The Argument for Democracy

This chapter defends an epistemic argument for democracy, namely the argument that the rule of the many is better at aggregating knowledge and, in the version presented here, at producing better decisions than the rule of the few. This argument builds on the formal properties of two key democratic decision-making mechanisms of democracy, namely inclusive deliberation on equal grounds and majority rule with universal suffrage. Properly used in sequence and under the right conditions, these two mechanisms ensure that no information and viewpoint is ignored and maximize the cognitive diversity brought to bear on collective political problems and predictions. Building on existing formal results by Lu Hong and Scott Page, the chapter introduces the “Number Trumps Ability” theorem, which formalizes the intuition that many minds are smarter than just a few. Under the right conditions systems governed by democratic decision-procedures can be expected to deliver greater epistemic performance than less inclusive and egalitarian systems.

Efficient Full Higher-Order Unification

We developed a procedure to enumerate complete sets of higher-order unifiers based on work by Jensen and Pietrzykowski. Our procedure removes many redundant unifiers by carefully restricting the search space and tightly integrating decision procedures for fragments that admit a finite complete set of unifiers. We identify a new such fragment and describe a procedure for computing its unifiers. Our unification procedure, together with new higher-order term indexing data structures, is implemented in the Zipperposition theorem prover. Experimental evaluation shows a clear advantage over Jensen and Pietrzykowski's procedure.

Tackling the DM Challenges with cDMN: A Tight Integration of DMN and Constraint Reasoning

Knowledge-based AI typically depends on a knowledge engineer to construct a formal model of domain knowledge – but what if domain experts could do this themselves? This paper describes an extension to the Decision Model and Notation (DMN) standard, called Constraint Decision Model and Notation (cDMN). DMN is a user-friendly, table-based notation for decision logic, which allows domain experts to model simple decision procedures without the help of IT staff. cDMN aims to enlarge the expressiveness of DMN in order to model more complex domain knowledge, while retaining DMNs goal of being understandable by domain experts. We test cDMN by solving the most complex challenges posted on the DM Community website. We compare our own cDMN solutions to the solutions that have been submitted to the website and find that our approach is competitive. Moreover, cDMN is able to solve more challenges than any other approach.

The problem of no hands: responsibility voids in collective decisions

The problem of no hands concerns the existence of so-called responsibility voids: cases where a group makes a certain decision, yet no individual member of the group can be held responsible for this decision. Criteria-based collective decision procedures play a central role in philosophical debates on responsibility voids. In particular, the well-known discursive dilemma has been used to argue for the existence of these voids. But there is no consensus: others argue that no such voids exist in the discursive dilemma under the assumption that casting an untruthful opinion is eligible. We argue that, under this assumption, the procedure used in the discursive dilemma is indeed immune to responsibility voids, yet such voids can still arise for other criteria-based procedures. We provide two general characterizations of the conditions under which criteria-based collective decision procedures are immune to these voids. Our general characterizations are used to prove that responsibility voids are ruled out by criteria-based procedures involving an atomistic or monotonic decision function. In addition, we show that our results imply various other insights concerning the logic of responsibility voids.

Complete Abstractions for Checking Language Inclusion

We study the language inclusion problem L 1 ⊆ L 2 , where L 1 is regular or context-free. Our approach relies on abstract interpretation and checks whether an overapproximating abstraction of L 1 , obtained by approximating the Kleene iterates of its least fixpoint characterization, is included in L 2 . We show that a language inclusion problem is decidable whenever this overapproximating abstraction satisfies a completeness condition (i.e., its loss of precision causes no false alarm) and prevents infinite ascending chains (i.e., it guarantees termination of least fixpoint computations). This overapproximating abstraction of languages can be defined using quasiorder relations on words, where the abstraction gives the language of all the words “greater than or equal to” a given input word for that quasiorder. We put forward a range of such quasiorders that allow us to systematically design decision procedures for different language inclusion problems, such as regular languages into regular languages or into trace sets of one-counter nets, and context-free languages into regular languages. In the case of inclusion between regular languages, some of the induced inclusion checking procedures correspond to well-known state-of-the-art algorithms, like the so-called antichain algorithms. Finally, we provide an equivalent language inclusion checking algorithm based on a greatest fixpoint computation that relies on quotients of languages and, to the best of our knowledge, was not previously known.

