How much do you trust me? A logico-mathematical analysis of the concept of the intensity of trust

Trust and monitoring are traditionally antithetical concepts. Describing trust as a property of a relationship of reliance, we introduce a theory of trust and monitoring, which uses mathematical models based on two classes of functions, including q-exponentials, and relates the levels of trust to the costs of monitoring. As opposed to several accounts of trust that attempt to identify the special ingredient of reliance and trust relationships, our theory characterizes trust as a quantitative property of certain relations of reliance that can be quantified and expressed as a scalar quantity. Our theory is applicable to both human–human and human–artificial agent interactions, as it is agnostic with respect to the concrete realization of trustworthiness properties, and is compatible with many views differing on which properties contribute to trust and trustworthiness. Finally, as our mathematical models make the quantitative features of trust measurable, they provide empirical studies on trust with a rigorous methodology for its measurement

How I Would have been Differently Treated: Discrimination Through the Lens of Counterfactual Fairness

The widespread use of algorithms for prediction-based decisions urges us to consider the question of what it means for a given act or practice to be discriminatory. Building upon work by Kusner and colleagues in the field of machine learning, we propose a counterfactual condition as a necessary requirement on discrimination. To demonstrate the philosophical relevance of the proposed condition, we consider two prominent accounts of discrimination in the recent literature, by Lippert-Rasmussen and Hellman respectively, that do not logically imply our condition and show that they face important objections. Specifically, Lippert-Rasmussen’s definition proves to be over-inclusive, as it classifies some acts or practices as discriminatory when they are not, whereas Hellman’s account turns out to lack explanatory power precisely insofar as it does not countenance a counterfactual condition on discrimination. By defending the necessity of our counterfactual condition, we set the conceptual limits for justified claims about the occurrence of discriminatory acts or practices in society, with immediate applications to the ethics of algorithmic decision-making

People are not coins: Morally distinct types of predictions necessitate different fairness constraints

In a recent paper, Brian Hedden has argued that most of the group fairness constraints discussed in the machine learning literature are not necessary conditions for the fairness of predictions, and hence that there are no genuine fairness metrics. This is proven by discussing a special case of a fair prediction. In our paper, we show that Hedden's argument does not hold for the most common kind of predictions used in data science, which are about people and based on data from similar people; we call these “human-group-based practices.” We argue that there is a morally salient distinction between human-group-based practices and those that are based on data of only one person, which we call “human-individual-based practices.” Thus, what may be a necessary condition for the fairness of human-group-based practices may not be a necessary condition for the fairness of human-individual-based practices, on which Hedden's argument is based. Accordingly, the group fairness metrics discussed in the machine learning literature may still be relevant for most applications of prediction-based decision making

People are not coins: a reply to Hedden

This paper is a reply to "On Statistical Criteria of Algorithmic Fairness," by Brian Hedden. We question the significance of arguing that many group fairness criteria discussed in the machine learning literature are not necessary conditions for the fairness of predictions or decisions based on them. We show that it may be true, in general, that F is not a necessary condition for the fairness of all predictions (or decisions based on them). And yet, compatibly with this, most predictions or decisions involving people could be unfair if they violate the statistical fairness constraint F

DNA methylation alterations caused by Leishmania infection may generate a microenvironment prone to tumour development

DNA methylation is an epigenetic signature consisting of a methyl group at the 5' cytosine of CpG dinucleotides. Modifications in DNA methylation pattern have been detected in cancer and infectious diseases and may be associated with gene expression changes. In cancer development DNA methylation aberrations are early events whereas in infectious diseases these epigenetic changes may be due to host/pathogen interaction. In particular, in leishmaniasis, a parasitic disease caused by the protozoan Leishmania, DNA methylation alterations have been detected in macrophages upon infection with Leishmania donovani and in skin lesions from patients with cutaneous leishmaniasis. Interestingly, different types of cancers, such as cutaneous malignant lesions, lymphoma and hepatocellular carcinoma, have been diagnosed in patients with a history of leishmaniasis. In fact, it is known that there exists an association between cancer and infectious diseases. Leishmania infection may increase susceptibility to develop cancer, but the mechanisms involved are not entirely clear. Considering these aspects, in this review we discuss the hypothesis that DNA methylation alterations induced by Leishmania may trigger tumorigenesis in long term infection since these epigenetic modifications may enhance and accumulate during chronic leishmaniasis

A Justice-Based Framework for the Analysis of Algorithmic Fairness-Utility Trade-Offs

