“AgriStack” is being developed as a Digital Public Infrastructure (DPI) that consists of registries, datasets, APIs, and IT Systems. It is enabled by a common set of policies, standards, and guidelines that make agricultural data accessible to the public and private sectors for the creation of services and solutions. The initiative is designed with a clear vision – to simplify farmers’ access to affordable credit, high-quality farm inputs, personalized advisories, and convenient market linkages. It also aims to streamline government planning and implementation of farmer-centric benefit schemes.
In addition, there are state-level initiatives such as the Digital Farmer Services (DFS) platform in Bihar. The DFS will serve as a one-stop solution for Bihar’s small-scale producers (SSPs) to cater to their needs and aspirations through a unified digital platform. It will provide unified and seamless access to services, such as government programs, agriculture advisories, financial services, and market linkages.
It will be built upon the existing state databases and will also be integrated with private service providers for additional capabilities and specialized services.
CGAP commissioned a study to understand the direct and indirect impacts of cyclones and their associated perils on the lives and livelihoods of the affected communities in southwest Bangladesh.
The adaptation strategies of these poor and vulnerable households and the role of financial services in those strategies were also investigated. The study explored pathways to enhance the role of financial services in adaptation strategies and strengthen the resilience of these communities against climate change.
The report was first published on the India Mobile Congress website in October 2023.
Over the past decade, India has seen transformative moments that have propelled its digital revolution onto the global stage. The collaboration between the public and private sectors has been a driving force to foster innovation, improve service delivery, and prioritize user-centered experiences. These initiatives have evolved digital infrastructure and given rise to disruptive ICT innovations, adaptable regulatory frameworks, supportive policies, and an unwavering commitment to customer-centricity. The Department of Telecommunications (DoT), Ministry of Communications, Government of India, has played a central role in this remarkable journey, serving as a pivotal force in facilitating digital connectivity.
Against the backdrop of current and emerging development challenges in both developed and developing economies, India’s extensive digital connectivity and pioneering Digital Public Infrastructure (DPI) programs stand as beacons of progress in the nation’s digital economy. These DPIs are now well-positioned to serve as valuable benchmarks to craft resilient and inclusive digital service delivery models in other economies. Their significance is particularly evident in how they can advance financial and digital inclusion, with a special emphasis on individuals from economically disadvantaged backgrounds, and offer valuable lessons to address the unique socioeconomic issues faced by both developed and developing nations. This report highlights crucial Indian case studies across diverse areas, such as identity, financial services, healthcare, education, and agriculture. It underscores the potential for these cases to be replicated and adopted to benefit developed and developing nations alike.
The press release was first published on the PIB website on 7th February 2024.
As a step towards Digital India, Shri Sanjeev Chopra, Secretary, Department of Food and Public Distribution, Government of India launched a pilot to on-board the Fair Price Shops (FPSs) in Una and Hamirpur districts of Himachal Pradesh on the Open Network Digital Commerce (ONDC). The pilot was launched virtually in 11 FPSs – 5 FPSs in Una and 6 FPSs in Hamirpur districts. This is the first time when Fair Price Shops are on-boarded on ONDC.
Speaking on the occasion, Shri Chopra said this landmark initiative adds to the continuous efforts of the Department in transforming the Fair Price Shops. This effort aims at providing additional avenues of income generation for FPS dealers along with enhancing beneficiary satisfaction.
Furthermore, he underlined that this initiative provides numerous benefits for FPS dealers including visibility in the digital marketplace, access to a larger customer base beyond NFSA beneficiaries, and the ability to compete on an equal footing with large retailers and e-commerce platforms. Additionally, beneficiaries who face difficulties in making online purchase can approach the FPS dealer to make online orders on their behalf.
He highlighted that the success of the pilot being implemented in Himachal Pradesh will serve as a model for statewide and nationwide adoption in the future. He also appreciated the support of MicroSave Consulting (MSC) in deploying this pilot program.
After the launch event, a workshop in physical mode was organised for the FPS dealers in Una & Hamirpur districts. The workshop explained on how to catalogue products, service orders, and commission structure on ONDC etc.
Ms. Anita Karn, Joint Secretary (PD), Shri Ravi Shankar, Director (PD), Shri Mitul Thapliyal, Partner, MSC and Shri Saransh Agrawal, ONDC were also present during the launch event.
