The investigation employs a standardized tool, the Environmental Knowledge Test (EKT - 19), supple mented by targeted questions, to evaluate the environmental knowledge of university students in comparison to the responses generated by the AI models. The results of this study suggest that while AI models possess a vast, readily accessible, and valid kno wledge base with the potential to empower both students and academic staff, a human discipline specialist in environmental sciences may still be necessary to validate the accuracy of the information provided. Keywords: En vironmental Education; AI Models; EKT - 19 1. Introduction Extreme weather events, increasing global temperatures, rising sea - levels, and changes to ecosystems and biodiversity are all consequences of climate change, which is mostly caused by anthropogenic greenhouse gas emissions ( Masson - Delmotte et al., 2018). Meanwhile, the loss of biodiversity due to habitat degradation, pollution, overexploitation, and invasive species threatens the resilience of society's ecosystems (Nature, 2021). These consequences pose questions regarding food security, public he alth, and socioeconomic stability. Thus, effective access to accurate environmental knowledge is crucial for developing sustainable solutions and informed environmental policies.

Large language models (LLMs) have transformed natural language processing, yet face challenges in specialized tasks such as simulating opinions on environmental policies. This paper introduces a novel fine-tuning approach that integrates socio-demographic data from the UK Household Longitudinal Study, uniquely using profiling factors, such as age, gender, income, education, and region. This method enhances the accuracy and representation of generated views. By emulating diverse synthetic profiles, the fine-tuned models significantly outperform pre-trained counterparts, achieving measurable improvements in capturing demographic nuances. Evaluation metrics, including Chi-Squared, Cosine Similarity, Jaccard Index, and KL-divergence, reveal a strong alignment between synthetic and real-world opinions. This work demonstrates the potential of fine-tuned LLMs tailored to societal contexts to enable more ethical and precise policy simulations. Its broader implications include deploying LLMs in domains like healthcare and education, fostering inclusive and data-driven decision-making in both research and practice.

Climate change poses critical challenges globally, disproportionately affecting low-income countries that often lack resources and linguistic representation on the international stage. Despite Bangladesh's status as one of the most vulnerable nations to climate impacts, research gaps persist in Bengali-language studies related to climate change and NLP. To address this disparity, we introduce Dhoroni, a novel Bengali (Bangla) climate change and environmental news dataset, comprising a 2300 annotated Bangla news articles, offering multiple perspectives such as political influence, scientific/statistical data, authenticity, stance detection, and stakeholder involvement. Furthermore, we present an in-depth exploratory analysis of Dhoroni and introduce BanglaBERT-Dhoroni family, a novel baseline model family for climate and environmental opinion detection in Bangla, fine-tuned on our dataset. This research contributes significantly to enhancing accessibility and analysis of climate discourse in Bengali (Bangla), addressing crucial communication and research gaps in climate-impacted regions like Bangladesh with 180 million people.

As the conversation around using geoengineering to combat climate change intensifies, it is imperative to engage the public and deeply understand their perspectives on geoengineering research, development, and potential deployment. Through a comprehensive data-driven investigation, this paper explores the types of news that captivate public interest in geoengineering. We delved into 30,773 English-language news articles from the BBC and the New York Times, combined with Google Trends data spanning 2018 to 2022, to explore how public interest in geoengineering fluctuates in response to news coverage of broader climate issues. Using BERT-based topic modeling, sentiment analysis, and time-series regression models, we found that positive sentiment in energy-related news serves as a good predictor of heightened public interest in geoengineering, a trend that persists over time. Our findings suggest that public engagement with geoengineering and climate action is not uniform, with some topics being more potent in shaping interest over time, such as climate news related to energy, disasters, and politics. Understanding these patterns is crucial for scientists, policymakers, and educators aiming to craft effective strategies for engaging with the public and fostering dialogue around emerging climate technologies.

