EBP+: Integrating science into policy evaluation using Evidential Pluralism

Curated on Posted on by Stefaan Verhulst

Article by Joe Jones, Alexandra Trofimov, Michael Wilde & Jon Williamson: “…While the need to integrate scientific evidence in policymaking is clear, there isn’t a universally accepted framework for doing so in practice. Orthodox evidence-based approaches take Randomised Controlled Trials (RCTs) as the gold standard of evidence. Others argue that social policy issues require theory-based methods to understand the complexities of policy interventions. These divisions may only further decrease trust in science at this critical time.

EBP+ offers a broader framework within which both orthodox and theory-based methods can sit. EBP+ also provides a systematic account of how to integrate and evaluate these different types of evidence. EBP+ can offer consistency and objectivity in policy evaluation, and could yield a unified approach that increases public trust in scientifically-informed policy…

EBP+ is motivated by Evidential Pluralism, a philosophical theory of causal enquiry that has been developed over the last 15 years. Evidential Pluralism encompasses two key claims. The first, object pluralism, says that establishing that A is a cause of B (e.g., that a policy intervention causes a specific outcome) requires establishing both that A and B are appropriately correlated and that there is some mechanism which links the two and which can account for the extent of the correlation. The second claim, study pluralism, maintains that assessing whether A is a cause of B requires assessing both association studies (studies that repeatedly measure A and B, together with potential confounders, to measure their association) and mechanistic studies (studies of features of the mechanisms linking A to B), where available…(More)”.

A diagrammatic representation of Evidential Pluralism
Evidential Pluralism (© Jon Williamson)

The Non-Coherence Theory of Digital Human Rights

Curated on Posted on by Stefaan Verhulst

Book by Mart Susi: “…offers a novel non-coherence theory of digital human rights to explain the change in meaning and scope of human rights rules, principles, ideas and concepts, and the interrelationships and related actors, when moving from the physical domain into the online domain. The transposition into the digital reality can alter the meaning of well-established offline human rights to a wider or narrower extent, impacting core concepts such as transparency, legal certainty and foreseeability. Susi analyses the ‘loss in transposition’ of some core features of the rights to privacy and freedom of expression. The non-coherence theory is used to explore key human rights theoretical concepts, such as the network society approach, the capabilities approach, transversality, and self-normativity, and it is also applied to e-state and artificial intelligence, challenging the idea of the sameness of rights…(More)”.

The Need for Climate Data Stewardship: 10 Tensions and Reflections regarding Climate Data Governance

Curated on Posted on by Stefaan Verhulst

Paper by Stefaan Verhulst: “Datafication — the increase in data generation and advancements in data analysis — offers new possibilities for governing and tackling worldwide challenges such as climate change. However, employing new data sources in policymaking carries various risks, such as exacerbating inequalities, introducing biases, and creating gaps in access. This paper articulates ten core tensions related to climate data and its implications for climate data governance, ranging from the diversity of data sources and stakeholders to issues of quality, access, and the balancing act between local needs and global imperatives. Through examining these tensions, the article advocates for a paradigm shift towards multi-stakeholder governance, data stewardship, and equitable data practices to harness the potential of climate data for public good. It underscores the critical role of data stewards in navigating these challenges, fostering a responsible data ecology, and ultimately contributing to a more sustainable and just approach to climate action and broader social issues…(More)”.

Meta Kills a Crucial Transparency Tool At the Worst Possible Time

Curated on Posted on by Stefaan Verhulst

Interview by Vittoria Elliott: “Earlier this month, Meta announced that it would be shutting down CrowdTangle, the social media monitoring and transparency tool that has allowed journalists and researchers to track the spread of mis- and disinformation. It will cease to function on August 14, 2024—just months before the US presidential election.

Meta’s move is just the latest example of a tech company rolling back transparency and security measures as the world enters the biggest global election year in history. The company says it is replacing CrowdTangle with a new Content Library API, which will require researchers and nonprofits to apply for access to the company’s data. But the Mozilla Foundation and 140 other civil society organizations protested last week that the new offering lacks much of CrowdTangle’s functionality, asking the company to keep the original tool operating until January 2025.

Meta spokesperson Andy Stone countered in posts on X that the groups’ claims “are just wrong,” saying the new Content Library will contain “more comprehensive data than CrowdTangle” and be made available to nonprofits, academics, and election integrity experts. When asked why commercial newsrooms, like WIRED, are to be excluded from the Content Library, Meta spokesperson Eric Porterfield said,  that it was “built for research purposes.” While journalists might not have direct access he suggested they could use commercial social network analysis tools, or “partner with an academic institution to help answer a research question related to our platforms.”

Brandon Silverman, cofounder and former CEO of CrowdTangle, who continued to work on the tool after Facebook acquired it in 2016, says it’s time to force platforms to open up their data to outsiders. The conversation has been edited for length and clarity…(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)”.

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)”.

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)”.

Facial Recognition Technology: Current Capabilities, Future Prospects, and Governance

Curated on Posted on by Stefaan Verhulst

Report by the National Academies of Sciences, Engineering, and Medicine: “Facial recognition technology is increasingly used for identity verification and identification, from aiding law enforcement investigations to identifying potential security threats at large venues. However, advances in this technology have outpaced laws and regulations, raising significant concerns related to equity, privacy, and civil liberties.

This report explores the current capabilities, future possibilities, and necessary governance for facial recognition technology. Facial Recognition Technology discusses legal, societal, and ethical implications of the technology, and recommends ways that federal agencies and others developing and deploying the technology can mitigate potential harms and enact more comprehensive safeguards…(More)”.