The news media is a critical source of information for the public. However, it neglects the interests of the poor. In this paper, we explore why this happens, why it matters, and what might be done about it. As to why this happens, we identify two main reasons: because of the way that media is funded and because of the composition of its journalists and its sources. As to why this matters, we argue that this neglect is problematic for three (...) main reasons: it deprives the poor of vital information; it contributes to public support for or acceptance of policies that harm the interests of the poor; and it undermines political equality. And as to what might be done about it, we suggest two proposals: proposals that change the composition of who makes the news and proposals that change how the media is funded. (shrink)

Large language models (LLMs) represent the currently most relevant incarnation of artificial intelligence with respect to the future fate of democratic governance. Considering their potential, this paper seeks to answer a pressing question: Could LLMs outperform humans as expert advisors to democratic assemblies? While bearing the promise of enhanced expertise availability and accessibility, they also present challenges of hallucinations, misalignment, or value imposition. Weighing LLMs’ benefits and drawbacks compared to their human counterparts, I argue for their careful integration to augment (...) democracy’s ability to address complex policy issues. The paper posits that time-tested democratic procedures like deliberation and aggregation by voting provide safeguards effective against both human and machine advisor imperfections. Additional protective measures include custom LLM training for the advisory role, boosting representatives’ competencies in query formulation, or implementation of adversarial proceedings in which LLM advisors could debate each other and provide dissenting opinions. These could further mitigate the risks that LLMs present in advisory roles and empower human decision-makers toward increased autonomy and quality of their collective choices. My conceptual exploration offers a roadmap for the co-evolution of AI and democratic institutions, setting the stage for an empirical research agenda to finetune the implementation specifics. (shrink)

In several countries, governments have implemented so-called ‘COVID passport’ schemes, which restrict access to venues such as bars or sports events to those who are vaccinated against COVID-19 and/or exempt vaccinated individuals from public health measures such as curfews or quarantine requirements. These schemes have been the subject of a heated debate. Concerns about inequality have played an important role in the opposition to such schemes. This article highlights that determining how COVID passports affect equality requires a much more nuanced (...) analysis than is typically assumed. I identify a range of broadly egalitarian considerations that could be affected by the introduction of COVID passport schemes. While these schemes could undermine certain aspects of equality, I argue that they could also be used to promote equality. The magnitude and severity of these different effects, both promoting and undermining equality, depend on how precisely these schemes are framed and the local context in which they are implemented. (shrink)

Journal of Social Philosophy, EarlyView.

Many democratic countries have failed to stand up to the challenge presented by the COVID-19 pandemic. I argue that the collective response to the pandemic has been incapacitated by an ‘epistemic crisis’, (i.e., a breakdown in the social division of epistemic labor) that led to a failure of citizens’ beliefs to converge towards a shared perception of the situation. Neither a paucity of relevant expert knowledge nor democratic citizens’ irrationality is required for the crisis to emerge. In particular, I highlight (...) three obstacles capable of preventing relevant expert testimony from gaining democratic legitimacy necessary for an effective policy response: 1) the proper domain of expertise is uncertain; 2) regular citizens’ meta-expertise – (i.e., ability to discriminate among the putative experts based on their relative epistemic merit) – is not efficacious enough to trigger truth-convergence of the public opinion; 3) the prominent sources of third-party meta-expertise lack credibility due to their conflicts of interest. Since the first two problems appear irresolvable, I propose that the search for a path towards preclusion of future epistemic crises concentrates on upgrading the institutional fundament for meta-expertise provision. Social epistemology plays a vital role in this search, but its close cooperation with other disciplines is a must. (shrink)

This article develops an account of distributive epistemic justice in the production of scientific knowledge. We identify four requirements: (a) science should produce the knowledge citizens need in order to reason about the common good, their individual good and pursuit thereof; (b) science should produce the knowledge those serving the public need to pursue justice effectively; (c) science should be organized in such a way that it does not aid the wilful manufacturing of ignorance; and (d) when making decisions about (...) epistemic risks, scientists should make sure that there aren’t social groups or weighty interests that are neglected. After discussing these requirements, we examine the relationship between discriminatory and distributive epistemic injustice in science and argue that they often compound each other. (shrink)

The setting of evidential standards is a core practice of scientific assessment for policy. Persuaded by considerations of inductive risk, philosophers generally agree that the justification of evidential standards must appeal to non-epistemic values but debate whether the balance of non-epistemic reasons favours varying evidential standards versus maintaining fixed high evidential standards in assessment, as both sets of standards promote different and important political virtues of advisory institutions. In this paper, I adjudicate the evidential standards debate by developing a novel (...) argument from justice, drawing on the IPCC’s assessment of climate impacts as a case study. I argue that in assessments marked by background evidential inequality, maintaining fixed high evidential standards results in an unequal distribution of ‘epistemic power’ among stakeholders, producing a ‘powerful assessment’ for the data-rich (a high rate of findings) and a ‘weak assessment’ for the data-poor (a low rate of findings). Where such inequalities of epistemic power disadvantage those in data-poor regions with respect to fundamental interests, such as basic human rights, we have decisive reasons of justice to vary evidential standards. (shrink)

Take a question like the safety and effectiveness of COVID-19 vaccines. Whether an ordinary citizen or a public official can acquire the correct answer to this question depends on the functioning of the epistemic basic structure of their society. The epistemic basic structure of a society consists of “the institutions that have a crucial role in the distribution of knowledge, that is, in the production and dissemination of knowledge, and in ensuring that people have the capability to assimilate what is (...) disseminated by providing them with the necessary educational background and intellectual skills”. It includes institutions of science and education, the media, search engines, libraries, museums, think tanks, and various government agencies. (shrink)