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UC Berkeley professor Joshua Blumenstock uses machine learning and AI on household surveys to optimize targeting of antipoverty programs and estimate the cost to end extreme global poverty.
A perspective on how society might transition to a post-scarcity state, likely driven by AI and automation.
Generative AI is reshaping the economics of outsourcing by automating routine tasks, reducing the labor cost advantage that drove offshore outsourcing for decades.
A hypothetical scenario shows how AI-driven efficiency in a company leads to layoffs, but also creates new competition that rehires workers, ultimately benefiting the economy.
This paper establishes a theoretical connection between market competitiveness and the P versus NP problem, arguing that competitive markets exist if and only if P ≠ NP.
The article discusses how a key signal that has been driving the AI trade is weakening, potentially impacting market expectations for AI-related stocks.
AI-research-feedback is an academic paper review skill for Claude Code. It checks grammar, coherence, formulas, figures, and argument flaws through six parallel agents, supports specifying journals to simulate reviewers, and finally generates a structured review report.
The article explores the concept of Engel's pause and its implications for the AI-driven economy.
The article explores how AI could drastically reduce transaction costs, enabling a single founder to build a billion-dollar company without a large team, drawing on Ronald Coase's theory of the firm.
This paper uses AT&T's exclusive iPhone monopoly from 2007-2011 as a natural experiment to estimate the causal effect of iPhone ownership on birth rates, finding evidence that the iPhone may act as a form of birth control.
According to a study, firms that adopt AI see a 10.2% increase in headcount over two years, suggesting AI creates jobs rather than eliminates them.
A curated GitHub collection of AI skills for economists, organized by workflow stage to automate research tasks like data cleaning and econometrics, using open-source formats.
Professor Roberto Serrano at Brown University detected at least 50 students cheating using AI on a midterm exam, sparking a debate about academic integrity in higher education.
Clement Delangue warns that the biggest risk in AI is the concentration of power, capabilities, and wealth among a few trillion-dollar companies and governments, calling for more rebels and alliances like USV's.
The article presents data showing a rise in solopreneurs reaching high income thresholds, with AI filling capability gaps that previously required hiring.
A tweet asks how to improve public perception of AI and post-labor economics, noting that many people associate it with dystopia rather than a future where normal people benefit.
Introduces EconEvals, an open-source evaluation suite that measures AI capabilities and predicts job disruption across the US labor economy, addressing the mismatch between benchmarking focus (math/coding) and actual job distribution.
The Bank of Korea released a report finding that AI saves workers about one hour per week, but this does not translate into higher productivity or profits; instead, the time saved leads to more reporting and no extra pay.
Chad Jones announced he will be on leave from Stanford starting June 30 to join the Anthropic Institute, where he will continue research on AI and economic futures.
In an interview with Ars Technica, author Cory Doctorow discusses his new book 'The Reverse Centaur's Guide to Life After AI', critiquing the AI bubble and advocating for resistance against AI hype.