2021
Santangelo
Volti simbolici. Per una teoria sociosemiotica del volto Journal Article
In: LEXIA, no. 37-38, pp. 503–520, 2021.
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title = {Volti simbolici. Per una teoria sociosemiotica del volto},
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Antonio Santangelo; Anita Botta
Raccomandazioni sociosemiotiche. Considerazioni sul significato dei suggerimenti di visione del sistema di raccomandazione di Netflix. Journal Article
In: @ DIGITCULT, vol. 2/2020, pp. 53–64, 2021.
@article{ 2318_1788794,
title = {Raccomandazioni sociosemiotiche. Considerazioni sul significato dei suggerimenti di visione del sistema di raccomandazione di Netflix.},
author = {Antonio Santangelo and Anita Botta},
year = {2021},
date = {2021-01-01},
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Marco Ricolfi
La restituzione degli utili conseguiti dall’autore di una violazione incolpevole di diritti di proprietà intellettuale Book Chapter
In: Studi di diritto commerciale per Vincenzo di Cataldo Vol. I, Proprietà intellettuale e concorrenza, vol. 288/I, pp. 471–504, Giappichelli, Torino, 2021, ISBN: 9788892139367.
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title = {La restituzione degli utili conseguiti dall’autore di una violazione incolpevole di diritti di proprietà intellettuale},
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year = {2021},
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booktitle = {Studi di diritto commerciale per Vincenzo di Cataldo Vol. I, Proprietà intellettuale e concorrenza},
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MARCO RICOLFI
Procedure concorsuali e garanzie su diritti di proprietà intellettuale Book Chapter
In: Le crisi di impresa e del consumatore dopo il d.l. 118/2021. Liber amicorum per Alberto Jorio, vol. 59, pp. 998–1017, Zanichelli, Bologna, 2021, ISBN: 9788808620040.
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title = {Procedure concorsuali e garanzie su diritti di proprietà intellettuale},
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booktitle = {Le crisi di impresa e del consumatore dopo il d.l. 118/2021. Liber amicorum per Alberto Jorio},
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pages = {998–1017},
publisher = {Zanichelli},
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abstract = {il lavoro esamina la sorte delle garanzie sui diritti di proprietà intellettuale nelle procedure concorsuali},
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il lavoro esamina la sorte delle garanzie sui diritti di proprietà intellettuale nelle procedure concorsuali
Antonio Vetrò
Imbalanced data as risk factor of discriminating automated decisions: a measurement-based approach Journal Article
In: JOURNAL OF INTELLECTUAL PROPERTY, INFORMATION TECHNOLOGY AND ELECTRONIC COMMERCE LAW, vol. 12, no. 4, pp. 272–288, 2021.
@article{ 11583_2951712,
title = {Imbalanced data as risk factor of discriminating automated decisions: a measurement-based approach},
author = {Antonio Vetrò},
url = {https://zenodo.org/record/5795184},
doi = {10.5281/zenodo.5795184},
year = {2021},
date = {2021-01-01},
journal = {JOURNAL OF INTELLECTUAL PROPERTY, INFORMATION TECHNOLOGY AND ELECTRONIC COMMERCE LAW},
volume = {12},
number = {4},
pages = {272–288},
publisher = {Karlsruhe Institute of Technology, Humboldt-Universität zu Berlin and Georg-August-Universität Göttingen},
abstract = {Over the last two decades, the number of organizations -both in the public and private sector- which have automated decisional processes has grown notably. The phenomenon has been enabled by the availability of massive amounts of personal data and the development of software systems that use those data to optimize decisions with respect to certain optimization goals. Today, software systems are involved in a wide realm of decisions that are relevant for the lives of people and the exercise of their rights and freedoms. Illustrative examples are systems that score individuals for their possibility to pay back a debt, recommenders of the best candidates for a job or a house rent advertisement, or tools for automatic moderation of online debates. While advantages for using algorithmic decision making concern mainly scalability and economic affordability, on the other hand, several critical aspects have emerged, including systematic adverse impact for individuals belonging to minorities and disadvantaged groups. In this context, the terms data and algorithm bias have become familiar to researchers, industry leaders and policy makers, and much ink has been spelled on the concept of algorithm fairness, in order to produce more equitable results and to avoid discrimination. Our approach is different from the main corpus of research on algorithm fairness because we