The widespread use of social media has led to a surge in popularity for automated methods of analyzing public opinion. Supervised methods are adept at text categorization, yet the dynamic nature of social media discussions poses a continual challenge for these techniques due to the constant shifting of the focus. On the other hand, traditional unsupervised methods for extracting themes from public discourse, such as topic modeling, often reveal overarching patterns that might not capture specific nuances. Consequently, a significant portion of research into social media discourse still depends on labor-intensive manual coding techniques and a human-in-the-loop approach, which are both time-consuming and costly. In this work, we study the problem of discovering arguments associated with a specific theme. We propose a generic LLMs-in-the-Loop strategy that leverages the advanced capabilities of Large Language Models (LLMs) to extract latent arguments from social media messaging. To demonstrate our approach, we apply our framework to contentious topics. We use two publicly available datasets: (1) the climate campaigns dataset of 14k Facebook ads with 25 themes and (2) the COVID-19 vaccine campaigns dataset of 9k Facebook ads with 14 themes. Additionally, we design a downstream task as stance prediction by leveraging talking points in climate debates. Furthermore, we analyze demographic targeting and the adaptation of messaging based on real-world events.

Recent reports from the Intergovernmental Panel on Climate Change (IPCC) show that climate change is affecting every region of our planet and that some of the changes -- such as rising temperatures and sea levels -- can only be arrested, but are irreversible. Part of the problem stems from how complex an issue climate change is. It has scientific and economic elements and sociopolitical and ethical ones, and it requires cooperation on a scale hitherto unseen. Halting climate change and responding to the effects of the damage already wrought requires two approaches. The first is mitigation, namely trying to remove carbon dioxide from the atmosphere while reducing emissions.

Climate change is causing more frequent and intense droughts, storm, heat waves, rising sea levels and melting glaciers and to stop this destruction, MIT researchers proposes'Space Bubbles' to shield Earth from the sun's rays to combat the devastation. This geoengineering idea would feature inflatable bubbles, organized in a circular shape the size of Brazil, which would sit between the Earth and the sun, blocking radiation from hitting our planet. 'We believe that inflating thin-film spheres directly in space from a homogeneous molten material–such as silicon can provide the variation in thickness that refracts a broader wave spectrum and allows us to avoid the necessity of launching large structural film elements,' the team share in a press release. Although Space Bubbles could reduce the amount of radiation hitting Earth, those involved with the work stress the innovation is designed to supplement and not replace current efforts to combat climate change. MIT researchers proposes'Space Bubbles' to shield Earth from the sun's rays to combat the devastation According to the team at MIT's Senseable City Lab, bubbles have been tested in outer space conditions that they believe could one day be used to deflect solar radiation.

Severe wildfires, raging storms and other extreme weather conditions are all indications that the climate is changing and not for the better. Earlier this month, the United Nations Intergovernmental Panel on Climate Change released its sixth report on the assessment of global climate conditions. The report looks at environments that are growing warmer, rising sea levels and species becoming extinct. The warning is clear: Something must be done to save the climate. But some have attempted to use AI to combat climate change.

"For example, the algorithm analyzes whether there are protected species in an area before the installation of wind farms and whether the designers need to change their plans," says Léa Manneheut, a data scientist at Sinay. If there are a lot of animals at planned construction sites, the noise pollution during the work can at least be reduced with certain insulation measures. Manneheut and her colleagues at Sinay have observed that companies are also paying increasing attention to environmental and climate aspects for image reasons. "There is growing pressure from the public," she says. Researcher Lynn Kaack of the Hertie School says there is a still a lot of catching up to do in terms of interdisciplinary experts working together.

Researchers on the OcéanIA project are developing new artificial intelligence and mathematical modelling tools to contribute to the understanding of the oceans and their role in regulating and sustaining the biosphere, and tackling climate change. You may have seen our recent interview with the director of the project, and of Inria Chile, Nayat Sánchez-Pi. She explained the challenges of research in the field, what they are working on as part of the project, and the role that AI methods play. A key part of the project is data, and much of this is being collected by the Tara Microbiome-CEODOS expedition. The objective of this expedition is to study the marine microorganisms which play a fundamental role in ocean ecosystems.

A lot happened this week in the AI space. The Guardian wrote an article with GPT-3 and again demonstrated that no matter what OpenAI paid to train and create the language model, the free marketing might be worth more. After losing the JEDI cloud contract appeal with the Pentagon, Amazon appointed to its board Keith Alexander, who oversaw the National Security Agency mass surveillance revealed by Edward Snowden leaks in 2013. And Portland passed the strictest facial recognition bans in U.S. history, outlawing government and business use of the technology. However, AI Weekly attempts to reach into the zeitgeist and highlight the issues on people's minds. This week without question it's the smoke that has hung over the western United States and the underlying problem of climate change.

A lot happened this week deserving of attention in the AI space. The Guardian wrote an article with GPT-3 and again demonstrated that no matter what OpenAI paid to train and create the language model, the free marketing might be worth more. After losing the JEDI cloud contract appeal with the Pentagon, Amazon appointed Keith Alexander to its board -- the man who oversaw the National Security Agency mass surveillance revealed by Edward Snowden leaks in 2013. And Portland passed the strictest facial recognition bans in U.S. history, outlawing government and business use of the technology. However, AI Weekly attempts to reach into the zeitgeist and highlight important events on people's minds. This week without question it's the smoke that's hung over the western United States and the underlying issue of climate change.

A new artificial intelligence invention by Hypergiant Industries could prove to be the solution to the world's carbon dioxide problem. The company is launching the second generation Eos Bioreactor, currently still a prototype, that can be used to absorb excess carbon dioxide from the atmosphere and give out oxygen. Besides its ability to reduce environmental pollution, the new AI-based bioreactor also improves health. The excessive presence of carbon dioxide in the atmosphere has led to a steady rise in the average global temperatures over the years. A National Geographic report states that ocean levels will rise by up to 2.3 feet by 2050 due to melting glaciers.

The importance of start-ups and climate tech companies in advancing the use of machine learning to combat climate change was emphasized at a recent online workshop. May 6, 2020 pv magazineAcademics from a group devoted to considering how machine learning can help combat climate change have spoken of the response to a recent workshop which was moved online because of the Covid-19 crisis.The Climate Change AI group hosted a'tackling climate change with machine learning' workshop during this year's International Conference on Learning Representations (ICLR) event."We've "These forecasts can then be sold to electricity suppliers …