Are you interested in what we are currently working on? Then you have come to the right place!

Welcome to our "Working Out Loud" page! In addition to our regular blog posts, we want to offer you a glimpse into our current activities. The idea is to foster collaboration, build connections and accelerate learning. Here, we'll share summaries and insights of our concepts, ideas, thoughts and ongoing activities that are either in the developmental stage or still in the exploratory phase.

While our blog posts dive deeper into our established processes, this page is a place where we can present our work-in-progress and invite your feedback. Some of the topics we present here are already in advanced stages and have corresponding blog posts linked to them, while others are still in their early stages of development.

As Data Lab, we strongly believe in the power of collaboration and are excited to engage with you on our ongoing journey. If you're interested in any of our activities or have some thoughts, ideas or even criticism, we'd love to hear your insights and feedback. Make sure to contact us and join the conversation. Let's work out loud together!

Contact us at: datalab@giz.de

Data Feminism

After the successful Data Feminism Event series conducted in partnership with the Data Pop Alliance, the Data Lab is working on concrete possibilities to implement a feminist approach to data in GIZ's partner countries. In close cooperation with think tanks like Data2X or the aapti Institute and inspired by Catherine d'Ignazio and Lauren Klein, authors of the book Data Feminism, the Data Lab is benefiting from the momentum of the German feminist development cooperation recently launched and explore how it can bring gender data approaches to the next level.

Integrating Data Feminism into Climate Justice Strategies in Brazil /

May 07, 2025 /
Vanessa Hochwald

Together with GIZ’s PoMuC Project in Brazil, we have been working on integrating Data Feminism into the structure of a new project. This involves analyzing the module offerings for entry points for Data Feminism, co-designing a workshop intended to identify potentials, and commenting on the Terms of Reference for the integration of Data Feminism into the Climate Justice Strategy of the program. Further collaboration is envisioned for the future.

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AI Tools for International Negotiations

Every year, 430 million tons of new plastics are produced, and this amount could triple by 2060. Sixty percent of plastics last less than five years and only nine percent are recycled. Microplastics have entered our bodies, our water, our air and our soil. In March 2022, the UN Environment Assembly adopted a historic resolution for a legally binding agreement on plastic pollution and aims to conclude negotiations by the end of 2024. In each round of negotiations, delegates from over 160 countries express their positions in the form of texts or oral statements, which are then documented. The current process requires the INC (Intergovernmental Negotiating Committee on Plastic Pollution) Secretariat to manually search through large amounts of text, which is time-consuming and prone to errors.
To support the INC in the negotiations, the Data Lab and the GIZ Project Marine Litter Prevention are developing an AI tool based on RAG (Retrieval Augmented Generation), which makes it possible to chat with the data to receive automatically generated answers and links to the relevant documents.

Making Circular Economy Knowledge Work: AI as an Enabler /

May 06, 2025 /
Robin Nowok

At the GGKP & SwitchAsia webinar “Harnessing AI to Scale the Impact of Circular Economy Knowledge”, we had the opportunity to discuss how AI can help make circular economy knowledge more accessible, structured, and practically useful. A key takeaway: The real value of AI lies not in how smoothly it generates text, but in how reliably it connects to verifiable knowledge. To be useful in policy and practice, AI must be grounded in curated sources and offer full transparency - users need to trace the origin of its answers.

One idea to connect NegotiateAI's "plastic knowledge hub" to an API integration with plastic taxonomies of the GGKP to link plastic-related knowledge and data models, helping users navigate complex sustainability content with precision.

The recording is available here: https://www.switch-asia.eu/event/harnessing-ai-to-scale-the-impact-of-circular-economy-knowledge/link

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Unveiling Vulnerabilities in Climate Policy

The global climate crisis affects everyone, but particularly impacts disadvantaged and vulnerable groups, such as children, the elderly, coastal communities, and the LGBTQI+ community, due to their socio-economic status. It's essential to integrate their concerns into national climate policies for effective and equitable climate action. However, analyzing extensive policy documents poses a significant challenge. To address this, the CPV pilot uses natural language processing (NLP) to identify and list contextual mentions of vulnerable groups, enabling gap identification and recommendations. It also incorporates a chat-based AI assistant, fine-tuned for user questions related to vulnerable groups in climate policy documents. Currently, the database covers 10 sub-Saharan African countries, starting with Kenya.

Inclusive climate policy at the UN World Data Forum in Medellín
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November 14, 2024 /
Robin Nowok

Together with our colleague Lea Voigt from our sister project, the Data Service Center, Robin Nowok had the opportunity to present our open-source Climate Policy Vulnerability App at the UN World Data Forum in Medellín. The presentation sparked significant interest in harnessing AI for development, particularly for advancing more inclusive climate policies. Our special thanks go to our partners in the GIZ NDC Assist II programme for their invaluable contributions - without their support, our selection for the WDF probably would not have been possible. 

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AI Image Recognition for Electronics Waste in Ghana

Driven by rapid technological advancements and the growing consumption of electronic devices, electronic waste is becoming a problem of global dimensions. The WHO documents that only 22.3% of the annual e-waste is formally collected and recycled. To tackle the e-waste crisis, we are collaborating with local stakeholders in Ghana to develop an AI-based image recognition application. The app is designed to assist users in the identification, categorization and documentation of electronic waste. By empowering local authorities, waste management organizations, and recyclers, our project aims to identify health and environmental risks, promote sustainable practices and contribute to a circular economy.

E-Waste Kick-off /

October 07, 2024 /
Lucas Braun

We are excited to share our newest Experiment! Partnering with local stakeholders in the Ghanaian recycling industry, we devised a plan to develop an advanced AI image recognition, which shall be integrated into local material flow processes. We imagine an application for handheld mobile devices, which allows for automatic scanning of landfill intake. Besides harmonizing stocktaking processes, working conditions of local waste collectors shall be improved by giving information about toxicity and value of different EWaste classes. Stay tuned!

DPPD - Road To Implementation

After the successful implementation of the DPPD Masterclass in November 2022, some teams are on their way to implement their proposed use case ideas. Topics of some of the projects deal with proven practices for reduced deforestation in Ghana or resilient wetland conservation in India. The Data Lab offers assistance with personal support with regards to technical aspects as well as deeper methodological DPPD insights and project fine-tuning. Furthermore, a self-paced atingi course on DPPD applications is in development.

Final Steps for Atingi Course /

October 01, 2024 /
Robin Nowok

Nearly two years after the instalment of the DPPD Masterclass, we are pleased to announce that a self-paced online course, "Getting Started with Data-Powered Positive Deviance," is nearing completion. This course will allow learners to explore the stages of the DPPD methodology at their own pace.

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