Epistemic Communities under Active Inference

The spread of ideas is a fundamental concern of today’s news ecology. Understanding the dynamics of the spread of information and its co-option by interested parties is of critical importance. Research on this topic has shown that individuals tend to cluster in echo-chambers and are driven by confirmation bias. In this paper, we leverage the active inference framework to provide an in silico model of confirmation bias and its effect on echo-chamber formation. We build a model based on active inference, where agents tend to sample information in order to justify their own view of reality, which eventually leads to them to have a high degree of certainty about their own beliefs. We show that, once agents have reached a certain level of certainty about their beliefs, it becomes very difficult to get them to change their views. This system of self-confirming beliefs is upheld and reinforced by the evolving relationship between agent's beliefs and its observations, which over time will continue to provide evidence for their ingrained ideas about the world. The epistemic communities that are consolidated by these shared beliefs, in turn, tend to produce perceptions of reality that reinforce those shared beliefs. We provide an active inference account of this community formation mechanism. We postulate that agents are driven by the epistemic value that they obtain from sampling or observing the behaviors of other agents. Inspired by digital social networks like Twitter, we build a generative model in which agents generate observable social claims or posts (e.g. `tweets') while reading the socially-observable claims of other agents, that lend support towards one of two mutually-exclusive abstract topics. Agents can choose which other agent they pay attention to at each timestep, and crucially who they attend to and what they choose to read influences their beliefs about the world. Agents also assess their local network’s perspective, influencing which kinds of posts they expect to see other agents making. The model was built and simulated simulated using the freely-available Python package pymdp. The proposed active inference model can reproduce the formation of echo-chambers over social networks, and gives us insight into the cognitive processes that lead to this phenomenon.

Open science and the academic profession

Open science is considered a new science paradigm to make research accessible, accountable, and effective. Open science is already changing the academic profession starting from micro-practices to professional relations with epistemic communities and stakeholders, with implications that we are not yet able to predict. The article delves first into literature and official documentation to unfold the discursive regimes which sustain the spread of open science. A specific focus is then devoted to the professional transition, highlighting the role of funding organizations in setting the new science environment and the subjective experience of academics. The article is completed by a case study in the field of Research Data Management where the misalignment among incumbent/changing processes can be more apparent. Finally, a research agenda that focuses on how academic micro-practices are affecting organizations and science structures is proposed. This article aims at beginning to plow the ground for new research directions to emerge.

Global Authenticity, Local Authority: Epistemic Power, Discursive Geographies, and the Creation of Civil Society Knowledge Networks

How do networks of civil society organizations spread and contest ideas around the globe? This chapter focuses the ways practitioners within development-focused civil society organizations use spatial discursive practices to label, organize, defend, and undermine the spread and application of ideas. In particular, I look at the way members of civil society organizations defend and promote ideas as authentic and/or authoritative, navigating the need to have their knowledge and practices accepted both by beneficiaries and elite international epistemic communities. I draw on ethnographic fieldwork with two multi-sited case studies of civil society organizations, ranging from global foundations in the USA and Switzerland to their national and regional NGO partners in Kenya and Kyrgyzstan. Actors in both of these networks defend a varied array of ideas that underpin their ecological interventions through invocations of local particularity and global expertise. This chapter thus addresses the ways epistemic communities are formed and knowledge is produced and legitimized via discursive geographies and identities.

A Sociology of Interdisciplinarity

In building upon the cases presented in Chaps. 10.1007/978-3-030-88455-0_2, 10.1007/978-3-030-88455-0_3, and 10.1007/978-3-030-88455-0_4, we develop a Sociology of Interdisciplinarity that draws our empirical insights together with resources from Science and Technology Studies (STS), in addition to Sociology of Scientific Knowledge, Research Policy, Infrastructure Studies, Anthropology, and Philosophy of Science. The key novelty of this framework is using STS insights to unpick the dynamics and consequences of interdisciplinary science, which distinguishes us from decades of earlier interdisciplinarity studies and gaps in understanding. Moreover, we not only focus on individual scholars and their experiences but pay careful attention to the wider contexts of interdisciplinary research, such as the impacts of funding structures, different access to resources, and power relations. We are careful in our approach so that our units of analyses—which vary from research groups and projects to whole epistemic communities and research policies—are most appropriate for the problem definitions that we put forward. The framework rests on a set of six dimensions, which we discuss in relation to current debates in the literature and our empirical analyses.

Evidentiary vacuum, epistemic communities and rare disease policymaking in India: an evolutionary policy perspective

There are divergent views among scholars and policymakers about the nature of permissible evidence for policymaking. It is often not feasible to construct a policy system exclusively based on objective research findings, particularly for rare diseases where conventionally accepted evidence remains a rarity. Evolutionary theories in such cases offer an overarching framework to represent the various heterodox understandings of what constitutes evidence and how evidence-based policies can be formulated under knowledge uncertainty. We conduct an empirical investigation of India’s rare disease policymaking endeavour in evolutionary perspective. The existing rare diseases policy architecture in India, in our view, reflects a ‘rationalistic’ framework. It intends to act only on ‘hard evidence’ to make, what may be called, an optimum decision, rather than initiating a ‘good enough’ policy decision based on existing (limited, soft) evidence and improving it incrementally through learning and trial-and-error. Our findings suggest that in the presence of ‘evidentiary vacuum’ and knowledge uncertainty, broadening the contours of epistemic communities, to include ‘lived experiences’ of the ‘lay’-stakeholders, can be effective in formulating an adaptive policy framework, which would ‘learn’ to better fit with the dynamic environment through inclusive deliberations, and trial-and-error.

What Should We Do as Intellectual Activists? A Comment on the Ethico-political in Knowledge Production

This research comment makes an argument on the need to develop epistemic communities of belonging. These are spaces facilitating conversations about and enabling transformative ethico-political research. A research practice that can invoke attentiveness, responsibility, curiosity, and awareness to the field we study. Rather than answering what we should do as intellectual activists to maintain ethically integrity, the author here investigates the spaces we may develop as intellectual activists. Based on her work in the transformative collective initiative, the Asylum Commission and the reading of the Caring for Big Data book, the author proposes two concepts that are valuable for the creation of such spaces: epistemic injustice and hope.

Foundations and Applications of Social Epistemology

This book collects twelve recent papers by the author on social epistemology. Roughly half of them propose a research program for social epistemology—including an animating vision, foundational questions, and core concepts—and the other half are applications of this vision to particular topics. The author characterizes the research program itself as the exploration of the epistemic significance of other minds. Such a program will enumerate the various ways in which we depend epistemically on others, it will describe the proper way to evaluate beliefs according to the sort of dependence they exhibit, and it will provide the basis for identifying and characterizing various dysfunctions of our epistemic communities. The book suggests that several core concepts will be helpful as part of this exploration: epistemic dependence (direct and diffuse); entitlements (epistemic as well as those deriving from our social practices); the normative expectations we have of one another as epistemic subjects; and the socio-epistemic practices in which we participate. It goes on to put this program and these concepts into practice by exploring such topics as the epistemic agency exhibited in inquiry, the practices that constitute news coverage, the basis for allegations of what we or others should have known, how reliance on another’s testimony contrasts with reliance on an instrument, our reliance on others as consumers of testimony, and the epistemic upshot of non-epistemic social norms (whether these are moral, political, professional, or relationship-based).