Achieving descriptive accuracy in explanations via argumentation: the case of probabilistic classifiers

The pursuit of trust in and fairness of AI systems in order to enable human-centric goals has been gathering pace of late, often supported by the use of explanations for the outputs of these systems. Several properties of explanations have been highlighted as critical for achieving trustworthy and fair AI systems, but one that has thus far been overlooked is that of descriptive accuracy (DA), i.e., that the explanation contents are in correspondence with the internal working of the explained system. Indeed, the violation of this core property would lead to the paradoxical situation of systems producing explanations which are not suitably related to how the system actually works: clearly this may hinder user trust. Further, if explanations violate DA then they can be deceitful, resulting in an unfair behavior toward the users. Crucial as the DA property appears to be, it has been somehow overlooked in the XAI literature to date. To address this problem, we consider the questions of formalizing DA and of analyzing its satisfaction by explanation methods. We provide formal definitions of naive, structural and dialectical DA, using the family of probabilistic classifiers as the context for our analysis. We evaluate the satisfaction of our given notions of DA by several explanation methods, amounting to two popular feature-attribution methods from the literature, variants thereof and a novel form of explanation that we propose. We conduct experiments with a varied selection of concrete probabilistic classifiers and highlight the importance, with a user study, of our most demanding notion of dialectical DA, which our novel method satisfies by design and others may violate. We thus demonstrate how DA could be a critical component in achieving trustworthy and fair systems, in line with the principles of human-centric AI

Explaining classifiers’ outputs with causal models and argumentation

We introduce a conceptualisation for generating argumentation frameworks (AFs) from causal models for the purpose of forging explanations for mod-els’ outputs. The conceptualisation is based on reinterpreting properties of semantics of AFs as explanation moulds, which are means for characterising argumentative relations. We demonstrate our methodology by reinterpreting the property of bi-variate reinforcement in bipolar AFs, showing how the ex-tracted bipolar AFs may be used as relation-based explanations for the outputs of causal models. We then evaluate our method empirically when the causal models represent (Bayesian and neural network) machine learning models for classification. The results show advantages over a popular approach from the literature, both in highlighting specific relationships between feature and classification variables and in generating counterfactual explanations with respect to a commonly used metric

Tio2-photocatalyzed water depollution, a strong, yet selective depollution method: New evidence from the solar light induced degradation of glucocorticoids in freshwaters

The photodegradation of the most prescribed glucocorticoids (GCs) was studied under relevant environmental conditions in the presence of suspended TiO2. The considered drugs in-cluded cortisone (CORT), hydrocortisone (HCORT), betamethasone (BETA), dexamethasone (DEXA), prednisone (PRED), prednisolone (PREDLO), and triamcinolone (TRIAM). The experiments were carried out at concentrations (50 µg L−1) close to the real ones in freshwater samples (tap and river) under simulated and natural sunlight, and their decomposition took place very efficiently under natural sunlight. The reactions were monitored by high-pressure liquid chromatography coupled to electrospray ionization tandem mass spectrometry (HPLC-ESI-MS/MS). According to a pseudo-first-order decay, all drugs underwent degradation within 15 min, following different paths with respect to the direct photolysis. The observed kinetic constants, slightly lower in river than in tap water, varied from 0.29 to 0.61 min−1 with modest differences among GCs in the same matrix. Among main matrix macro-constituents, humic acids (HAs) were the most interfering species involved in GCs degradation. The photogenerated primary products were identified by HPLC-ESI-MS/MS, allowing to elucidate the general photochemical path of GCs. Finally, a comparison with literature data obtained using different advanced oxidation processes (AOPs) highlights the treatment efficiency with TiO2 /solar light for removing such persistent aquatic contaminants

