Advancing Environmental Justice with AI


Article by Justina Nixon-Saintil: “Given its capacity to innovate climate solutions, the technology sector could provide the tools we need to understand, mitigate, and even reverse the damaging effects of global warming. In fact, addressing longstanding environmental injustices requires these companies to put the newest and most effective technologies into the hands of those on the front lines of the climate crisis.

Tools that harness the power of artificial intelligence, in particular, could offer unprecedented access to accurate information and prediction, enabling communities to learn from and adapt to climate challenges in real time. The IBM Sustainability Accelerator, which we launched in 2022, is at the forefront of this effort, supporting the development and scaling of projects such as the Deltares Aquality App, an AI-powered tool that helps farmers assess and improve water quality. As a result, farmers can grow crops more sustainably, prevent runoff pollution, and protect biodiversity.

Consider also the challenges that smallholder farmers face, such as rising costs, the difficulty of competing with larger producers that have better tools and technology, and, of course, the devastating effects of climate change on biodiversity and weather patterns. Accurate information, especially about soil conditions and water availability, can help them address these issues, but has historically been hard to obtain…(More)”.

Interested but Uncertain: Carbon Markets and Data Sharing among U.S. Crop Farmers


Paper by Guang Han and Meredith T. Niles: “The potential for farmers and agriculture to sequester carbon and contribute to global climate change goals is widely discussed. However, there is currently low participation in agricultural carbon markets and a limited understanding of farmer perceptions and willingness to participate. Furthermore, farmers’ concerns regarding data privacy may complicate participation in agricultural carbon markets, which necessitates farmer data sharing with multiple entities. This study aims to address research gaps by assessing farmers’ willingness to participate in agricultural carbon markets, identifying the determinants of farmers’ willingness regarding carbon markets participation, and exploring how farmers’ concerns for data privacy relate to potential participation in agricultural carbon markets. Data were collected through a multistate survey of 246 farmers and analyzed using descriptive statistics, factor analysis, and multinomial regression models. We find that the majority of farmers (71.8%) are aware of carbon markets and would like to sell carbon credits, but they express high uncertainty about carbon market information, policies, markets, and cost impacts. Just over half of farmers indicated they would share their data for education, developing tools and models, and improving markets and supply chains. Farmers who wanted to participate in carbon markets were more likely to have higher farm revenues, more likely to share their data overall, more likely to share their data with private organizations, and more likely to change farming practices and had more positive perceptions of the impact of carbon markets on farm profitability. In conclusion, farmers have a general interest in carbon market participation, but more information is needed to address their uncertainties and concerns…(More)”.

Setting data free: The politics of open data for food and agriculture


Paper by M. Fairbairn, and Z. Kish: “Open data is increasingly being promoted as a route to achieve food security and agricultural development. This article critically examines the promotion of open agri-food data for development through a document-based case study of the Global Open Data for Agriculture and Nutrition (GODAN) initiative as well as through interviews with open data practitioners and participant observation at open data events. While the concept of openness is striking for its ideological flexibility, we argue that GODAN propagates an anti-political, neoliberal vision for how open data can enhance agricultural development. This approach centers values such as private innovation, increased production, efficiency, and individual empowerment, in contrast to more political and collectivist approaches to openness practiced by some agri-food social movements. We further argue that open agri-food data projects, in general, have a tendency to reproduce elements of “data colonialism,” extracting data with minimal consideration for the collective harms that may result, and embedding their own values within universalizing information infrastructures…(More)”.

German lawmakers mull creating first citizen assembly


APNews: “German lawmakers considered Wednesday whether to create the country’s first “citizen assembly’” to advise parliament on the issue of food and nutrition.

Germany’s three governing parties back the idea of appointing consultative bodies made up of members of the public selected through a lottery system who would discuss specific topics and provide nonbinding feedback to legislators. But opposition parties have rejected the idea, warning that such citizen assemblies risk undermining the primacy of parliament in Germany’s political system.

Baerbel Bas, the speaker of the lower house, or Bundestag, said that she views such bodies as a “bridge between citizens and politicians that can provide a fresh perspective and create new confidence in established institutions.”

“Everyone should be able to have a say,” Bas told daily Passauer Neue Presse. “We want to better reflect the diversity in our society.”

Environmental activists from the group Last Generation have campaigned for the creation of a citizen assembly to address issues surrounding climate change. However, the group argues that proposals drawn up by such a body should at the very least result in bills that lawmakers would then vote on.

Similar efforts to create citizen assemblies have taken place in other European countries such as Spain, Finland, Austria, Britain and Ireland…(More)”.

Farmer-Centric Data Governance: Towards A New Paradigm


Report, six Deep Dives, and nine Case Studies by The Development Gateway: “..provide user-centric approaches to data governance that places farmers and their communities at the center of data gathering initiatives and aims to reduce the negative effects of centralized power. The findings are based on literature, interviews, and workshops, to gather the experiences of change-makers and aims to:
• Raise awareness around the current political economy of agricultural data and its implications;
• Identify user-centric data governance models and mechanisms, particularly in LMICs;
• Demonstrate the purpose, value, benefits, and challenges of these models for all stakeholders; and
• Identify appropriate and relevant actionable principles, recommendations, and considerations related to user-centric data governance in the agriculture sector for the donor community…(More)”

Here’s how the agricultural sector can solve its data problem


Article by Satyanarayana Jeedigunta and Arushi Goel: “Food and nutrition security, skewed distribution of farmer incomes, natural disasters and climate change are severely impacting the sustainability of agricultural systems across the globe. Policy reforms are needed to correct these distortions, but innovative emerging technologies like artificial intelligence, machine learning, distributed ledger technologies, sensors and drones, can make a significant difference.

