My dog contributes to climate change. I've been a vegetarian for over a decade. It's not because of my health, or because I dislike the taste of chicken or beef: It's a lifestyle choice I made because I wanted to reduce my impact on the planet. And yet, twice a day, every day, I lovingly scoop a cup of meat-based kibble into a bowl and set it down for my 50-pound rescue dog, a husky mix named Loki. Until recently, I hadn't devoted a huge amount of thought to that paradox.

Large Language Models (LLMs) distinguish themselves by quickly delivering information and providing personalized responses through natural language prompts. However, they also infer user demographics, which can raise ethical concerns about bias and implicit personalization and create an echo chamber effect. This study aims to explore how inferred political views impact the responses of ChatGPT globally, regardless of the chat session. We also investigate how custom instruction and memory features alter responses in ChatGPT, considering the influence of political orientation. We developed three personas (two politically oriented and one neutral), each with four statements reflecting their viewpoints on DEI programs, abortion, gun rights, and vaccination. We convey the personas' remarks to ChatGPT using memory and custom instructions, allowing it to infer their political perspectives without directly stating them. We then ask eight questions to reveal differences in worldview among the personas and conduct a qualitative analysis of the responses. Our findings indicate that responses are aligned with the inferred political views of the personas, showing varied reasoning and vocabulary, even when discussing similar topics. We also find the inference happening with explicit custom instructions and the implicit memory feature in similar ways. Analyzing response similarities reveals that the closest matches occur between the democratic persona with custom instruction and the neutral persona, supporting the observation that ChatGPT's outputs lean left.

This thesis explores the impact of the Climate Emergency movement on local government climate policy, using computational methods. The Climate Emergency movement sought to accelerate climate action at local government level through the mechanism of Climate Emergency Declarations (CEDs), resulting in a series of commitments from councils to treat climate change as an emergency. With the aim of assessing the potential of current large language models to answer complex policy questions, I first built and configured a system named PALLM (Policy Analysis with a Large Language Model), using the OpenAI model GPT-4. This system is designed to apply a conceptual framework for climate emergency response plans to a dataset of climate policy documents. I validated the performance of this system with the help of local government policymakers, by generating analyses of the climate policies of 11 local governments in Victoria and assessing the policymakers' level of agreement with PALLM's responses. Having established that PALLM's performance is satisfactory, I used it to conduct a large-scale analysis of current policy documents from local governments in the state of Victoria, Australia. This thesis presents the methodology and results of this analysis, comparing the results for councils which have passed a CED to those which did not. This study finds that GPT-4 is capable of high-level policy analysis, with limitations including a lack of reliable attribution, and can also enable more nuanced analysis by researchers. Its use in this research shows that councils which have passed a CED are more likely to have a recent and climate-specific policy, and show more attention to urgency, prioritisation, and equity and social justice, than councils which have not. It concludes that the ability to assess policy documents at scale opens up exciting new opportunities for policy researchers.

Claire chatted to Patrick Meier from the Climate Robotics Network about how robots can help scale action on climate change. Patrick Meier has 15 years of leadership and field experience at the intersection of emerging tech, innovation, and social impact. He founded the Climate Robotics Network and currently leads the UK FCDO project on Robotics for Global Development in low- and middle-income countries. Previously, he served as Strategy Lead for Robotics at the Swiss Institute of Technology (EPFL) and Innovation Booster Robotics. He also co-founded and led WeRobotics, an international technology nonprofit with labs in 40 countries.

The world's addiction to fossil fuels is a "Frankenstein's monster sparing nothing and no one", the UN secretary general, António Guterres, told leaders at the World Economic Forum in Davos on Wednesday. "Our fossil fuel addiction is a Frankenstein's monster, sparing nothing and no one. All around us, we see clear signs that the monster has become master," Guterres said in a speech days after 2024 was revealed to have been the hottest year on record and Donald Trump began his second term as US president by pulling the country out of the Paris climate agreement and pledging to "drill, baby, drill" for more oil and gas. The fossil fuel industry gave 75m ( 60m) to Trump's campaign. Guterres said: "What we are seeing today – sea-level rise, heatwaves, floods, storms, droughts and wildfires – are just a preview of the horror movie to come."

