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Truth and Cognitive Division of Labour: First Steps Towards a Computer Aided Social Epistemology

The paper analyzes the chances for the truth to be found and broadly accepted under conditions of cognitive division of labour combined with a social exchange process. Cognitive division of labour means, that only some individuals are active truth seekers, possibly with different capacities. The social exchange process consists in an exchange of opinions between all individuals, whether truth seekers or not. We de- velop a model which is investigated by both, mathematical tools and computer simulations. As an analytical result the Funnel theorem states that under rather weak conditions on the social process a consensus on the truth will be reached if all individuals posses an arbitrarily small inclination for truth seeking. The Leading the pack theorem states that under certain conditions even a single truth seeker may lead all individuals to the truth. Systematic simulations analyze how close and how fast groups can get to the truth depending on the frequency of truth seekers, their capacities as truth seekers, the position of the truth (more to the extreme or more in the centre of an opinion space), and the willingness to take into account the opinions of others when exchanging and updating opinions. A tricky movie visualizes simulations results in a parameter space of higher dimensions.Opinion Dynamics, Consensus/dissent, Bounded Confidence, Truth, Social Epistemology

Opinion Dynamics and Bounded Confidence Models, Analysis and Simulation

When does opinion formation within an interacting group lead to consensus, polarization or fragmentation? The article investigates various models for the dynamics of continuous opinions by analytical methods as well as by computer simulations. Section 2 develops within a unified framework the classical model of consensus formation, the variant of this model due to Friedkin and Johnsen, a time-dependent version and a nonlinear version with bounded confidence of the agents. Section 3 presents for all these models major analytical results. Section 4 gives an extensive exploration of the nonlinear model with bounded confidence by a series of computer simulations. An appendix supplies needed mathematical definitions, tools, and theorems.opinion dynamics, consensus/dissent, bounded confidence, nonlinear dynamical systems.

Bounded confidence, radical groups, and charismatic leaders

By few simple extensions it is possible to model radical groups, charismatic leaders and processes of radicalization in the bounded confidence framework. In the resulting model we get a lot of surprising (non-)monotonicities. In certain regions of the parameter space more radicals or more 'charismaticity' may lead to less radicalisation

Meinungsbildung in Gruppen: Wie tragfaehig sind vereinfachende Modellierungsansaetze?

The article describes a radically simplifying model of opinion formation processes. The model abstracts away almost everything. A very common reaction to such an approach is the objection that important factors are not included. The article anticipates ten objections of this type and tries to show how to cope with them without giving up the radically simplifying approach. The strategies that we use can be summarized to a certain heuristics. Following the principles of this heuristics will often allow at least a partial qualitative understanding of real world phenomena. In many areas we probably cannot hope for more.opinion formation

Optimal Opinion Control: The Campaign Problem

Opinion dynamics is nowadays a very common field of research. In this article we formulate and then study a novel, namely strategic perspective on such dynamics: There are the usual normal agents that update their opinions, for instance according the well-known bounded confidence mechanism. But, additionally, there is at least one strategic agent. That agent uses opinions as freely selectable strategies to get control on the dynamics: The strategic agent of our benchmark problem tries, during a campaign of a certain length, to influence the ongoing dynamics among normal agents with strategically placed opinions (one per period) in such a way, that, by the end of the campaign, as much as possible normals end up with opinions in a certain interval of the opinion space. Structurally, such a problem is an optimal control problem. That type of problem is ubiquitous. Resorting to advanced and partly non-standard methods for computing optimal controls, we solve some instances of the campaign problem. But even for a very small number of normal agents, just one strategic agent, and a ten-period campaign length, the problem turns out to be extremely difficult. Explicitly we discuss moral and political concerns that immediately arise, if someone starts to analyze the possibilities of an optimal opinion control.Comment: 47 pages, 12 figures, and 11 table

Tight Bounds for Asymptotic and Approximate Consensus

We study the performance of asymptotic and approximate consensus algorithms under harsh environmental conditions. The asymptotic consensus problem requires a set of agents to repeatedly set their outputs such that the outputs converge to a common value within the convex hull of initial values. This problem, and the related approximate consensus problem, are fundamental building blocks in distributed systems where exact consensus among agents is not required or possible, e.g., man-made distributed control systems, and have applications in the analysis of natural distributed systems, such as flocking and opinion dynamics. We prove tight lower bounds on the contraction rates of asymptotic consensus algorithms in dynamic networks, from which we deduce bounds on the time complexity of approximate consensus algorithms. In particular, the obtained bounds show optimality of asymptotic and approximate consensus algorithms presented in [Charron-Bost et al., ICALP'16] for certain dynamic networks, including the weakest dynamic network model in which asymptotic and approximate consensus are solvable. As a corollary we also obtain asymptotically tight bounds for asymptotic consensus in the classical asynchronous model with crashes. Central to our lower bound proofs is an extended notion of valency, the set of reachable limits of an asymptotic consensus algorithm starting from a given configuration. We further relate topological properties of valencies to the solvability of exact consensus, shedding some light on the relation of these three fundamental problems in dynamic networks

Certified Coronavirus Immunity as a Resource and Strategy to Cope with Pandemic Costs

A pandemic is not only a biological event and a public health disaster, but it also generates impacts that are worth understanding from economic, societal, historical, and cultural perspectives. In this contribution, we argue that as the disease spreads, we are able to harness a valuable key resource: people who have immunity to coronavirus. This vital resource must be effectively employed, it must be certified, it must be searched for, it must be found, and it may even be actively produced. We discuss why this needs to be done and how this can be achieved. Our arguments not only apply to the current pandemic but also to any future rapidly spreading, infectious disease epidemics. In addition, we argue for high awareness of a major secondary, nonbiological crisis arising from the side effects of societal and economic pandemic reactions to actual or imagined health risks. There is a risk that the impacts of the secondary crisis could outweigh that of the biological event.</p

Scientists have favorable opinions on immunity certificates but raise concerns regarding fairness and inequality

Abstract During the first wave of the COVID-19 pandemic, we collected over 12,000 responses from a survey of scientists, who were asked to express their opinions on immunity certificates (also called “immunity passports”) as a potential instrument to lessen the impact of the crisis. Overall, we find that scientists perceive immunity certificates as favorable for public health (50.2%) and the state of the economy (54.4%) while one-fifth (19.1%) and one-sixth (15.4%) disagree. Scientists stipulate some concerns about fairness (36.5%) and inequality (22.4%) arising from implementation of immunity certification. We find some smaller differences among scientific fields, particularly between health scientists and social scientists, with the latter being slightly more positive about the effect of immunity certification. Scholars in the United States, including health scientists, are more likely to view the immunity certificates favorably and mention fewer concerns about this policy’s effect on fairness and inequality. Female scholars are significantly less in favor of immunity certificates, while scientists with more conservative political views hold more favorable opinions. Our results reveal that given the uncertainties during an early phase of a pandemic, scientists see scope for immunity certification to lessen the general societal impacts of the crisis