This Chatbot Democratizes Data to Empower India’s Farmers

Curated on Posted on by Stefaan Verhulst

Article by Abha Malpani Naismith: “…The lack of access to market price information and reliance on intermediaries to sell on their behalf leaves farmers vulnerable to price exploitation and uncertain returns on their investments.

To solve this, Gramhal is building a data cooperative in India where farmers contribute their information to a data ecosystem, which all farmers can leverage for better informed decision-making…

The social enterprise started the project to democratize data first by using the Indian government’s collected data sets from markets and crops across the country. It then built a chatbot (called Bolbhav) and plugged in that data. Soon about 300,000 farmers were accessing this data set via the chatbot on their mobile phones. 

“We spent no money on marketing — this was all just from word of mouth!” Kaleem said. 

gramhal chatbot provides market data for small farmers in India
Gramhal’s Bolbhav chatbot provides farmers with market data so they know how to fairly price their crops. 

However, Gramhal started getting feedback from farmers that the chatbot was giving them prices three days old and what they wanted was real-time, reliable data. “That is when we realized that we need to work with the power of community and think about a societal network framework where every farmer who is selling can contribute to the data and have access to it,” Kaleem explained. “We needed to find a way where the farmer can send price information about what they are selling by uploading their receipts, and we can aggregate that data across markets and share it with them.”

The solution was an upgraded version of the chatbot called Bolbhav Plus, which Gramhal launched in April 2023…(More)”

AI Is Building Highly Effective Antibodies That Humans Can’t Even Imagine

Curated on Posted on by Stefaan Verhulst

Article by Amit Katwala: “Robots, computers, and algorithms are hunting for potential new therapies in ways humans can’t—by processing huge volumes of data and building previously unimagined molecules. At an old biscuit factory in South London, giant mixers and industrial ovens have been replaced by robotic arms, incubators, and DNA sequencing machines.

James Field and his company LabGenius aren’t making sweet treats; they’re cooking up a revolutionary, AI-powered approach to engineering new medical antibodies. In nature, antibodies are the body’s response to disease and serve as the immune system’s front-line troops. They’re strands of protein that are specially shaped to stick to foreign invaders so that they can be flushed from the system. Since the 1980s, pharmaceutical companies have been making synthetic antibodies to treat diseases like cancer, and to reduce the chance of transplanted organs being rejected. But designing these antibodies is a slow process for humans—protein designers must wade through the millions of potential combinations of amino acids to find the ones that will fold together in exactly the right way, and then test them all experimentally, tweaking some variables to improve some characteristics of the treatment while hoping that doesn’t make it worse in other ways. “If you want to create a new therapeutic antibody, somewhere in this infinite space of potential molecules sits the molecule you want to find,” says Field, the founder and CEO of LabGenius…(More)”.

Open Government Products (OGP)

Curated on Posted on by Stefaan Verhulst

About: “We are an experimental development team that builds technology for the public good. This includes everything from building better apps for citizens to automating the internal operations of public agencies. Our role is to accelerate the digital transformation of the Singapore Government by being a space where it can experiment with new tech practices, including new technologies, management techniques, corporate systems, and even cultural norms. Our end goal is that through our work, Singapore becomes a model of how governments can use technology to improve the public good…(More)”.

Citizen Jury on New Genomic Techniques

Curated on Posted on by Stefaan Verhulst

Paper by Kai P. Purnhagen and Alexandra Molitorisova: “Between 26-28 January 2024, a citizen jury was convened at the Schloss Thurnau in Upper Franconia, Germany to deliberate about new genomic techniques (NGTs) used in agriculture and food/feed production, ahead of the vote of the European Parliament and the Council of the European Union on the European Commission’s proposal for a regulation on plants obtained by certain NGTs and their food and feed. This report serves as a policy brief with all observations, assessments, and recommendations agreed by the jury with a minimum of 75 percent of the jurors’ votes. This report aims to provide policymakers, stakeholders, and the public with perspectives and considerations surrounding the use of NGTs in agriculture and food/feed production, as articulated by the members of the jury. There are 18 final recommendations produced by the jury. Through thoughtful analysis and dialogue, the jury sought to contribute to informed decision-making processes…(More)”.

The Crisis of Culture: Identity Politics and the Empire of Norms

Curated on Posted on by Stefaan Verhulst

Book by Olivier Roy: “Are we confronting a new culture—global, online, individualistic? Or is our existing concept of culture in crisis, as explicit, normative systems replace implicit, social values?

Olivier Roy’s new book explains today’s fractures via the extension of individual political and sexual freedoms from the 1960s. For Roy, twentieth-century youth culture disconnected traditional political protest from class, region or ethnicity, fashioning an identity premised on repudiation rather than inheritance of shared history or values. Having spread across generations under neoliberalism and the internet, youth culture is now individualised, ersatz.

