Metrics for Identifying Bias in Datasets

Nowadays automated decision-making systems are pervasively used and more often, they are used for taking important decisions in sensitive areas such as the granting of a bank overdraft, the susceptibility of an individual to a virus infection, or even the likelihood of repeating a crime. The widespread use of these systems raises a growing ethical concern about the risk of a potential discriminatory impact. In particular, machine-learning systems trained on unbalanced data could rise to systematic discriminations in the real world. One of the most important challenges is to determine metrics capable of detecting when an unbalanced training dataset may lead to discriminatory behaviour of the model built on it. In this paper, we propose an approach based on the notion of data completeness using two different metrics: one based on the combinations of the values of the dataset, which will be our benchmark, and the second using frame theory, widely used among others for quality measures of control systems. It is important to remark that the use of metrics cannot be a substitute for a broader design that must take into account the columns that could lead to the presence of bias in the data. The line of research does not end with these activities but aims to continue the path towards a standardised register of measures

Integrating SQuARE data quality model with ISO 31000 risk management to measure and mitigate software bias

In the last decades the exponential growth of available information, together with the availability of systems able to learn the knowledge that is present in the data, has pushed towards the complete automation of many decision- making processes in public and private organizations. This circumstance is posing impelling ethical and legal issues since a large number of studies and journalistic investigations showed that software-based decisions, when based on historical data, perpetuate the same prejudices and bias existing in society, resulting in a systematic and inescapable negative impact for individuals from minorities and disadvantaged groups. The problem is so relevant that the terms data bias and algorithm ethics have become familiar not only to researchers, but also to industry leaders and policy makers. In this context, we believe that the ISO SQuaRE standard, if appropriately integrated with risk management concepts and procedures from ISO 31000, can play an important role in democratizing the innovation of software-generated decisions, by making the development of this type of software systems more socially sustainable and in line with the shared values of our societies. More in details, we identified two additional measure for a quality characteristic already present in the standard (completeness) and another that extends it (balance) with the aim of highlighting information gaps or presence of bias in the training data. Those measures serve as risk level indicators to be checked with common fairness measures that indicate the level of polarization of the software classifications/predictions. The adoption of additional features with respect to the standard broadens its scope of application, while maintaining consistency and conformity. The proposed methodology aims to find correlations between quality deficiencies and algorithm decisions, thus allowing to verify and mitigate their impact

designing digital circuits in multi valued logic

In the last few decades we have witnessed an increase in CPU performance, which has been made possible thanks to the increase in the clock frequency and the increase in the number of transistors in the unit of space. In the last few years, however, we reached the limit for the clock and for the miniaturization of the transistor grid. Beyond this growth new problems arose such as the disposal of the produced heat and the minimum distance to be respected between elements for the electrical signals transfer. So the chip makers, to further increase the processing power of the processors, started to insert more cores on the same chip. The presence of several cores undoubtedly improves performance and improves consumption, but the ability to transfer data between cores and components remains limited by the number of pins of the cores themselves. Furthermore, it is necessary to manage the synchronization between cores during the access to common resources and all those multi-core architectures typical problems. This article provides a different approach to improve the computing capacity of the CPUs that is based on the extension of the binary system in a multi-value coding system or, commonly, called MVL. Although this direction has already been explored, the idea behind the study is in the representation of the generic function in the MVL domain. This representation has a link to the binary system and a surprisingly greater simplicity of the corresponding digital circuits (combinatorial and sequential). A different mathematical approach is thus provided for the realization of the multivalue logic gates. This could enable the use of different data encoding systems no longer linked to the voltage value of a signal but to other physical quantities as it happens at present, for example, in the world of telecommunications

GROWTH INHIBITION AND DIFFERENTIATION OF HUMAN BREAST CANCER CELLS BY THE PAFR ANTAGONIST WEB-2086

WEB-2086 – an antagonist of platelet-activating factor receptor (PAFR) with known anti-inflammatory, antiangiogenic and antileukaemic properties – also proved to inhibit the proliferation in human solid tumour cell lines of different histology, and with much higher efficacy than in normal fibroblasts. A detailed analysis of WEB-2086 anticancer activity was then performed focusing on breast adenocarcinoma MCF-7 and MDA-MB-231 cells. WEB-2086-treated cells, either expressing (MCF-7) or unexpressing (MDA-MB-231) the oestrogen receptor (ER)α, underwent a dose-dependent growth arrest (IC(50)=0.65±0.09 and 0.41±0.07 mM, respectively) and accumulation in G(0)–G(1) phase. WEB-2086 also induced morphological and functional changes typical of mature mammary phenotype including (i) cell enlargement and massive neutral lipid deposition (best accomplished in MCF-7 cells); (ii) decrease in motility and active cathepsin D levels (mainly observed in highly invasive MDA-MB-231 cells). The expression of ERα was neither increased nor reactivated in treated MCF-7 or MDA-MB-231 cells, respectively. WEB-2086-induced differentiation in breast cancer cells involved the upregulation of PTEN, a key tumour suppressor protein opposing tumorigenesis, and was apparently independent of p53, PAFR, peripheral benzodiazepine receptor and ERα status. Overall, WEB-2086 can be proposed as an effective antiproliferative and differentiative agent with interesting translational opportunities to treat breast cancers in support to conventional chemotherapy

A tool for evaluating geothermal power exploitability and its application to Ischia, Southern Italy

The paper proposes a method to evaluate the potential for electric power production at any site of possible geothermal interest. Accounting for geological data of the reservoirs, the method allows the computation of the available electrical power of the investigated site. Electrical energy production from geothermal sources is realized through different techniques, such as single flash and double flash, dry steam, and binary ORC plants. The technique chosen to be the most productive is determined by analyzing a specific range of geofluid properties, mainly temperature and pressure. Moreover, each plant typology has a global efficiency that may be correlated to geofluid enthalpy by empiric relations available in literature. The proposed evaluation method brings together all these correlations, yielding the power availability from a geosource, once its temperature and pressure are known. The method takes as input the geofluid available flow rate, its pressure, temperature and non-condensable gas content. It defines the best plant option from these parameters, calculates its global efficiency and finally returns the actual available power. For sites of geothermic interest, such as the volcanic island of Ischia in Southern Italy, the results of the application of this new method clearly highlight the most suitable zones for power plants installations