The Deep Learning Indaba 2024 was not just another event for us--it was a reunion. For AfriClimate AI, the Indaba represents our birthplace. It was at the Indaba 2023 in Accra, Ghana, that a pivotal conversation ignited a movement, sparking the creation of AfriClimate AI. "Last year, I was invited to give a talk about my work on Uncertainty, AI, and Climate Science at the Deep Learning Indaba in Accra, Ghana. As is usual with invited talks, one tends to focus on the successful parts of the work. But for some reason, that morning, I decided to add a slide about the challenges of working in AI and sustainability in Africa, primarily driven by the pervasive data scarcity issues. It turned out that almost everyone in the room identified with these issues. This was the birthplace of AfriClimate AI, a grassroots research community dedicated to tackling these issues head-on through capacity building, open datasets, representative benchmarks, and state-of-the-art weather forecasting models for Africa."

As climate change issues become more pressing, their impact in Africa calls for urgent, innovative solutions tailored to the continent's unique challenges. While Artificial Intelligence (AI) emerges as a critical and valuable tool for climate change adaptation and mitigation, its effectiveness and potential are contingent upon overcoming significant challenges such as data scarcity, infrastructure gaps, and limited local AI development. This position paper explores the role of AI in climate change adaptation and mitigation in Africa. It advocates for a collaborative approach to build capacity, develop open-source data repositories, and create context-aware, robust AI-driven climate solutions that are culturally and contextually relevant.

Online memes have emerged as powerful digital cultural artifacts in the age of social media, offering not only humor but also platforms for political discourse, social critique, and information dissemination. Their extensive reach and influence in shaping online communities' sentiments make them invaluable tools for campaigning and promoting ideologies. Despite the development of several meme-generation tools, there remains a gap in their systematic evaluation and their ability to effectively communicate ideologies. Addressing this, we introduce MemeCraft, an innovative meme generator that leverages large language models (LLMs) and visual language models (VLMs) to produce memes advocating specific social movements. MemeCraft presents an end-to-end pipeline, transforming user prompts into compelling multimodal memes without manual intervention. Conscious of the misuse potential in creating divisive content, an intrinsic safety mechanism is embedded to curb hateful meme production.

Fashion and lifestyle have a knack for the surprise. The out-of-the-blue rise of butter moulding, say, or the sudden coolness of a shoe with a cloven toe. Divergence and disparateness are the mood music for 2024. What this means for fashion is yet more extreme luxury, both of the stealth wealth and exhibitionist varieties. But there will also be more emphasis than ever on thrifting, textile recycling, and the development of new materials, especially in the luxury market. Expect more seaweed yarns, plastic-free sequins and grape leathers like those shown by designer Stella McCartney at Cop28. With several elections set for 2024, slogan T-shirts will be used once more for political statements and to pledge allegiance rather than for more personal messages. Expect Maga caps and merch in the vein of Keir Starmer's Sparkle With Starmer tee, turned around at speed after he was glitter-bombed at Labour conference.

"AI for Good is about building AI in the right way and using it for social good. We've learned there are good business reasons for building this technology safely – if you want people to adopt it and use it, they need to be able to trust it. We've done a lot of work around helping domestic abuse victims in South Africa, with a chatbot called rAInbow. It was designed to help people understand their legal rights. It can be quite overwhelming to take that first step to getting help and trusted information if you don't know where to begin. I think it's important to acknowledge the risks this technology brings, but there are also tremendous positive opportunities. I spend a lot of my time building AI that helps improve the justice system and helps people understand their legal rights. With this technology, we can produce legal drafts in minutes that used to take days. Courts can function better and faster, so people can get their hearing dates and we can make the system more efficient. What excites me is that the new generation of technologists don't have to have my background. I went to geek school after geek school, but the newest programming language is human language. This means we can bring in people from many different backgrounds to build it. If we do this right, we will be opening up the profile of people who work in technology and AI." Fanning the flames of a "culture war" might drive ratings, generate clicks and provide politicians with election fodder, but the idea there are ever-deepening divides in British social attitudes is misleading.