As a result, many of the communities most vulnerable to climate change are excluded and unable to participate in the digital revolution. This deprives them of opportunities to access critical information, financial services, key inputs, and collaboration. We need to enlist, train, and deploy a range of community-focused players to help vulnerable communities use the growing array of valuable digital tools to optimize their locally-led adaptation (LLA) planning, implementation, and governance. These players could include the staff of community-based organizations, financial service providers with reach into remote rural areas, agricultural extension workers, agriculture input dealers, and cash-in and cash-out (CICO) agents. Indeed, this is probably the only way we can scale up LLA to the levels required by climate change’s rapidly emerging and increasingly debilitating impacts.
Can AI help?
It is immensely appealing to think that AI can play a role in the development, implementation, and oversight of LLA strategies. However, the development of these strategies necessarily requires the identification, analysis, summarization, and communication of a diverse array of information, datasets, and complex ideas. Effective LLA strategies must consider policy and regulation, climate science, ecology, geography, agriculture, health, financial services, and gender, among other factors. AI could potentially play an important role in distilling the key elements and critical success factors from this daunting range of variables.
Yet the desire to apply AI to complex problems that have historically remained elusive or irrelevant to most modern technology or digital developments has often made the situation worse. The UC Berkley School of Information has already shown how artificial intelligence bias affects women and people of color. Much of this bias is because of feedback loops built onto the most readily and abundantly available data to train the algorithm.
The school notes, “AI is created using a feedback loop. Real-world experiences shape data, which is used to build algorithms. Those algorithms drive decisions affecting real-world experiences. This kind of circular reasoning means that bias can infiltrate the AI process in many ways.” These biases will be amplified further for people on the analog side of the digital divide.
If we are to close the digital divide, we will need a highly cautious, context-specific strategy that considers the needs, interests, and capabilities of local participants. The data on which AI is trained is crucial, so if we want to deploy it to assist with LLA, and indeed many development challenges, we must:
Avoid the imposition of external or top-down solutions and strike a balance between the use of digital technologies even as we respect and acknowledge local expertise, culture, and values;
Ensure local players, particularly those without the required infrastructure, expertise, or money, can access and use digital technology;
Resolve the ethical and legal concerns about data ownership, permission, and use, and ensure the reliability, security, and privacy of digital data and systems.
So, what are the implications for digitally-enabled, locally-led adaptation?
Chatbots and natural language processing (NLP) present valuable possibilities to improve access to information for LLA strategies. However, another key limitation amplifies the challenges outlined by the UC Berkeley School of Information: The datasets used to train NLP systems often lack comprehensive coverage of local dialects, native languages, and regional cultural knowledge. When people are stranded on the analog side of the digital divide, it also reinforces that exclusion as algorithms are built and trained on data from those already connected to the digital world. Thus, such algorithms exclude the voices of those who are not connected. We see an instance of such exclusion in the fact that 99% of the world’s online content is limited to only 40 languages.
Limitations in AI technology highlight the digital divide, as experienced by MSC in our recent projects. In India and Bangladesh, we used AI to analyze voice recordings. Despite being trained in the local languages, the NLP systems, developed with commonly available digital voice data, struggled with the dialects and accents of marginalized groups. Additionally, when we attempted to use AI to anticipate responses from rural women for survey follow-up questions, all AI systems failed, as they did not understand these women’s unique challenges.
The guidance offered by large language model AI systems is likely to be either too general or simply not applicable to the local context of many climate-affected communities. Furthermore, the feedback mechanism in the supervised learning process becomes less effective, as it is challenging to measure and correct the extent of inaccuracies or irrelevance in such generalized or inappropriate solutions. These challenges are mutually reinforcing and could lead to lower adoption rates and trust issues regarding the information provided by AI interfaces.
A good example of this arose in MSC’s work with an AI-driven agri-advisory app, which we have been testing with farmers in Bihar. There, we found the following issues:
Compatibility of the application: We found a wide range of mobile phone models and Android versions, which vary depending on the farmers’ ability to afford them. The lower configuration of the handsets and older versions of Android affect the performance and functionalities that the farmer can avail through the app. This served as an important lesson for us for other digital projects, including the Digital Farmer Services (DFS) platform that MSC has been implementing in Bihar.
