Can Large Language Models Capture Public Opinion about Global Warming? An Empirical Assessment of Algorithmic Fidelity and Bias


Paper by S. Lee et all: “Large language models (LLMs) have demonstrated their potential in social science research by emulating human perceptions and behaviors, a concept referred to as algorithmic fidelity. This study assesses the algorithmic fidelity and bias of LLMs by utilizing two nationally representative climate change surveys. The LLMs were conditioned on demographics and/or psychological covariates to simulate survey responses. The findings indicate that LLMs can effectively capture presidential voting behaviors but encounter challenges in accurately representing global warming perspectives when relevant covariates are not included. GPT-4 exhibits improved performance when conditioned on both demographics and covariates. However, disparities emerge in LLM estimations of the views of certain groups, with LLMs tending to underestimate worry about global warming among Black Americans. While highlighting the potential of LLMs to aid social science research, these results underscore the importance of meticulous conditioning, model selection, survey question format, and bias assessment when employing LLMs for survey simulation. Further investigation into prompt engineering and algorithm auditing is essential to harness the power of LLMs while addressing their inherent limitations…(More)”.

Data collaboration to enable the EU Green Deal


Article by Justine Gangneux: “In the fight against climate change, local authorities are increasingly turning to cross-sectoral data sharing as a game-changing strategy.

This collaborative approach empowers cities and communities to harness a wealth of data from diverse sources, enabling them to pinpoint emission hotspots, tailor policies for maximum impact, and allocate resources wisely.

Data can also strengthen climate resilience by engaging local communities and facilitating real-time progress tracking…

In recent years, more and more local data initiatives aimed at tackling climate change have emerged, spanning from urban planning to mobility, adaptation and energy management.

Such is the case of Porto’s CityCatalyst – the project put five demonstrators in place to showcase smart cities infrastructure and develop data standards and models, contributing to the efficient and integrated management of urban flows…

In Latvia, Riga is also exploring data solutions such as visualisations, aggregation or analytics, as part of the Positive Energy District strategy.  Driven by the national Energy Efficiency Law, the city is developing a project to monitor energy consumption based on building utility use data (heat, electricity, gas, or water), customer and billing data, and Internet of Things smart metre data from individual buildings…

As these examples show, it is not just public data that holds the key; private sector data, from utilities as energy or water, to telecoms, offers cities valuable insights in their efforts to tackle climate change…(More)”.

Our Planet Powered by AI: How We Use Artificial Intelligence to Create a Sustainable Future for Humanity


Book by Mark Minevich: “…You’ll learn to create sustainable, effective competitive advantage by introducing previously unheard-of levels of adaptability, resilience, and innovation into your company.

Using real-world case studies from a variety of well-known industry leaders, the author explains the strategic archetypes, technological infrastructures, and cultures of sustainability you’ll need to ensure your firm’s next-level digital transformation takes root. You’ll also discover:

  • How AI can enable new business strategies, models, and ecosystems of innovation and growth
  • How to develop societal impact and powerful organizational benefits with ethical AI implementations that incorporate transparency, fairness, privacy, and reliability
  • What it means to enable all-inclusive artificial intelligence

An engaging and hands-on exploration of how to take your firm to new levels of dynamism and growth, Our Planet Powered by AI will earn a place in the libraries of managers, executives, directors, and other business and technology leaders seeking to distinguish their companies in a new age of astonishing technological advancement and fierce competition….(More)”.

Lessons from the Past to Govern for the Future


Article by Claudette Salinas Leyva et al: “Many of our institutions are focused on the short term. Whether corporations, government bodies, or even nonprofits, they tend to prioritize immediate returns and discount long-term value and sustainability. This myopia is behind planetary crises such as climate change and biodiversity loss and contributes to decision-making that harms the wellbeing of communities.