shift the focus from the outcomes of automated decision making systems to its inputs and processes. Instead, we lay the foundations of a risk assessment approach based on a measurable characteristic of input data, i.e. imbalance, which can lead to discriminating automated decisions. We then relate the imbalance to existing standards and risk assessment procedures. We believe that the proposed approach can be useful to a variety of stakeholders, e.g. producers and adopters of automated decision making software, policy makers, certification or audit authorities. This would allow for the assessment of the risk level of discriminations when using imbalanced data in decision making software. This assessment should prompt all the involved stakeholders to take appropriate actions to prevent adverse effects. Such discriminations, in fact, pose a significant obstacle to human rights and freedoms, as our societies increasingly rely on automated decision making. This work is intended to help mitigate this problem, and to contribute to the development of software systems that are socially sustainable and are in line with the shared values of our democratic societies.},
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Over the last two decades, the number of organizations -both in the public and private sector- which have automated decisional processes has grown notably. The phenomenon has been enabled by the availability of massive amounts of personal data and the development of software systems that use those data to optimize decisions with respect to certain optimization goals. Today, software systems are involved in a wide realm of decisions that are relevant for the lives of people and the exercise of their rights and freedoms. Illustrative examples are systems that score individuals for their possibility to pay back a debt, recommenders of the best candidates for a job or a house rent advertisement, or tools for automatic moderation of online debates. While advantages for using algorithmic decision making concern mainly scalability and economic affordability, on the other hand, several critical aspects have emerged, including systematic adverse impact for individuals belonging to minorities and disadvantaged groups. In this context, the terms data and algorithm bias have become familiar to researchers, industry leaders and policy makers, and much ink has been spelled on the concept of algorithm fairness, in order to produce more equitable results and to avoid discrimination. Our approach is different from the main corpus of research on algorithm fairness because we shift the focus from the outcomes of automated decision making systems to its inputs and processes. Instead, we lay the foundations of a risk assessment approach based on a measurable characteristic of input data, i.e. imbalance, which can lead to discriminating automated decisions. We then relate the imbalance to existing standards and risk assessment procedures. We believe that the proposed approach can be useful to a variety of stakeholders, e.g. producers and adopters of automated decision making software, policy makers, certification or audit authorities. This would allow for the assessment of the risk level of discriminations when using imbalanced data in decision making software. This assessment should prompt all the involved stakeholders to take appropriate actions to prevent adverse effects. Such discriminations, in fact, pose a significant obstacle to human rights and freedoms, as our societies increasingly rely on automated decision making. This work is intended to help mitigate this problem, and to contribute to the development of software systems that are socially sustainable and are in line with the shared values of our democratic societies.
Antonio Vetrò; Marco Torchiano; Mariachiara Mecati
A data quality approach to the identification of discrimination risk in automated decision making systems Journal Article
In: GOVERNMENT INFORMATION QUARTERLY, vol. 38, no. 4, 2021.
@article{ 11583_2922214,
title = {A data quality approach to the identification of discrimination risk in automated decision making systems},
author = {Antonio Vetrò and Marco Torchiano and Mariachiara Mecati},
url = {https://doi.org/10.1016/j.giq.2021.101619},
doi = {10.1016/j.giq.2021.101619},
year = {2021},
date = {2021-01-01},
journal = {GOVERNMENT INFORMATION QUARTERLY},
volume = {38},
number = {4},
publisher = {Elsevier},
abstract = {Automated decision-making (ADM) systems may affect multiple aspects of our lives. In particular, they can result in systematic discrimination of specific population groups, in violation of the EU Charter of Fundamental Rights. One of the potential causes of discriminative behavior, i.e., unfairness, lies in the quality of the data used to train such ADM systems.