Local dialect: The sensitivity of the voice detection functionality to local dialects is an issue. The app struggled to identify keywords, which led to instances where the farmer needed to provide multiple inputs.
Maturity of the apps: In the current state of the app, the quality of the prompts decides the quality of the output. If the prompts are not written properly, the farmer gets basic and generic advice, which is not helpful. The app’s responses may not be relevant in some instances, such as when the farmer does not know of a new pest or disease or if its name is in a local dialect that the app cannot understand. Such examples highlight the LLMs’ limitations.
Appropriate learning data: We wanted to conduct a similar experiment in Bangladesh. Yet, despite the app being already available in West Bengal, which shares a common language with Bangladesh, the cost to retrain the app for Bangladeshi agricultural policies, climatic conditions, value chains, and markets was surprisingly high.
Moreover, significant computing and storage resources are clearly needed to train these models, considering the large volume of data produced in local contexts across a region or geographic area. Additionally, these models may need to be enhanced with more neural nodes to preserve the accuracy of the results. Consequently, the cost of these resources is a major concern—particularly given the remote and “low-value” nature of many vulnerable communities.
Finally, the privacy and security of data significantly increase the challenges. Institutions and governments are still struggling to develop rules, laws, and frameworks for the responsible and ethical use of AI. Given this, communities or local government officials involved in LLA strategies are unlikely to trust a digital platform with their personally identifiable information, especially when they are uncertain about the accuracy of its results. Additionally, while people are still vulnerable to traditional phishing and malware attacks, the emergence of AI-generated deepfakes further complicates and intensifies these security issues.
Conclusion
AI could play an important role to support development initiatives in general and LLA in particular. However, as in all other cases, any AI-based solution or intervention is as good as the relevance and authenticity of the data it is trained on. We will need to make very conscious efforts to include the voices of vulnerable communities, typically on the analog side of the digital divide, if we are to realize the potential of AI. Failure to do so will widen and deepen the divide. This is a challenge on which MSC is working—stay tuned for updates!
“Farming has become such a lottery now that the weather gods are no longer our friends. Everyone in the village has sent their sons away to earn in the city—we have no other way to make ends meet,” sighs Krishna Lal as he laments that “Everything has changed.”
Climate change events impact smallholder farmers in direct and indirect ways. Firstly, extreme weather events, such as hurricanes, floods, and droughts, threaten smallholder farmers, particularly in regions where rain-fed agriculture is prevalent, such as Africa, Asia, and Latin America. These events can lead to crop failure, reduced yields, and loss of income, which affect food security. Additionally, changes in temperature and precipitation can impact livestock and reduce feed quantity and quality, and water availability, which further exacerbates the challenges of smallholder farmers. Moreover, changing growing seasons and the prevalence and dispersal of pests and diseases present additional challenges for farmers.
Climate change will continue to affect food production worldwide. As pera report by the World Bank, 80% of the global population most at risk from crop failures and hunger from climate change are in Sub-Saharan Africa, South Asia, and Southeast Asia. Crop production in South Asia is expected to decrease by 30% by the end of this century. The World Bank report highlights that the most vulnerable populations are those who are already poor and depend on agriculture for their livelihoods.
Digital technologies can facilitate, speed up, and scale LLA planning and the governance functions of monitoring, evaluation, and learning to refine and optimize adaptation initiatives. These technologies can provide various benefits, such as easier and real-time access to information, peer-to-peer information exchange, digital recordkeeping, performance-based payments and carbon credits, and the integration of scientific data and analytics into local plans. As the Climate Resilient Agriculture (CRAg) working group of the CIFAR Alliance notes, digital solutions in various forms can also significantly improve market functioning and the delivery of productivity-enhancing solutions for farmers. These technologies open up new pathways for the adaptation and transformation of agri-food system value chains. Furthermore, many of these technologies are already available but remain hopelessly underused.
Agents as gateways to the digital world and catalysts of change
About 16% of the global adult population lacks access to a mobile phone. For the foreseeable future, 409 million men and 440 million women lack access to basic feature phones, let alone smartphones. As such, we need alternative approaches to ensure they can access digital services and thus provide the data to train algorithms and large language models. Cash-in and cash-out (CICO) agents used by mobile money service providers and banks to deliver financial services can play a pivotal role in the transition of underserved communities to Internet or app usage. They can act as mentors to promote this shift.