Social media is now the predominant source of information due to the availability of immediate public response. As a result, social media data has become a valuable resource for comprehending public sentiments. Studies have shown that it can amplify ideas and influence public sentiments. This study analyzes the public perception of climate change and the environment over a decade from 2014 to 2023. Using the Pointwise Mutual Information (PMI) algorithm, we identify sentiment and explore prevailing emotions expressed within environmental tweets across various social media platforms, namely Twitter, Reddit, and YouTube. Accuracy on a human-annotated dataset was 0.65, higher than Vader score but lower than that of an expert rater (0.90). Our findings suggest that negative environmental tweets are far more common than positive or neutral ones. Climate change, air quality, emissions, plastic, and recycling are the most discussed topics on all social media platforms, highlighting its huge global concern. The most common emotions in environmental tweets are fear, trust, and anticipation, demonstrating public reactions wide and complex nature. By identifying patterns and trends in opinions related to the environment, we hope to provide insights that can help raise awareness regarding environmental issues, inform the development of interventions, and adapt further actions to meet environmental challenges.

Over the past decades, artificial intelligence (AI) has gone from being something out of science fiction to being very much part of science fact. It is now an integral part of our present, and we are beginning to see the impact it has on the workplace, the economy and the technology we use every day. How can we leverage AI to build a greener and more sustainable future? AI has long been a favourite subject in fiction, be it books, graphic novels or films – think 2001: A Space Odyssey, The Matrix or even The Terminator. In the interests of drama and suspense, the AI portrayed is more often than not malevolent, with machines having half an eye on taking over the world (or in the case of The Matrix, the machine actually being the world).

Environmental problems become more urgent and affect the lives of people, marine life, and various animal species. Only in 2022, forest fires in Spain, France, and many other countries worldwide led to the destruction of animals' natural habitats, a decrease in the number of air producers, and many harmful outcomes for local residents. Although it is hard to say if humanity can still stop global warming and other environmental issues, there are some ways to restrain their development, and the utilization of renewable energy sources is among them. In this article, we list the best and most innovative renewable energy companies to keep on your radar this year. Moreover, if you are seeking more information on how modern technology can help us prevent global environmental catastrophes, read these AITJ articles: 5 Ways AI Can Improve Environmental Sustainability and How AI Helps Clean Oceans from Plastics.

The world of finance is changing. Since the financial crash in 2008, there has been a slow but steady move away from traditional finance models, as the value of embedding deeper approaches to social and environmental issues has become increasingly clear. Now, the world has taken a shocking blow from the COVID-19 pandemic. The tragic deaths, lost livelihoods, and curtailed freedoms are unprecedented, and no-one can tell how or when the global economy will recover from a downturn of this speed and scale. As we tackle one of the biggest global crises of our time, and look to rebuild in a way that ensures we emerge from this stronger and more resilient, sustainable finance – in other words, finance that takes account of positive and negative social and environmental factors, particularly the factors that tend to play out over the medium to long-term – will be more critical than ever.

The use of technology to solve environmental issues featured strongly at Microsoft's Future Decoded conference this year. Multiple sources show that to slow the effect of climate change and continue to support an ever-growing population, we need to act now. Here, Annie Andrews, head of technology at Microsoft recruitment agency, Curo Talent, explains how. It is a topic that will profoundly affect many aspects of the lives of the workforce of the future. During the Day 1 morning keynote, Dr Lucas Joppa, Chief Environmental Officer for Microsoft, gave businesses three priorities to consider.

On 11 December 2017, at the One Planet Summit in Paris, Microsoft announced our $50m, five-year commitment to using AI to improve sustainability, known as AI for Earth. In the past year, the program has grown to support 233 grantees doing work with impact in more than 50 countries and all seven continents. We have also seen the science, from the IPCC and others, that indicate progress is still too slow and uneven to achieve a 2-degree future agreed to in the Paris Accord. Below, you'll see our vision for the program and in following pieces, you'll see how we're continuing to accelerate our efforts. On the two-year anniversary of the Paris climate accord, the world's political, civic and business leaders came together in Paris to discuss one of the most important issues and opportunities of our time: climate change.