Unplanned Coordination: Ensemble Improvisation as Collective Action

The characteristic features of ensemble dance improvisation (EDI) make it an interesting case for theories of intentional collective action. These features include the high degree of freedom enjoyed by each individual, and the lack of fixed hierarchical roles, rigid decision procedures, or detailed plans. We present a “reductive” approach to collective action, apply it to EDI, and show how the theory enriches our perspective on this practice. We show, with the help of our theory of collective action, that EDI (as typically practiced) constitutes a significant collective achievement, one that manifests an impressive, spontaneous, jointly cooperative and individually highly autonomous activity that meets demanding aesthetic standards. Its being good in this way is not a mere extrinsic feature of the artwork, but part of its aesthetic value. We end by discussing how this value is easily missed by classic aesthetics, but is revealed by more contemporary frameworks like social aesthetics.

Ethical factors determining ECMO allocation during the COVID-19 pandemic

Background ECMO is a particularly scarce resource during the COVID-19 pandemic. Its allocation involves ethical considerations that may be different to usual times. There is limited pre-pandemic literature on the ethical factors that ECMO physicians consider during ECMO allocation. During the pandemic, there has been relatively little professional guidance specifically relating to ethics and ECMO allocation; although there has been active ethical debate about allocation of other critical care resources. We report the results of a small international exploratory survey of ECMO clinicians’ views on different patient factors in ECMO decision-making prior to and during the COVID-19 pandemic. We then outline current ethical decision procedures and recommendations for rationing life-sustaining treatment during the COVID-19 pandemic, and examine the extent to which current guidelines for ECMO allocation (and reported practice) adhere to these ethical guidelines and recommendations. Methods An online survey was performed with responses recorded between mid May and mid August 2020. Participants (n = 48) were sourced from the ECMOCard study group—an international group of experts (n = 120) taking part in a prospective international study of ECMO and intensive care for patients during the COVID-19 pandemic. The survey compared the extent to which certain ethical factors involved in ECMO resource allocation were considered prior to and during the pandemic. Results When initiating ECMO during the pandemic, compared to usual times, participants reported giving more ethical weight to the benefit of ECMO to other patients not yet admitted as opposed to those already receiving ECMO, (p < 0.001). If a full unit were referred a good candidate for ECMO, participants were more likely during the pandemic to consider discontinuing ECMO from a current patient with low chance of survival (53% during pandemic vs. 33% prior p = 0.002). If the clinical team recommends that ECMO should cease, but family do not agree, the majority of participants indicated that they would continue treatment, both in usual circumstances (67%) and during the pandemic (56%). Conclusions We found differences during the COVID-19 pandemic in prioritisation of several ethical factors in the context of ECMO allocation. The ethical principles prioritised by survey participants were largely consistent with ECMO allocation guidelines, current ethical decision procedures and recommendations for allocation of life-sustaining treatment during the COVID-19 pandemic.

The strategic biomarker roadmap for the validation of Alzheimer’s diagnostic biomarkers: methodological update

Background The 2017 Alzheimer’s disease (AD) Strategic Biomarker Roadmap (SBR) structured the validation of AD diagnostic biomarkers into 5 phases, systematically assessing analytical validity (Phases 1–2), clinical validity (Phases 3–4), and clinical utility (Phase 5) through primary and secondary Aims. This framework allows to map knowledge gaps and research priorities, accelerating the route towards clinical implementation. Within an initiative aimed to assess the development of biomarkers of tau pathology, we revised this methodology consistently with progress in AD research. Methods We critically appraised the adequacy of the 2017 Biomarker Roadmap within current diagnostic frameworks, discussed updates at a workshop convening the Alzheimer’s Association and 8 leading AD biomarker research groups, and detailed the methods to allow consistent assessment of aims achievement for tau and other AD diagnostic biomarkers. Results The 2020 update applies to all AD diagnostic biomarkers. In Phases 2–3, we admitted a greater variety of study designs (e.g., cross-sectional in addition to longitudinal) and reference standards (e.g., biomarker confirmation in addition to clinical progression) based on construct (in addition to criterion) validity. We structured a systematic data extraction to enable transparent and formal evidence assessment procedures. Finally, we have clarified issues that need to be addressed to generate data eligible to evidence-to-decision procedures. Discussion This revision allows for more versatile and precise assessment of existing evidence, keeps up with theoretical developments, and helps clinical researchers in producing evidence suitable for evidence-to-decision procedures. Compliance with this methodology is essential to implement AD biomarkers efficiently in clinical research and diagnostics.