Policymakers worldwide are beginning to recognize the importance of governing for the long term. The United Nations is currently developing a Declaration on Future Generations to codify this approach. This collection of case studies profiles community-level institutions rooted in Indigenous traditions that focus on governing for the long term and preserving the interests of future generations…(More)”.

How to share data — not just equally, but equitably


Editorial in Nature: “Two decades ago, scientists asked more than 150,000 people living in Mexico City to provide medical data for research. Each participant gave time, blood and details of their medical history. For the researchers, who were based at the National Autonomous University of Mexico in Mexico City and the University of Oxford, UK, this was an opportunity to study a Latin American population for clues about factors contributing to disease and health. For the participants, it was a chance to contribute to science so that future generations might one day benefit from access to improved health care. Ultimately, the Mexico City Prospective Study was an exercise in trust — scientists were trusted with some of people’s most private information because they promised to use it responsibly.

Over the years, the researchers have repaid the communities through studies investigating the effects of tobacco and other risk factors on participants’ health. They have used the data to learn about the impact of diabetes on mortality rates, and they have found that rare forms of a gene called GPR75 lower the risk of obesity. And on 11 October, researchers added to the body of knowledge on the population’s ancestry.

But this project also has broader relevance — it can be seen as a model of trust and of how the power structures of science can be changed to benefit the communities closest to it.

Mexico’s population is genetically wealthy. With a complex history of migration and mixing of several populations, the country’s diverse genetic resources are valuable to the study of the genetic roots of diseases. Most genetic databases are stocked with data from people with European ancestry. If genomics is to genuinely benefit the global community — and especially under-represented groups — appropriately diverse data sets are needed. These will improve the accuracy of genetic tests, such as those for disease risk, and will make it easier to unearth potential drug targets by finding new genetic links to medical conditions…(More)”.

Think, before you nudge: those who pledge to eco-friendly diets respond more effectively to a nudge


Article (and paper) by Sanchayan Banerjee: “We appreciate the incredible array of global cuisines available to us. Despite the increasing prices, we enjoy a wide variety of food options, including an abundance of meats that our grandparents could only dream of, given their limited access. However, this diverse culinary landscape comes with a price – the current food choices significantly contribute to carbon emissions and conflict with our climate objectives. Therefore, transitioning towards more eco-friendly diets is crucial.

Instead of imposing strict measures or raising costs, researchers have employed subtle “nudges”, those that gently steer individuals toward socially beneficial choices, to reduce meat consumption. These nudges aim to modify how food choices are presented to consumers without imposing choices on them. Nevertheless, expanding the use of these nudges has proven to be a complex task in general, as it sometimes raises ethical concerns about whether people are fully aware of the messages encouraging them to change their behaviour. In the context of diets which are personal, researchers have argued nudging can be ethically dubious. What business do we have in telling people what to eat?

To address these challenges, a novel approach in behavioral science, known as “nudge+”, can empower individuals to reflect on their choices and encourage meaningful shifts towards more environmentally friendly behaviours. A nudge+ is a combination of a nudge with an encouragement to think…(More)”.

The growing energy footprint of artificial intelligence


Paper by Alex de Vries: “Throughout 2022 and 2023, artificial intelligence (AI) has witnessed a period of rapid expansion and extensive, large-scale application. Prominent tech companies such as Alphabet and Microsoft significantly increased their support for AI in 2023, influenced by the successful launch of OpenAI’s ChatGPT, a conversational generative AI chatbot that reached 100 million users in an unprecedented 2 months. In response, Microsoft and Alphabet introduced their own chatbots, Bing Chat and Bard, respectively.

 This accelerated development raises concerns about the electricity consumption and potential environmental impact of AI and data centers. In recent years, data center electricity consumption has accounted for a relatively stable 1% of global electricity use, excluding cryptocurrency mining. Between 2010 and 2018, global data center electricity consumption may have increased by only 6%.

 There is increasing apprehension that the computational resources necessary to develop and maintain AI models and applications could cause a surge in data centers’ contribution to global electricity consumption.