Using a data quality measurement approach combined with risk management, both defined in ISO standards, we focus on balance characteristics and we aim to understand how balance indexes (Gini, Simpson, Shannon, Imbalance Ratio) identify discrimination risk in six large datasets containing the classification output of ADM systems.
The best result is achieved using the Imbalance Ratio index. Gini and Shannon indexes tend to assume high values and for this reason they have modest results in both aspects: further experimentation with different thresholds is needed.
In terms of policies, the risk-based approach is a core element of the EU approach to regulate algorithmic systems: in this context, balance measures can be easily assumed as risk indicators of propagation – or even amplification – of bias in the input data of ADM systems.},
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Automated decision-making (ADM) systems may affect multiple aspects of our lives. In particular, they can result in systematic discrimination of specific population groups, in violation of the EU Charter of Fundamental Rights. One of the potential causes of discriminative behavior, i.e., unfairness, lies in the quality of the data used to train such ADM systems.
Using a data quality measurement approach combined with risk management, both defined in ISO standards, we focus on balance characteristics and we aim to understand how balance indexes (Gini, Simpson, Shannon, Imbalance Ratio) identify discrimination risk in six large datasets containing the classification output of ADM systems.
The best result is achieved using the Imbalance Ratio index. Gini and Shannon indexes tend to assume high values and for this reason they have modest results in both aspects: further experimentation with different thresholds is needed.
In terms of policies, the risk-based approach is a core element of the EU approach to regulate algorithmic systems: in this context, balance measures can be easily assumed as risk indicators of propagation – or even amplification – of bias in the input data of ADM systems.
Using a data quality measurement approach combined with risk management, both defined in ISO standards, we focus on balance characteristics and we aim to understand how balance indexes (Gini, Simpson, Shannon, Imbalance Ratio) identify discrimination risk in six large datasets containing the classification output of ADM systems.
The best result is achieved using the Imbalance Ratio index. Gini and Shannon indexes tend to assume high values and for this reason they have modest results in both aspects: further experimentation with different thresholds is needed.
In terms of policies, the risk-based approach is a core element of the EU approach to regulate algorithmic systems: in this context, balance measures can be easily assumed as risk indicators of propagation – or even amplification – of bias in the input data of ADM systems.
Mariachiara Mecati; Antonio Vetro; Marco Torchiano
2021 IEEE International Conference on Big Data (Big Data), IEEE, 2021, ISBN: 978-1-6654-3902-2.
@conference{ 11583_2950474,
title = {Detecting Discrimination Risk in Automated Decision-Making Systems with Balance Measures on Input Data},
author = {Mariachiara Mecati and Antonio Vetro and Marco Torchiano},
url = {https://ieeexplore.ieee.org/document/9671443},
doi = {10.1109/BigData52589.2021.9671443},
isbn = {978-1-6654-3902-2},
year = {2021},
date = {2021-01-01},
booktitle = {2021 IEEE International Conference on Big Data (Big Data)},
pages = {4287–4296},
publisher = {IEEE},
abstract = {Bias in the data used to train decision-making systems is a relevant socio-technical issue that emerged in recent years, and it still lacks a commonly accepted solution. Indeed, the "bias in-bias out" problem represents one of the most significant risks of discrimination, which encompasses technical fields, as well as ethical and social perspectives. We contribute to the current studies of the issue by proposing a data quality measurement approach combined with risk management, both defined in ISO/IEC standards. For this purpose, we investigate imbalance in a given dataset as a potential risk factor for detecting discrimination in the classification outcome: specifically, we aim to evaluate whether it is possible to identify the risk of bias in a classification output by measuring the level of (im)balance in the input data. We select four balance measures (the Gini, Shannon, Simpson, and Imbalance ratio indexes) and we test their capability to identify discriminatory classification outputs by applying such measures to protected attributes in the training set. The results of this analysis show that the proposed approach is suitable for the goal highlighted above: the balance measures properly detect unfairness of software output, even though the choice of the index has a relevant impact on the detection of discriminatory outcomes, therefore further work is required to test more in-depth the reliability of the balance measures as risk indicators. We believe that our approach for assessing the risk of discrimination should encourage to take more conscious and appropriate actions, as well as to prevent adverse effects caused by the "bias in-bias out" problem.},
