New insights from Google’s AI & Economy ATLAS

Google AI 与经济 ATLAS 的最新洞察

New data visualizations make ATLAS data easier to explore and use, while new research provides insights on how scientists are using AI. 全新的数据可视化功能使 ATLAS 数据更易于探索和使用，同时最新的研究也为科学家如何使用人工智能提供了洞察。

How is AI being used by people every day, including in offices, labs, and creative studios around the world? Insights from Google’s AI & Economy ATLAS show how AI is actively reshaping global work. For example: 人工智能在世界各地的办公室、实验室和创意工作室中是如何被人们日常使用的？来自 Google AI 与经济 ATLAS 的洞察显示，人工智能正在积极重塑全球工作方式。例如：

India’s creative industry is using AI at a higher rate than the rest of the world, with arts, design, and media occupations making up 19% of work-related AI usage, 1.6 times the global average.
印度的创意产业使用人工智能的比例高于世界其他地区，艺术、设计和媒体职业占工作相关人工智能使用量的 19%，是全球平均水平的 1.6 倍。
The U.S. is leading in technical AI adoption, with computer and mathematical occupations accounting for 30% of work-related AI usage, double the share in the rest of the world.
美国在技术性人工智能应用方面处于领先地位，计算机和数学职业占工作相关人工智能使用量的 30%，是世界其他地区份额的两倍。

To make these insights and ATLAS’s millions of other global data points easier to explore, we’re launching a new interactive, open-access experience. You can look more closely at the rates different occupations are using AI, from electricians to purchasing managers, dive into the ways people are using AI at home, and explore the rate of AI adoption in countries around the world. 为了让这些洞察以及 ATLAS 中数以百万计的其他全球数据点更易于探索，我们推出了全新的交互式开放访问体验。您可以更深入地了解不同职业（从电工到采购经理）使用人工智能的比率，深入研究人们在家中使用人工智能的方式，并探索世界各国的人工智能应用率。

And new ATLAS-based research from Google, Google DeepMind, in collaboration with MIT FutureTech provides new insights how scientists are using AI in their work, including: 此外，由 Google、Google DeepMind 与麻省理工学院 FutureTech 合作开展的基于 ATLAS 的最新研究，为科学家如何在工作中利用人工智能提供了新的见解，包括：

Scientists are using AI at a higher rate than many other occupations; nearly half of surveyed scientists use some form of AI every day.
科学家使用人工智能的比例高于许多其他职业；近一半受访科学家每天都在使用某种形式的人工智能。
Both LLMs and specialized models are used widely for science, in mutually reinforcing ways.
大语言模型（LLMs）和专用模型都在科学领域得到广泛应用，并以相互促进的方式发挥作用。
Scientists report saving almost 7 hours a week with AI, freeing up time for more research. However, there are now bottlenecks further down the research production pipeline, creating a backlog of hypotheses.
科学家报告称，人工智能每周可为他们节省近 7 小时的时间，从而腾出更多时间进行研究。然而，研究生产流程的后续环节目前出现了瓶颈，导致了假设积压。

Which professions are using AI most, and where?

哪些职业最常使用人工智能，分布在哪里？

ATLAS data reveals how different professions around the globe are adopting AI, highlighting key regional trends and usage patterns: ATLAS 数据揭示了全球不同职业如何采用人工智能，并突显了关键的区域趋势和使用模式：