This commentary explores initial research on AI electricity consumption and assesses the potential implications of widespread AI technology adoption on global data center electricity use. The piece discusses both pessimistic and optimistic scenarios and concludes with a cautionary note against embracing either extreme…(More)”.

Google’s Expanded ‘Flood Hub’ Uses AI to Help Us Adapt to Extreme Weather


Article by Jeff Young: “Google announced Tuesday that a tool using artificial intelligence to better predict river floods will be expanded to the U.S. and Canada, covering more than 800 North American riverside communities that are home to more than 12 million people. Google calls it Flood Hub, and it’s the latest example of how AI is being used to help adapt to extreme weather events associated with climate change.

“We see tremendous opportunity for AI to solve some of the world’s biggest challenges, and climate change is very much one of those,” Google’s Chief Sustainability Officer, Kate Brandt, told Newsweek in an interview.

At an event in Brussels on Tuesday, Google announced a suite of new and expanded sustainability initiatives and products. Many of them involve the use of AI, such as tools to help city planners find the best places to plant trees and modify rooftops to buffer against city heat, and a partnership with the U.S. Forest Service to use AI to improve maps related to wildfires.

Google Flood Hub Model AI extreme weather
A diagram showing the development of models used in Google’s Flood Hub, now available for 800 riverside locations in the U.S. and Canada. Courtesy of Google Research…

Brandt said Flood Hub’s engineers use advanced AI, publicly available data sources and satellite imagery, combined with hydrologic models of river flows. The results allow flooding predictions with a longer lead time than was previously available in many instances…(More)”.

More Companies Are Disclosing Their ESG Data, but Confusion on How Persists


Article by David Breg: “Public companies in the U.S. are increasingly disclosing sustainability information, but many say they find it a challenge to report fundamental climate data that many regulators around the globe likely will require under incoming mandatory reporting standards

Nearly two-thirds of respondents said their company was disclosing environmental, social and governance information, up from 56% in the prior year, according to the annual survey of sustainability officials that WSJ Pro conducted this spring.

However, there was little consensus on which framework to use and respondents highlighted three fundamental types of information as their three biggest environmental reporting challenges: Greenhouse-gas emissions, climate-change risk and energy management.

The proportion of companies disclosing sustainability and ESG information was 63%, up from 56% last year. Those that don’t yet report this data but plan to was 16%, down from 25% last year. About one-fifth of respondents said their organization had no plans to report their progress, virtually unchanged from last year. Breaking that down, a quarter of private companies don’t plan any ESG reporting, while only 7% of public companies felt the same.

Regulators around the globe are finalizing rules that would require companies to publish standardized information after years of patchy voluntary ESG reporting based on a host of frameworks. California’s governor has said he would soon sign that state’s requirements into law. The U.S. Securities and Exchange Commission’s rules are expected later this year. European regulations are already in place and many other countries are also working on standards. The International Sustainability Standards Board hopes its climate framework, completed this past summer, becomes the global baseline

While it is mostly public companies that face mandatory requirements, even private businesses face increased scrutiny of their sustainability and ESG policies from stakeholders including shareholders, eco-conscious consumers, suppliers, insurers and lenders…(More)”.

Computing the Climate: How We Know What We Know About Climate Change


Book by Steve M. Easterbrook: “How do we know that climate change is an emergency? How did the scientific community reach this conclusion all but unanimously, and what tools did they use to do it? This book tells the story of climate models, tracing their history from nineteenth-century calculations on the effects of greenhouse gases, to modern Earth system models that integrate the atmosphere, the oceans, and the land using the full resources of today’s most powerful supercomputers. Drawing on the author’s extensive visits to the world’s top climate research labs, this accessible, non-technical book shows how computer models help to build a more complete picture of Earth’s climate system. ‘Computing the Climate’ is ideal for anyone who has wondered where the projections of future climate change come from – and why we should believe them…(More)”.