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Bias in the data used to train decision-making systems is a relevant socio-technical issue that emerged in recent years, and it still lacks a commonly accepted solution. Indeed, the “bias in-bias out” problem represents one of the most significant risks of discrimination, which encompasses technical fields, as well as ethical and social perspectives. We contribute to the current studies of the issue by proposing a data quality measurement approach combined with risk management, both defined in ISO/IEC standards. For this purpose, we investigate imbalance in a given dataset as a potential risk factor for detecting discrimination in the classification outcome: specifically, we aim to evaluate whether it is possible to identify the risk of bias in a classification output by measuring the level of (im)balance in the input data. We select four balance measures (the Gini, Shannon, Simpson, and Imbalance ratio indexes) and we test their capability to identify discriminatory classification outputs by applying such measures to protected attributes in the training set. The results of this analysis show that the proposed approach is suitable for the goal highlighted above: the balance measures properly detect unfairness of software output, even though the choice of the index has a relevant impact on the detection of discriminatory outcomes, therefore further work is required to test more in-depth the reliability of the balance measures as risk indicators. We believe that our approach for assessing the risk of discrimination should encourage to take more conscious and appropriate actions, as well as to prevent adverse effects caused by the “bias in-bias out” problem.
Alessandro Simonetta; Andrea Trenta; Maria Cristina Paoletti; Antonio Vetrò
Metrics for Identifying Bias in Datasets Conference
Proceedings of the International Conference of Yearly Reports on Informatics, Mathematics and Engineering, vol. 3118, CEUR-WS.org, Aachen, 2021.
@conference{ 11583_2961712,
title = {Metrics for Identifying Bias in Datasets},
author = {Alessandro Simonetta and Andrea Trenta and Maria Cristina Paoletti and Antonio Vetrò},
url = {http://ceur-ws.org/Vol-3118/},
year = {2021},
date = {2021-01-01},
booktitle = {Proceedings of the International Conference of Yearly Reports on Informatics, Mathematics and Engineering},
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publisher = {CEUR-WS.org},
address = {Aachen},
abstract = {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.},
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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.
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.
Antonio Vetrò; Marco Torchiano; Mariachiara Mecati
2021.
@misc{ 11583_2922232,
title = {Reproducibility Package for 'A Data Quality Approach to the Identification of Discrimination Risk in Automated Decision Making Systems'},
author = {Antonio Vetrò and Marco Torchiano and Mariachiara Mecati},
url = {https://doi.org/10.24433/CO.0509748.v3},
doi = {10.24433/CO.0509748.v3},
year = {2021},
date = {2021-01-01},
abstract = {Automated decision-making (ADM) systems may affect multiple aspects of our lives. In particular, they can result in systematic discrimination of specific population groups, in violation of the EU Charter of Fundamental Rights. One of the potential causes of discriminative behavior, i.e. unfairness, lies in the quality of the data used to train such ADM systems. Using a data quality measurement approach combined with risk management, both defined in ISO standards, we focus on balance characteristics and we aim to understand how balance indexes (Gini, Simpson, Shannon, Imbalance ratio) identify discrimination risk in six large datasets containing the classification output of ADM systems. The best result is achieved using the Imbalance Ratio index. Gini and Shannon indexes tend to assume high values and for this reason they have modest results in both aspects: further experimentation with different thresholds is needed. In terms of policies, the risk-based approach is a core element of the EU approach to regulate algorithmic systems: in this context, balance measures can be easily assumed as risk indicators of propagation – or even amplification – of bias in the input data of ADM systems.},
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Automated decision-making (ADM) systems may affect multiple aspects of our lives. In particular, they can result in systematic discrimination of specific population groups, in violation of the EU Charter of Fundamental Rights. One of the potential causes of discriminative behavior, i.e. unfairness, lies in the quality of the data used to train such ADM systems. Using a data quality measurement approach combined with risk management, both defined in ISO standards, we focus on balance characteristics and we aim to understand how balance indexes (Gini, Simpson, Shannon, Imbalance ratio) identify discrimination risk in six large datasets containing the classification output of ADM systems. The best result is achieved using the Imbalance Ratio index. Gini and Shannon indexes tend to assume high values and for this reason they have modest results in both aspects: further experimentation with different thresholds is needed. In terms of policies, the risk-based approach is a core element of the EU approach to regulate algorithmic systems: in this context, balance measures can be easily assumed as risk indicators of propagation – or even amplification – of bias in the input data of ADM systems.
