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cover of episode Harnessing AI: safeguarding high-integrity data for climate action

Harnessing AI: safeguarding high-integrity data for climate action

2025/6/24
logo of podcast LSE: Public lectures and events

LSE: Public lectures and events
AI Deep Dive AI Chapters Transcript
People
A
Amy Fisher
C
Carmen Nuzzo
D
David McNeil
M
Melissa Chapman
S
Sylvan Lutz
Topics
Carmen Nuzzo: 作为TPI中心执行董事，我认为人工智能在气候行动中扮演着关键角色。我们中心致力于提供独立、严谨的数据，以评估公司、银行和国家在向低碳经济转型方面的进展。然而，在利用人工智能进行数据收集和分析时，必须高度关注数据完整性。我们正在进行一个试点项目，旨在自动化数据收集过程，但同时也强调区分好坏数据的重要性，确保为投资者提供可靠的信息，以便他们能够做出明智的投资决策并与投资实体进行有效互动。人工智能的应用必须审慎，以避免绿色清洗和信息误导，确保数据的质量和可靠性。 Sylvan Lutz: 作为LSE数据科学研究所的成员，我认为人工智能在气候变化领域既带来了机遇，也带来了挑战。一方面，人工智能可以帮助我们更快速、更高效地处理大量数据，从而加速净零转型。另一方面，我们也必须警惕人工智能可能带来的风险，如绿色清洗和环境成本。我们需要构建强大的AI管道，并确保在整个过程中进行严格的分析师验证，以保证数据的质量和可靠性。此外，我们还应该关注人工智能的能源消耗问题，并努力开发更节能的模型。重要的是，我们要认识到人工智能只是一种工具，其最终结果取决于我们如何使用它。我们有责任与人工智能合作，引导我们走向可持续的未来，而不是被市场激励所驱动。

Deep Dive

Chapters
This chapter introduces the LSE event, "Harnessing AI: Safeguarding High-Integrity Data for Climate Action," organized by the Transition Pathway Initiative Centre (TPI Centre) and the LSE Data Science Institute. It sets the stage by highlighting the event's focus on using AI to improve data collection for net-zero transition assessments while addressing concerns about data integrity and potential biases.
  • Event title: "Harnessing AI: Safeguarding High-Integrity Data for Climate Action"
  • Organizers: TPI Centre and LSE Data Science Institute
  • Event is part of London Climate Action Week
  • Focus on AI's role in accelerating decarbonization and addressing socioeconomic issues while mitigating risks of misinformation and greenwashing

Shownotes Transcript

Contributor(s): Dr Melissa Chapman, Amy Fisher, Sylvan Lutz, David McNeil, Professor Carmen Nuzzo | Artificial intelligence (AI) and machine learning (ML) are versatile technologies that have drastically lowered the cost of data production and analysis, potentially accelerating global decarbonisation and addressing socioeconomic issues. Nonetheless, concerns persist regarding their environmental impact and the risk of propagating low-quality information, especially with large language models (LLMs). Like any tool, AI can yield both positive and negative outcomes. As the demand for real-time data increases for the net-zero transition, the Transition Pathway Initiative Centre (TPI Centre) at LSE is navigating this challenge. While AI could help process the necessary data for net zero alignment, unchecked reliance on automation may lead to misinformation and greenwashing, jeopardising sound decision-making. This event will explore the TPI Centre’s pilot programme aimed at automating data collection to evaluate the net-zero progress of companies, banks, and countries. By bringing together academics, researchers, investors and businesses, we hope to foster discussions on the information essential for advancing the net-zero transition.Featured image (used in source code with watermark added): Photo by Getty Images via Unsplash: https://unsplash.com/photos/3d-rendering-of-earth-futuristic-technology-abstract-background-illustration-60_6d24hGTg