Emerging technologies need data, and it must be the right data, for the right purpose at the right time. This is how it can deliver maximum impact. Agricultural value chains comprise a complex system of stakeholders and activities. The enormity of the size and complexity of agricultural data, coupled with its fragmented nature, pose significant challenges to unlocking its potential economic value, estimated at $65 billion in India alone….

As such, there is a need to promote standards-based interoperability, which enables multiple digital systems to exchange agricultural data in an automated manner with limited human intervention. The ease and speed of such an exchange of data, across domains and technologies, would spur the development of innovative solutions and lead to evidence-driven, prediction-based decision-making on the farm and in the market.

Most agricultural data is dynamic

Most current efforts to develop standards of agriculture data are isolated and localized. The AGROVOC initiative of the United Nations’ Food and Agriculture Organization addresses a part of the data problem by creating an exhaustive vocabulary of agricultural terms. There is also a need to develop an open data format for the automated interchange of agriculture data. A coordinated initiative of the industry is an attractive approach to develop such a format…(More)”.

Blue Spoons: Sparking Communication About Appropriate Technology Use


Paper by Arun G. Chandrasekhar, Esther Duflo, Michael Kremer, João F. Pugliese, Jonathan Robinson & Frank Schilbach: “An enduring puzzle regarding technology adoption in developing countries is that new technologies often diffuse slowly through the social network. Two of the key predictions of the canonical epidemiological model of technology diffusion are that forums to share information and higher returns to technology should both spur social transmission. We design a large-scale experiment to test these predictions among farmers in Western Kenya, and we fail to find support for either. However, in the same context, we introduce a technology that diffuses very fast: a simple kitchen spoon (painted in blue) to measure out how much fertilizer to use. We develop a model that explains both the failure of the standard approaches and the surprising success of this new technology. The core idea of the model is that not all information is reliable, and farmers are reluctant to develop a reputation of passing along false information. The model and data suggest that there is value in developing simple, transparent technologies to facilitate communication…(More)”.

Designing Data Spaces: The Ecosystem Approach to Competitive Advantage


Open access book edited by Boris Otto, Michael ten Hompel, and Stefan Wrobel: “…provides a comprehensive view on data ecosystems and platform economics from methodical and technological foundations up to reports from practical implementations and applications in various industries.

To this end, the book is structured in four parts: Part I “Foundations and Contexts” provides a general overview about building, running, and governing data spaces and an introduction to the IDS and GAIA-X projects. Part II “Data Space Technologies” subsequently details various implementation aspects of IDS and GAIA-X, including eg data usage control, the usage of blockchain technologies, or semantic data integration and interoperability. Next, Part III describes various “Use Cases and Data Ecosystems” from various application areas such as agriculture, healthcare, industry, energy, and mobility. Part IV eventually offers an overview of several “Solutions and Applications”, eg including products and experiences from companies like Google, SAP, Huawei, T-Systems, Innopay and many more.

Overall, the book provides professionals in industry with an encompassing overview of the technological and economic aspects of data spaces, based on the International Data Spaces and Gaia-X initiatives. It presents implementations and business cases and gives an outlook to future developments. In doing so, it aims at proliferating the vision of a social data market economy based on data spaces which embrace trust and data sovereignty…(More)”.

Modernizing Agriculture Data Infrastructure to Improve Economic and Ecological Outcomes.


Paper by the AGree Initiative and the Data Foundation: “The paper highlights the necessity of data innovation to address a growing number of critical short and long-term food and agricultural issues, including agricultural production, environmental sustainability, nutrition assistance, food waste, and food and farm labor. It concludes by offering four practical options that are effective case studies for data acquisition, management, and use in other sectors.

Given the increasingly dynamic conditions in which the sector operates, the modernization of agricultural data collection, storage, and analysis will equip farmers, ranchers, and the U.S. Department of Agriculture (USDA) with tools to adapt, innovate, and ensure a food-secure future.

While USDA has made strides over the years, to truly unlock the potential of data to improve farm productivity and the resilience of rural communities, the department must establish a more effective data infrastructure, which will require addressing gaps in USDA’s mandate and authorities across its agencies and programs.

The white paper explores four options that are effective case studies for data acquisition, management, and use in other sectors:

  1. Centralized Data Infrastructure Operated by USDA
  2. Centralized Data Infrastructure Operated by a Non-Governmental Intermediary
  3. Data Linkage Hub Operated by a Non-USDA Agency in the Federal Government
  4. Contractual Model with Relevant Partners

Each of the models considered offers opportunities for collaboration with farmers and other stakeholders to ensure there are clear benefits and to address shortfalls in the current system. Careful consideration of the trade-offs of each option is critical given the dynamic weather and economic challenges the agriculture sector faces and the potential new economic opportunities that may be unlocked by harnessing the power of data…(More)”.

The digitalisation of agriculture: A literature review and emerging policy issues


OECD Working Paper: “Digitalisation offers the potential to help address the productivity, sustainability and resilience challenges facing agriculture. Evidence on the adoption and impacts of digital agriculture in OECD countries from national surveys and the literature indicates broad use of digital technologies in row crop farms, but less evidence is available on uptake for livestock and speciality crops. Common barriers to adoption include costs (up-front investment and recurring maintenance expenses), relevance and limited use cases, user-friendliness, high operator skill requirements, mistrust of algorithms, and technological risk. National governments have an important role in addressing bottlenecks to adoption, such as by ensuring better information about costs and benefits of various technologies (including intangible benefits such as quality of life improvements); investing in human capital; ensuring appropriate incentives for innovation; serving as knowledge brokers and facilitators of data-sharing to spur inclusive, secure and representative data ecosystems; and promoting competitive markets….(More)”.