Juan Carlos De Martin
La grande migrazione online. Costi e opportunità Journal Article
In: PHILOSOPHY KITCHEN, no. 15, pp. 63–78, 2021.
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title = {La grande migrazione online. Costi e opportunità},
author = {Juan Carlos De Martin},
url = {https://www.ojs.unito.it/index.php/philosophykitchen/article/view/6216},
doi = {10.13135/2385-1945/6216},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
journal = {PHILOSOPHY KITCHEN},
number = {15},
pages = {63–78},
publisher = {Università degli Studi di Torino},
abstract = {In the last three decades, many human activities have migrated online: some completely, others only partially – even if the latter were strongly influenced by the digital rev- olution too. Other activities have kept their physicality while gaining a digital extension, with variable and unprec- edented results. As any social mutation, this is a gradual process characterised by great achievements as well as by important failures; a process changing both our life and global power politics.
Under this respect, March 2020 represents a turning point: by experiencing the first so-called “lock- down”, in a few weeks the physical life of millions of Italians was transferred online – partially or even entirely. What exactly happened? Who succeeded in this migration, who failed, and why? Which were, are, and will be the conse- quences? Have we learned anything? And, most impor- tantly: eighteen months after the beginning of this Great Online Migration, how do we want to shape our future?},
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In the last three decades, many human activities have migrated online: some completely, others only partially – even if the latter were strongly influenced by the digital rev- olution too. Other activities have kept their physicality while gaining a digital extension, with variable and unprec- edented results. As any social mutation, this is a gradual process characterised by great achievements as well as by important failures; a process changing both our life and global power politics.
Under this respect, March 2020 represents a turning point: by experiencing the first so-called “lock- down”, in a few weeks the physical life of millions of Italians was transferred online – partially or even entirely. What exactly happened? Who succeeded in this migration, who failed, and why? Which were, are, and will be the conse- quences? Have we learned anything? And, most impor- tantly: eighteen months after the beginning of this Great Online Migration, how do we want to shape our future?
Under this respect, March 2020 represents a turning point: by experiencing the first so-called “lock- down”, in a few weeks the physical life of millions of Italians was transferred online – partially or even entirely. What exactly happened? Who succeeded in this migration, who failed, and why? Which were, are, and will be the conse- quences? Have we learned anything? And, most impor- tantly: eighteen months after the beginning of this Great Online Migration, how do we want to shape our future?
Giovanni Garifo; Giuseppe Futia; Antonio Vetro’; Juan Carlos De Martin
The Geranium Platform: A KG-Based System for Academic Publications Journal Article
In: INFORMATION, vol. 12, no. 9, 2021.
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title = {The Geranium Platform: A KG-Based System for Academic Publications},
author = {Giovanni Garifo and Giuseppe Futia and Antonio Vetro' and Juan Carlos De Martin},
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doi = {10.3390/info12090366},
year = {2021},
date = {2021-01-01},
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Elena Beretta; Antonio Vetrò; Bruno Lepri; Juan Carlos De Martin
Equality of Opportunity in Ranking: a Fair-Distributive Model Conference
Advances in Bias and Social Aspects in Search and Recommendation, Springer, 2021, ISBN: 978-3-030-78817-9.