The use of agents in this capacity enables shared hardware and allows assisted, on-demand Internet access without the need to buy bulk data. Thus, it grooms future generations of smartphone users. Investments are crucial to establish profitable models that incentivize agents to offer these essential services.
Likewise, microfinance institutions’ (MFIs) staff and agricultural extension agents (AEAs) can be catalytic to promote the development of LLA strategies and plans. MFI staff’s involvement can also ease the collection of data and promote a better understanding of credit risks associated with lending to climate-impacted communities to facilitate lending to these communities. AEAs can provide technical inputs into the rural communities’ adaptation plans, which can strengthen their strategies to respond to climate change along agri-food value chains.
Digitally-enabled locally-led adaptation
CICO agents, MFI staff, and AEAs in climate change-vulnerable areas can emerge as nodal points to help community-based organizations develop LLA plans. With Internet access, they can provide inroads to key data and insights for the participatory planning process and then ease the management and governance to implement these plans.
This would entail these agents being reinvented and incentivized as “catalysts of change,” who would use and facilitate access to various digital technologies for underserved communities. These technologies can be deployed to support and scale LLA planning and monitor the implementation of those plans for performance-based payments. AI-enabled online forums in local languages can offer opportunities for communities to share knowledge, discuss challenges, and co-create adaptation strategies. Mobile platforms can be used to deliver educational content on adaptation practices suitable for local conditions.
These can be complemented by mobile phone surveys, either through IVR, currently being tested by MSC, or voice mobile, such as CATI, as used by 60 Decibels, to collect local climate and environmental data directly from the community. Community-based and operated sensors can collect localized climate data for analysis and planning and complement climate change predictions from GIS and machine learning models. Such machine learning models can be used to predict current and future flood susceptibility under different climate change scenarios. These predictions can be validated and strengthened by satellite and drone service providers, such as Ushahidi, Cropin, and Amini. This could allow communities to use digital mapping to collaboratively plan and visualize adaptation strategies with the use of simple simulation tools to help them understand the potential impacts and benefits of different strategies and provide inputs to national policy and AI models.
As adaptation plans are implemented, local language weather apps, such as TomorrowNow, can be used to provide communities with essential alerts on imminent weather changes, which would enable them to prepare and respond better. Mobile money services can be used to deliver funds in a transparent and efficient way for adaptation projects. Moreover, digital recordkeeping canensure the accountable use of resources and create important digital trails that promote lending by formal financial service providers. In addition, digitally enabled carbon credit tracking and trading platforms, such as CaVEx, can allow farmers to receive financial support for their adaptation.
Digital technologies can help monitor and govern the implementation of adaptation plans and enable smart contracts to reward the achievement of performance goals. Communities can report progress and challenges in real time through community-based and operated sensors, satellite and drone services, and feedback platforms, and provide insights and recommendations to improve adaptation initiatives and local and national climate adaptation policies.
A focus on accessible and practical digital technologies for rural communities and the agents that serve them can significantly enhance LLA strategies’ effectiveness. However, these digital tools must be aligned with the local context, language, and needs, to foster community participation, knowledge sharing, and sustainable adaptation practices. Particular care must be taken to ensure the poorest and most vulnerable people are encouraged and enabled to participate in the planning and monitoring exercises.
Although untested, we believe that agents’ involvement in LLA planning can offer them additional revenue streams and provide real use cases for poorer, vulnerable people in remote communities. This can help often excluded vulnerable people start their journey into the digital world and deliver data to inform and train AI tools. These LLA-driven use cases provide us with opportunities to offer tangible value to these hard-to-reach communities, increase their resilience, and show them the benefits of digital tools. Many vulnerable communities comprise smallholder farmers who can benefit from digitally-enabled value chains and financial services. Climate change and the LLA response to it can bridge the digital divide for these farmers and others currently stranded in the analog world—if we encourage and enable it.
Yet the desire to apply AI to complex problems that have historically remained elusive or irrelevant to most modern technology or digital developments has often made the situation worse. The UC Berkley School of Information has already shown 
These can be complemented by mobile phone surveys, either through