Updates from I2SC

Vibe-coding has, of late, transformed from a novelty among programmers into a mainstay of the software industry. Garry Tan, Y Combinator’s president, has returned to hands-on coding for the first time since his early days of founding a software company, and has praised AI’s ability to quickly reproduce his early software product. Mark Zuckerberg has similarly returned to coding , making his first substantive pull requests to Meta’s production code for the first time in 20 years. Some may dismiss vibe-coding as an advancement in slop-making or a phenomenon in C-suite micro-management, but I find myself in partial agreement with Jensen Huang’s comment that he would go “ape something else” if an engineer on a $500,000 salary were to spend only $5,000 in tokens—there have to be some ways in which AI can save your precious time. On a similar note, a resident AI expert at I2SC has similarly cautioned us against sparing tokens: if 10 hours of your work can be eliminated by $100 in tokens, ...

Fig.1. From OpenClaw to Your Favorite Messaging App At the Interdisciplinary Institute for Societal Computing (I2SC), we recently explored OpenClaw —an open-source, self-hosted AI assistant. It connects to platforms such as Telegram, WhatsApp, Microsoft Teams, Slack, and Discord. Unlike most AI chatbots, it also lets you choose the AI model that best fits your task. One of OpenClaw’s biggest advantages is control . Conversations, memory, API keys, and configuration stay on infrastructure that you manage. The assistant can also run continuously on a server, even when your laptop is turned off. One assistant, multiple channels OpenClaw uses a central gateway between messaging platforms and AI models. The gateway keeps conversation history, runs scheduled tasks, uses browser tools, and executes reusable skills. It also supports multiple AI providers. You can use Claude for complex reasoning, GPT for general tasks, Gemini for Google integrations, or switch models depending on cost and ...

Even though humans produce more photographs than ever, their value is becoming increasingly hidden. The problem is not that photographs have lost their meaning, but that we are surrounded by so many of them that we have started to stop looking at them carefully. This loss of attention matters because photography can do much more than simply preserve a memory. Besides freezing a moment, photographs can document a place, show damage after a crisis, capture public emotion, or make visible something that numbers alone may fail to express. Today, society is increasingly documented through images produced by smartphones, social media, Google Street View, CCTV, news media, and public archives. For societal computing, this makes photographs especially important. They can become data sources for understanding social life, infrastructure, inequality, crisis, collective behavior, and public space. However, in order to use them responsibly, we first need to take them seriously again and see them...

On a hot summer day, the difference between standing beneath a tree and standing beside a wall of concrete is not subtle. One place gives shade, softness, and a small but immediate sense of relief. The other holds heat, reflects it back, and makes the day feel heavier. That contrast is what drew our attention to Berlin. The question is not whether Berlin is getting hotter. Residents have already felt the city's summer heat intensify. The more interesting question is how that heat is distributed across the city, and whether urban greenery influences who experiences the highest temperatures. Recent work highlights the importance of this question is. The Artha Global Climate Study found that neighbourhood-scale heat exposure is closely tied to urban form and tree cover, and that household-level vulnerability cannot be understood from citywide averages alone. Reddington et al. (2025) reached a similar conclusion from another direction, showing that tropical deforestation is associate...

Maybe it’s just me, but the state of the world has me thinking more about data privacy than ever before. I always knew I had to be mindful about my online activity, but now it’s constantly on my mind—and even on my Instagram feed. It all started when I saw a post about how data from Strava was used to identify the locations of active military bases and operational routines. That led me down the rabbit hole of the latest #StravaLeaks, where Le Monde uncovered the location of the Charles de Gaulle, a French nuclear-capable submarine, based on one personnel's running data. Then there was the case of a Russian commander allegedly shot during his jog after posting his route on the app.   Now, Strava is just a fitness app on our phones. I’m sure none of us think twice before installing it, especially regarding privacy. But it really shows how intertwined our data is and how easily it can be accessed. So, I started looking for privacy-aware alternatives for the things I spend most of my t...

Figure: Conceptual illustration of satellite image dimensions (AI-generated based on author description) When we look at a photograph, we see colour, shape, and shadow captured in three channels: red, green, and blue. A satellite image looks similar on the surface, but it is a fundamentally different kind of data. Understanding that difference is the first step toward analysing it properly. A satellite image has three key dimensions. The first is spatial resolution. Every pixel in a satellite image corresponds to a precise latitude and longitude on the ground. This means a pixel is not just a visual element, it has a geographic connotation. You can locate it on Earth, associate it with a real place, and study the spatial patterns of features across an area. The second dimension is spectral resolution. Satellites carry multiple sensors, each measuring a different part of the electromagnetic spectrum. The Sentinel-2 satellite, for example, captures 12 spectral bands. Each band records a ...