@conference{<LineBreak> 11583_2898812,
title = {Equality of Opportunity in Ranking: a Fair-Distributive Model},
author = {Elena Beretta and Antonio Vetrò and Bruno Lepri and Juan Carlos De Martin},
url = {https://link.springer.com/chapter/10.1007/978-3-030-78818-6_6#citeas},
doi = {10.1007/978-3-030-78818-6_6},
isbn = {978-3-030-78817-9},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
booktitle = {Advances in Bias and Social Aspects in Search and Recommendation},
pages = {51–63},
publisher = {Springer},
abstract = {In this work, we define a Fair-Distributive ranking system based on Equality of Opportunity theory and fair division models. The aim is to determine the ranking order of a set of candidates maximizing utility bound to a fairness constraint. Our model extends the notion of protected attributes to a pool of individual circumstances, which determine the membership to a specific type. The contribution of this paper are i) a Fair-Distributive Ranking System based on criteria derived from distributive justice theory and its applications in both economic and social sciences; ii) a class of fairness metrics for ranking systems based on the Equality of Opportunity theory. We test our approach on a hypothetical scenario of a selection university process. A follow-up analysis shows that the Fair-Distributive Ranking System preserves an equal exposure level for both minority and majority groups, providing a minimal system utility cost.},
keywords = {},
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In this work, we define a Fair-Distributive ranking system based on Equality of Opportunity theory and fair division models. The aim is to determine the ranking order of a set of candidates maximizing utility bound to a fairness constraint. Our model extends the notion of protected attributes to a pool of individual circumstances, which determine the membership to a specific type. The contribution of this paper are i) a Fair-Distributive Ranking System based on criteria derived from distributive justice theory and its applications in both economic and social sciences; ii) a class of fairness metrics for ranking systems based on the Equality of Opportunity theory. We test our approach on a hypothetical scenario of a selection university process. A follow-up analysis shows that the Fair-Distributive Ranking System preserves an equal exposure level for both minority and majority groups, providing a minimal system utility cost.
2020
Antonio Santangelo; others
Semiotica e VR: il senso di un’esperienza mediale Book Section
In: Immersi nel futuro. La realtà virtuale, nuova frontiera del cinema e della tv, pp. 191–198, Palermo University Press, 2020.
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title = {Semiotica e VR: il senso di un'esperienza mediale},
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year = {2020},
date = {2020-01-01},
booktitle = {Immersi nel futuro. La realtà virtuale, nuova frontiera del cinema e della tv},
pages = {191–198},
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Antonio Santangelo
I narcisi mascherati, gli eroi e noi Book Chapter
In: Volti virali, pp. 39–68, Facets Digital Press, Torino, 2020, ISBN: 979-12-200-6423-1.
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title = {I narcisi mascherati, gli eroi e noi},
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year = {2020},
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Antonio Santangelo
Gravidanza per altri e ideologie. Riflessioni sul film “Tuttinsieme” di Marco Puccioni Journal Article
In: BIOETICA, vol. 4, pp. 656–675, 2020.
@article{ 2318_1810967,
title = {Gravidanza per altri e ideologie. Riflessioni sul film "Tuttinsieme" di Marco Puccioni},
author = {Antonio Santangelo},
year = {2020},
date = {2020-01-01},
journal = {BIOETICA},
volume = {4},
pages = {656–675},
abstract = {Questo articolo parte dall’analisi del film Tuttinsieme di Marco Puccioni (2020), per occuparsi del tema della gravidanza per altri e delle cosiddette “famiglie arcobaleno”. Prendendo spunto dai contenuti dell’opera in questione, affronta alcune delle più importanti critiche che vengono rivolte a questa pratica, riflettendo sulle soluzioni proposte all’interno del film stesso. Inoltre, si concentra sul concetto di ideologia e su come quest’ultimo può essere affrontato da un punto di vista semiotico, per mostrare come i termini del confronto tra i sostenitori della gravidanza per altri e i suoi detrattori possa essere inquadrato in questo senso, soprattutto per quanto riguarda la diatriba su ciò che viene interpretato come “naturale” e ciò che non appare tale.},
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Questo articolo parte dall’analisi del film Tuttinsieme di Marco Puccioni (2020), per occuparsi del tema della gravidanza per altri e delle cosiddette “famiglie arcobaleno”. Prendendo spunto dai contenuti dell’opera in questione, affronta alcune delle più importanti critiche che vengono rivolte a questa pratica, riflettendo sulle soluzioni proposte all’interno del film stesso. Inoltre, si concentra sul concetto di ideologia e su come quest’ultimo può essere affrontato da un punto di vista semiotico, per mostrare come i termini del confronto tra i sostenitori della gravidanza per altri e i suoi detrattori possa essere inquadrato in questo senso, soprattutto per quanto riguarda la diatriba su ciò che viene interpretato come “naturale” e ciò che non appare tale.