AI by occupation: In OECD countries, computer and mathematical and business and financial operations lead in AI usage. In non-OECD countries, office and administrative support, arts, design, entertainment, sports, and media, and educational instruction and library occupations take the top spots.
按职业划分的人工智能使用情况： 在经合组织（OECD）国家，计算机与数学以及商业与金融运营职业在人工智能使用方面处于领先地位。在非经合组织国家，办公室与行政支持、艺术、设计、娱乐、体育与媒体，以及教育教学与图书馆职业占据了首位。
Income level vs. adoption: While AI adoption generally correlates with a country’s income level, countries like Brazil and the UAE stand out with higher adoption rates than their GDP per capita would predict.
收入水平与应用率： 虽然人工智能的应用通常与一个国家的收入水平相关，但巴西和阿联酋等国表现突出，其应用率高于人均 GDP 所预期的水平。
AI for manual tasks: Usage for real-time equipment diagnostics and troubleshooting varies significantly by region. In Brazil and Germany, 7% of work AI usage goes toward manual tasks (1.4 times the global average), compared to 4% in Japan.
用于手动任务的人工智能： 用于实时设备诊断和故障排除的人工智能使用情况在不同地区差异显著。在巴西和德国，7% 的工作人工智能使用量用于手动任务（是全球平均水平的 1.4 倍），而日本这一比例为 4%。

How are scientists using AI?

科学家如何使用人工智能？

New research also highlights how scientists are using AI in their work. A new study from Google, Google DeepMind, and MIT FutureTech draws on ATLAS data. It’s an analysis of 2600 specialized AI models, and a survey of over 600 U.S. and U.K. scientists, all organized using a new taxonomy from MIT FutureTech that maps out what scientists do. 最新的研究还强调了科学家如何在工作中利用人工智能。这项由 Google、Google DeepMind 和麻省理工学院 FutureTech 共同开展的新研究利用了 ATLAS 数据。该研究分析了 2600 个专用人工智能模型，并对 600 多名美国和英国科学家进行了调查，所有数据均使用麻省理工学院 FutureTech 的新分类法进行整理，该分类法详细规划了科学家的工作内容。

According to the research, scientists are using AI at a higher rate than many other occupations, and nearly half use some form of AI every day. While scientists are using both specialized models and LLMs, they’re using them for different tasks. Usage of LLMs like Gemini is spread widely across scientific fields and task categories, while specialized AI models tend to be relatively more common in health and life sciences and in domain-specific data prediction, generation, and simulation tasks. 研究显示，科学家使用人工智能的比例高于许多其他职业，近一半的人每天都在使用某种形式的人工智能。虽然科学家同时使用专用模型和大语言模型，但他们将两者用于不同的任务。像 Gemini 这样的大语言模型在各个科学领域和任务类别中得到广泛应用，而专用人工智能模型则在健康与生命科学以及特定领域的预测、生成和模拟任务中相对更为常见。

Scientists are reporting significant time gains based on AI, with savings of just below seven hours a week, freeing up more time for research. But this may not immediately translate to new discoveries. The research also finds evidence of significant time spent validating AI outputs, an increased backlog of hypotheses yet to be tested, and bottlenecks emerging in areas like physical experimentation and clinical validation. In this way, science is similar to most other occupations: although AI offers significant potential to increase productivity, the large-scale impact on outputs and discoveries may require redesigning scientific processes and workflows to realize the potential of fast-evolving AI capabilities. 科学家报告称，人工智能带来了显著的时间收益，每周节省的时间略低于 7 小时，从而腾出了更多时间进行研究。但这可能不会立即转化为新的发现。研究还发现，科学家花费大量时间验证人工智能输出，导致待测试的假设积压增加，并在物理实验和临床验证等领域出现了瓶颈。从这个角度来看，科学研究与其他大多数职业并无二致：尽管人工智能在提高生产力方面具有巨大潜力，但要实现对产出和发现的大规模影响，可能需要重新设计科学流程和工作流，以充分发挥快速发展的人工智能能力。

What’s ahead?

未来展望

Many questions about the future of AI and the economy remain. ATLAS is a long-term research project, and we’ll work with partners in academia and elsewhere to identify new areas of research and deliver new insights that contribute to a better understanding of how AI is transforming the economy. 关于人工智能和经济的未来，仍有许多问题悬而未决。ATLAS 是一个长期研究项目，我们将与学术界及其他领域的合作伙伴共同努力，确定新的研究领域，并提供新的洞察，以帮助更好地理解人工智能如何改变经济。