Cancer prevention by targeting angiogenesis

Healthy individuals can harbour microscopic tumours and dysplastic foci in different organs in an undetectable and asymptomatic state for many years. These lesions do not progress in the absence of angiogenesis or inflammation. Targeting both processes before clinical manifestation can prevent tumour growth and progression. Angioprevention is a chemoprevention approach that interrupts the formation of new blood vessels when tumour cell foci are in an indolent state. Many efficacious chemopreventive drugs function by preventing angiogenesis in the tumour microenvironment. Blocking the vascularization of incipient tumours should maintain a dormancy state such that neoplasia or cancer exist without disease. The current limitations of antiangiogenic cancer therapy may well be related to the use of antiangiogenic agents too late in the disease course. In this Review, we suggest mechanisms and strategies for using antiangiogenesis agents in a safe, preventive clinical angioprevention setting, proposing different levels of clinical angioprevention according to risk, and indicate potential drugs to be employed at these levels. Finally, angioprevention may go well beyond cancer in the prevention of a range of chronic disorders where angiogenesis is crucial, including different forms of inflammatory or autoimmune diseases, ocular disorders, and neurodegeneration

Vibrational spectrum of solid picene (C_22H_14)

Recently, Mitsuhashi et al., have observed superconductivity with transition temperature up to 18 K in potassium doped picene (C22H14), a polycyclic aromatic hydrocarbon compound [Nature 464 (2010) 76]. Theoretical analysis indicate the importance of electron-phonon coupling in the superconducting mechanisms of these systems, with different emphasis on inter- and intra-molecular vibrations, depending on the approximations used. Here we present a combined experimental and ab-initio study of the Raman and infrared spectrum of undoped solid picene, which allows us to unanbiguously assign the vibrational modes. This combined study enables the identification of the modes which couple strongly to electrons and hence can play an important role in the superconducting properties of the doped samples

Interpreting and explaining pagerank through argumentation semantics

In this paper we show how re-interpreting PageRank as an argumentation semantics for a bipolar argumentation framework empowers its explainability. After showing that PageRank, naively re-interpreted as an argumentation semantics for support frameworks, fails to satisfy some generally desirable properties, we propose a novel approach able to reconstruct PageRank as a gradual semantics of a suitably defined bipolar argumentation framework, while satisfying these properties. We then show how the theoretical advantages afforded by this approach also enjoy an enhanced explanatory power: we propose several types of argument-based explanations for PageRank, each of which focuses on different aspects of the algorithm and uncovers information useful for the comprehension of its results

Mathematical modelling of the spread of contamination during fires in forests exposed to radioactive contamination

The paper suggested in the context of the general mathematical model of forest fires [1] gives a new mathematical setting and method of numerical solution of a problem of a radioactive spread above the forest region. Numerical solution of problems of radioactive smoke spread during crown fire in exemplified heat energy release in the forest fire front was found. Heat energy release in the forest fire front was found to cause further radioactive particles spread by the action of wind. In the absence of wind, radioactive smoke particles deposit again on the underlying surface after a time. As a wind velocity increases, these particles are transferred in the ground layer over distances proportional to a wind velocity

Argflow: a toolkit for deep argumentative explanations for neural networks

In recent years, machine learning (ML) models have been successfully applied in a variety of real-world applications. However, they are often complex and incomprehensible to human users. This can decrease trust in their outputs and render their usage in critical settings ethically problematic. As a result, several methods for explaining such ML models have been proposed recently, in particular for black-box models such as deep neural networks (NNs). Nevertheless, these methods predominantly explain outputs in terms of inputs, disregarding the inner workings of the ML model computing those outputs. We present Argflow, a toolkit enabling the generation of a variety of ‘deep’ argumentative explanations (DAXs) for outputs of NNs on classification tasks

Atrial Fibrillation in the Setting of Acute Pneumonia: Not a Secondary Arrhythmia

Atrial fibrillation (AF) is the most common arrhythmia in the setting of critically ill patients. Pneumonia, and in particular communityacquired pneumonia, is one of the most common causes of illness and hospital admission worldwide. This article aims to review the association between AF and acute diseases, with specific attention to pneumonia, from the pathophysiology to its clinical significance. Even though the relationship between pneumonia and AF has been known for years, it was once considered a transient bystander. In recent years there has been growing knowledge on the clinical significance of this arrhythmia in acute clinical settings, in which it holds a prognostic role which is not so different as compared to that of the so-called "primary"AF. AF is a distinct entity even in the setting of pneumonia, and acute critical illnesses in general, and it should therefore be managed with a guidelines-oriented approach, including prescription of anticoagulants in patients at thromboembolic risk, always considering patients' individuality. More data on the significance of the arrhythmia in this setting will help clinicians to give patients the best possible care