Antonio Santangelo; Vera Tripodi
Riflessioni sul film “Tuttinsieme” di Marco Puccioni Miscellaneous
2020.
@misc{ 2318_1810968,
title = {Riflessioni sul film "Tuttinsieme" di Marco Puccioni},
author = {Antonio Santangelo and Vera Tripodi},
year = {2020},
date = {2020-01-01},
journal = {BIOETICA},
volume = {4},
pages = {622–693},
publisher = {Vicolo del Pavone},
address = {Piacenza},
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Antonio Santangelo
Dalla fine all’inizio: ma quale inizio? Journal Article
In: E/C, pp. 46–48, 2020.
@article{ 2318_1788796,
title = {Dalla fine all’inizio: ma quale inizio?},
author = {Antonio Santangelo},
year = {2020},
date = {2020-01-01},
journal = {E/C},
pages = {46–48},
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Antonio Santangelo
Semiotica e VR: il senso di un’esperienza mediale Book Chapter
In: Immersi nel futuro. La realtà virtuale, nuova frontiera del cinema e della tv, pp. 191–198, Palermo University Press, Palermo, 2020, ISBN: 978-88-5509-180-0.
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title = {Semiotica e VR: il senso di un'esperienza mediale},
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date = {2020-01-01},
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Marco Ricolfi
Le operazioni di garanzia su marchio Journal Article
In: GIURISPRUDENZA COMMERCIALE, vol. 47, no. 3, pp. 475–489, 2020.
@article{ 2318_1755016,
title = {Le operazioni di garanzia su marchio},
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year = {2020},
date = {2020-01-01},
journal = {GIURISPRUDENZA COMMERCIALE},
volume = {47},
number = {3},
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il lavoro tratta le operazioni di garanzia su marchio
Marco Ricolfi
Opinion of the European Copyright Society in Relation to the Pending Reference before the CJEU in Brompton Bycicle v Chedech/Get2Get (C-833/18) Journal Article
In: EUROPEAN INTELLECTUAL PROPERTY REVIEW, vol. 42, no. 4, pp. 205–213, 2020.
@article{ 2318_1736288,
title = {Opinion of the European Copyright Society in Relation to the Pending Reference before the CJEU in Brompton Bycicle v Chedech/Get2Get (C-833/18)},
author = {Marco Ricolfi},
year = {2020},
date = {2020-01-01},
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volume = {42},
number = {4},
pages = {205–213},
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Alessandro Enrico Cogo; Marco Ricolfi
Administrative Enforcement of Copyright Infringement in Europe Book Chapter
In: The Oxford Handbook of Online Intermediary Liability, pp. 586–610, Oxford University Press, Oxford, 2020, ISBN: 978-0198837138.
