and lower institutional coherence. To assess how alternative institutional embeddings could have altered these paths, the study develops a generative counterfactual framework grounded in economic complexity, institutional path dependence, and a Wasserstein GAN trained on data from 1960-2020. The resulting Expected Developmental Shift (EDS) quantifies structural gains or losses from hypothetical re-embedding in different institutional ecosystems. Counterfactual simulations indicate that Spain would have experienced significant developmental decline under a Latin American configuration, while Uruguay would have achieved higher complexity and resilience within a European regime. These findings suggest that development is not solely determined by domestic reforms but emerges from a country's structural position within transnational institutional networks.

Human capital (HC) is increasingly important to corporate value creation. Unlike other assets, however, HC is not currently subject to well-defined measurement or disclosure rules. We use a machine learning algorithm (word2vec) trained on a confirmed set of HC disclosures to develop a comprehensive list of HC-related keywords classified into five subcategories (DEI; health and safety; labor relations and culture; compensation and benefits; and demographics and other) that capture the multidimensional nature of HC management. We share our lexicon, corporate HC disclosures, and the Python code used to develop the lexicon, and we provide detailed examples of using our data and code, including for fine-tuning a BERT model. Researchers can use our HC lexicon (or modify the code to capture another construct of interest) with their samples of corporate communications to address pertinent HC questions. We close with a discussion of future research opportunities related to HC management and disclosure.

Generative AI is rapidly reshaping creative work, raising critical questions about its beneficiaries and societal implications. This study challenges prevailing assumptions by exploring how generative AI interacts with diverse forms of human capital in creative tasks. Through two random controlled experiments in flash fiction writing and song composition, we uncover a paradox: while AI democratizes access to creative tools, it simultaneously amplifies cognitive inequalities. Our findings reveal that AI enhances general human capital (cognitive abilities and education) by facilitating adaptability and idea integration but diminishes the value of domain-specific expertise. We introduce a novel theoretical framework that merges human capital theory with the automation-augmentation perspective, offering a nuanced understanding of human-AI collaboration. This framework elucidates how AI shifts the locus of creative advantage from specialized expertise to broader cognitive adaptability. Contrary to the notion of AI as a universal equalizer, our work highlights its potential to exacerbate disparities in skill valuation, reshaping workplace hierarchies and redefining the nature of creativity in the AI era. These insights advance theories of human capital and automation while providing actionable guidance for organizations navigating AI integration amidst workforce inequalities.

INTRACOM TELECOM is a global telecommunication systems and solutions vendor operating for over 40 years in the market. The company innovates in the wireless access and transmission field, offers a competitive telco software solutions portfolio and combines its offerings with a complete range of professional services. Our mission is to shape the future through technology and we recognize that human capital is the key factor to achieve this in today's business environment. Our company's highly specialized and experienced personnel are pivotal to achieving demanding objectives and advancing the capabilities of the company to better serve its customers. Within this framework, we are looking for a highly-motivated " Big Data Engineer" to join INTRACOM TELECOM's Business Support Systems.

Human capital'--the economic value of our cognitive and noncognitive capacities--is our most important asset. According to recent World Bank estimates, the value of human capital globally amounts to 64 per cent of total capital, while in the advanced-country members of the Organisation for Economic Co-operation and Development it is typically worth four to six times as much as physical capital. Human capital is decisive not only for welfare but also for growth, social mobility and income distribution. Among these latter variables, the link between growth and inequality has been contentious in economic research. Three or four decades ago, the consensus in the profession was that inequality was beneficial for growth--indeed this was deemed so self-evident that empirical testing was unnecessary.

The debate on AI has focused mainly on its potential effect on employment. The impact on equality should not however be missed. 'Human capital'--the economic value of our cognitive and noncognitive capacities--is our most important asset. According to recent World Bank estimates, the value of human capital globally amounts to 64 per cent of total capital, while in the advanced-country members of the Organisation for Economic Co-operation and Development it is typically worth four to six times as much as physical capital. Human capital is decisive not only for welfare but also for growth, social mobility and income distribution.

With companies facing labor challenges and rising inflation across all industries, automation and robotics offer measurable relief, enabling increased productivity and a more efficient use of human capital. Two to three years ago, only about 5% of warehouses in the U.S. relied heavily on automation, a percentage that has not increased much to date. But with fewer available workers and increased costs, the business case for implementing these technologies to aid the available workforce has become all the more compelling. In non-automated facilities as large as one million square feet, 30% of a worker's time can be spent traveling from one area of the warehouse to another to perform assigned tasks. Cutting down on employee transit time can not only increase productivity and service levels, but also save money.

This article is part of our series that explores the business of artificial intelligence. Digital technologies, and at their forefront artificial intelligence, are triggering fundamental shifts in society, politics, education, economy, and other fundamental aspects of life. These changes provide opportunities for unprecedented growth across different sectors of the economy. But at the same time, they entail challenges that organizations must overcome before they can tap into their full potential. In a recent talk at an online conference organized by Stanford Human-Centered Artificial Intelligence (HAI), Stanford professor Erik Brynjolfsson discussed some of these opportunities and challenges.