Without a shared culture, everything becomes an explicit code of how to speak and act, often online. Identities are now defined by socially fragmenting personal traits, creating affinity-based sub-cultures seeking safe spaces: universities for the left, gated communities and hard borders for the right.

Increased left- and right-wing references to ‘identity’ fail to confront this deeper crisis of culture and community. Our only option, Roy argues, is to restore social bonds at the grassroots or citizenship level…(More)”.

Narratives Online. Shared Stories in Social Media

Curated on Posted on by Stefaan Verhulst

Book by Ruth Page: “Stories are shared by millions of people online every day. They post and re-post interactions as they re-tell and respond to large-scale mediated events. These stories are important as they can bring people together, or polarise them in opposing groups. Narratives Online explores this new genre – the shared story – and uses carefully chosen case-studies to illustrate the complex processes of sharing as they are shaped by four international social media contexts: Wikipedia, Facebook, Twitter and YouTube. Building on discourse analytic research, Ruth Page develops a new framework – ‘Mediated Narrative Analysis’ – to address the large scale, multimodal nature of online narratives, helping researchers interpret the micro- and macro-level politics that are played out in computer-mediated communication…(More)”.

Market Power in Artificial Intelligence

Curated on Posted on by Stefaan Verhulst

Paper by Joshua S. Gans: “This paper surveys the relevant existing literature that can help researchers and policy makers understand the drivers of competition in markets that constitute the provision of artificial intelligence products. The focus is on three broad markets: training data, input data, and AI predictions. It is shown that a key factor in determining the emergence and persistence of market power will be the operation of markets for data that would allow for trading data across firm boundaries…(More)”.

Citizen silence: Missed opportunities in citizen science

Curated on Posted on by Stefaan Verhulst

Paper by Damon M Hall et al: “Citizen science is personal. Participation is contingent on the citizens’ connection to a topic or to interpersonal relationships meaningful to them. But from the peer-reviewed literature, scientists appear to have an acquisitive data-centered relationship with citizens. This has spurred ethical and pragmatic criticisms of extractive relationships with citizen scientists. We suggest five practical steps to shift citizen-science research from extractive to relational, reorienting the research process and providing reciprocal benefits to researchers and citizen scientists. By virtue of their interests and experience within their local environments, citizen scientists have expertise that, if engaged, can improve research methods and product design decisions. To boost the value of scientific outputs to society and participants, citizen-science research teams should rethink how they engage and value volunteers…(More)”.

Predicting IMF-Supported Programs: A Machine Learning Approach

Curated on Posted on by Stefaan Verhulst

Paper by Tsendsuren Batsuuri, Shan He, Ruofei Hu, Jonathan Leslie and Flora Lutz: “This study applies state-of-the-art machine learning (ML) techniques to forecast IMF-supported programs, analyzes the ML prediction results relative to traditional econometric approaches, explores non-linear relationships among predictors indicative of IMF-supported programs, and evaluates model robustness with regard to different feature sets and time periods. ML models consistently outperform traditional methods in out-of-sample prediction of new IMF-supported arrangements with key predictors that align well with the literature and show consensus across different algorithms. The analysis underscores the importance of incorporating a variety of external, fiscal, real, and financial features as well as institutional factors like membership in regional financing arrangements. The findings also highlight the varying influence of data processing choices such as feature selection, sampling techniques, and missing data imputation on the performance of different ML models and therefore indicate the usefulness of a flexible, algorithm-tailored approach. Additionally, the results reveal that models that are most effective in near and medium-term predictions may tend to underperform over the long term, thus illustrating the need for regular updates or more stable – albeit potentially near-term suboptimal – models when frequent updates are impractical…(More)”.

Whatever Happened to All Those Care Robots?

Curated on Posted on by Stefaan Verhulst

Article by Stephanie H. Murray: “So far, companion robots haven’t lived up to the hype—and might even exacerbate the problems they’re meant to solve…There are likely many reasons that the long-predicted robot takeover of elder care has yet to take off. Robots are expensive, and cash-strapped care homes don’t have money lying around to purchase a robot, let alone to pay for the training needed to actually use one effectively. And at least so far, social robots just aren’t worth the investment, Wright told me. Pepper can’t do a lot of the things people claimed he could—and he relies heavily on humans to help him do what he can. Despite some research suggesting they can boost well-being among the elderly, robots have shown little evidence that they make life easier for human caregivers. In fact, they require quite a bit of care themselves. Perhaps robots of the future will revolutionize caregiving as hoped. But the care robots we have now don’t even come close, and might even exacerbate the problems they’re meant to solve…(More)”.