In prediction-based decision-making systems, different perspectives can be at odds: The short-term business goals of the decision makers are often in conflict with the decision subjects' wish to be treated fairly. Balancing these two perspectives is a question of values. However, these values are often hidden in the technicalities of the implementation of the decision-making system. In this paper, we propose a framework to make these value-laden choices clearly visible. We focus on a setting in which we want to find decision rules that balance the perspective of the decision maker and of the decision subjects. We provide an approach to formalize both perspectives, i.e., to assess the utility of the decision maker and the fairness towards the decision subjects. In both cases, the idea is to elicit values from decision makers and decision subjects that are then turned into something measurable. For the fairness evaluation, we build on well-known theories of distributive justice and on the algorithmic literature to ask what a fair distribution of utility (or welfare) looks like. This allows us to derive a fairness score that we then compare to the decision maker's utility. As we focus on a setting in which we are given a trained model and have to choose a decision rule, we use the concept of Pareto efficiency to compare decision rules. Our proposed framework can both guide the implementation of a decision-making system and help with audits, as it allows us to resurface the values implemented in a decision-making system

Ultra-Hypofractionation for Whole-Breast Irradiation in Early Breast Cancer: Interim Analysis of a Prospective Study

We report on the early clinical outcomes of a prospective series of early breast cancer (EBC) patients treated with ultra-hypofractionated post-operative whole-breast irradiation (WBI) after breast-conserving surgery (BCS) and axillary management. Primary endpoints were patient's compliance and acute toxicity. Secondary endpoints included physician-rated cosmesis and ipsilateral breast tumour recurrence (IBTR). Acute toxicity was evaluated at the end of WBI, 3 weeks and 6 months thereafter, according to the Common Terminology Criteria for Adverse Events (v. 5.0). Patients were treated between September 2021 and May 2022. The treatment schedule for WBI consisted of either 26 Gy in 5 fractions over one week (standard approach) or 28.5 Gy in 5 fractions over 5 weeks (reserved to elders). Inverse planned intensity-modulated radiation therapy (IMRT) was used employing a static technique. A total of 70 patients were treated. Fifty-nine were treated with the 26 Gy/5 fr/1 w and 11 with the 28.5 Gy/5 fr/5 ws schedule. Median age was 67 and 70 in the two groups. Most of the patients had left-sided tumours (53.2%) in the 26 Gy/5 fr/1 w or right-sided lesions (63.6%) in the 28.5 Gy/5 fr/5 ws group. Most of the patients had a clinical T1N0 disease and a pathological pT1pN0(sn) after surgery. Ductal invasive carcinoma was the most frequent histology. Luminal A intrinsic subtyping was most frequent. Most of the patients underwent BCS and sentinel lymph node biopsy and adjuvant endocrine therapy. All patients completed the treatment program as planned. Maximum detected acute skin toxicities were grade 2 erythema (6.7%), grade 2 induration (4.4%), and grade 2 skin colour changes. No early IBTR was observed. Ultra-hypofractionated WBI provides favourable compliance and early clinical outcomes in EBC after BCS in a real-world setting

Gene Methylation Affects Salivary Levels of the Taste Buds' Trophic Factor, Gustin Protein

The salivary protein, Gustin/carbonic anhydrase VI, has been described as a trophic factor responsible for the growth of taste buds. We found, in a genetically homogeneous population, that the polymorphism rs2274333 (A/G) of the Gustin gene is crucial for the full functionality of the protein and is associated with taste sensitivity. However, other studies have failed to find this evidence. Here, we verified if Gustin gene methylation can affect the salivary levels of the protein, also concerning the polymorphism rs2274333 and PROP bitter responsiveness. The Gustin gene methylation profiling and the quantification of the Gustin salivary levels were determined in sixty-six volunteers genotyped for the polymorphism rs2274333 (A/G) (Ser90Gly in the protein sequence). The fungiform papillae density was also determined. The results confirm our earlier observations by showing that AA genotypes had a greater density of fungiform taste papillae, whereas the GG genotypes showed a lower density. We also found variations in the protein levels in the three genotype groups and an inverse relationship between Gustin gene methylation and the salivary levels of the protein, mostly evident in AA and ST volunteers, i.e., in volunteers who would be carriers of the functional isoform of the protein. These findings could justify the conflicting data in the literature

Stereotactic ablative radiotherapy for oligometastatic prostate cancer

Background: The present study assessed clinical outcomes of stereotactic body radiotherapy (SBRT) in oligometastatic prostate cancer patients. Materials and methods: Between 2017 and 2020, 37 lesions (12 osseous and 25 nodal targets) detected with conventional and/or functional imaging, were treated in 29 patients (pts), in different clinical settings: de novo oligometastatic (2 pts), oligorecurrent castration-sensitive (19 pts), castration-resistant (6 pts) prostate cancers and oligoprogressive disease during systemic therapy (2 pts). SBRT was delivered with volumetric modulated arc therapy up to a total dose of 21 Gy given in 3 fractions for bone and 30 Gy in 5 fractions for nodal metastases. A total of 34% of pts received hormonal therapy. We evaluated biochemical control [prostate serum antigen (PSA) increase grade 2 was reported. Conclusions: SBRT for oligometastatic prostate cancer offers a good biochemical/local control and tangible delay of hormone/systemic therapy without major toxicities