@inbook{ 2318_1768672,
title = {Administrative Enforcement of Copyright Infringement in Europe},
author = {Alessandro Enrico Cogo and Marco Ricolfi},
doi = {10.1093/oxfordhb/9780198837138.001.0001},
isbn = {978-0198837138},
year = {2020},
date = {2020-01-01},
booktitle = {The Oxford Handbook of Online Intermediary Liability},
pages = {586–610},
publisher = {Oxford University Press},
address = {Oxford},
abstract = {In recent years, the number of countries which have opted for the involvement of administrative bodies in the enforcement of copyright has increased as a result of the remarkable difficulties that the enforcement of copyright faces in a digital environment. This chapter describes first the European landscape of administrative bodies entrusted with the enforcement of copyright infringement online, with special emphasis on Greece, Italy, and Spain. Secondly, the chapter considers the legal framework where these administrative bodies operate with emphasis on the TRIPs Agreement, EU law, and the EU Charter of Fundamental Rights. Thirdly, the chapter looks into the essential features of these administrative enforcement systems, including procedural rules, allocation of costs, remedies, transparency, and safeguards against abuse. Finally, the chapter elaborates on the implementation of the AGCOM Regulation in practice, providing data from the case law developed so far.},
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In recent years, the number of countries which have opted for the involvement of administrative bodies in the enforcement of copyright has increased as a result of the remarkable difficulties that the enforcement of copyright faces in a digital environment. This chapter describes first the European landscape of administrative bodies entrusted with the enforcement of copyright infringement online, with special emphasis on Greece, Italy, and Spain. Secondly, the chapter considers the legal framework where these administrative bodies operate with emphasis on the TRIPs Agreement, EU law, and the EU Charter of Fundamental Rights. Thirdly, the chapter looks into the essential features of these administrative enforcement systems, including procedural rules, allocation of costs, remedies, transparency, and safeguards against abuse. Finally, the chapter elaborates on the implementation of the AGCOM Regulation in practice, providing data from the case law developed so far.
Marco Ricolfi
Diritto industriale. Proprietà intellettuale e concorrenza Book Chapter
In: Diritto industriale. Proprietà intellettuale e concorrenza, pp. 75–208, G. Giappichelli Editore srl, Torino, 2020, ISBN: 9788892133167.
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MARCO RICOLFI
Trademarks and Human Rights Book Chapter
In: Intellectual Property Law and Human Rights, Fourth Edition, vol. 34, pp. 593–643, Wolters Kluwer, Alphen aan den Rijn, 2020, ISBN: 9789403513041.
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booktitle = {Intellectual Property Law and Human Rights, Fourth Edition},
volume = {34},
pages = {593–643},
publisher = {Wolters Kluwer},
address = {Alphen aan den Rijn},
abstract = {Il lavoro esamina la interazione fra il diritto dei marchi ed i diritti fondamentali in prospettiva di diritto europeo, comparato e internazionale},
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Il lavoro esamina la interazione fra il diritto dei marchi ed i diritti fondamentali in prospettiva di diritto europeo, comparato e internazionale
Marco Ricolfi
Security Rights in Intellectual Property in Italy Book Chapter
In: Security Rights in Intellectual Property, vol. 45, pp. 439–467, Springer, Cham,, 2020, ISBN: 9783030441906.
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title = {Security Rights in Intellectual Property in Italy},
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booktitle = {Security Rights in Intellectual Property},
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publisher = {Springer},
address = {Cham,},
abstract = {the essay sets forth the Italian rules concerning securities over IP against a EU backgroiund},
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the essay sets forth the Italian rules concerning securities over IP against a EU backgroiund
Mariachiara Mecati; Flavio Emanuele Cannavò; Antonio Vetrò; Marco Torchiano
Identifying Risks in Datasets for Automated Decision–Making Conference
Electronic Government, vol. 12219, Springer, Cham, 2020, ISBN: 978-3-030-57599-1.
@conference{ 11583_2843005,
title = {Identifying Risks in Datasets for Automated Decision–Making},
author = {Mariachiara Mecati and Flavio Emanuele Cannavò and Antonio Vetrò and Marco Torchiano},
url = {https://doi.org/10.1007/978-3-030-57599-1_25},
doi = {10.1007/978-3-030-57599-1_25},
isbn = {978-3-030-57599-1},
year = {2020},
date = {2020-01-01},
booktitle = {Electronic Government},
volume = {12219},
pages = {332–344},
publisher = {Springer},
address = {Cham},
abstract = {Our daily life is profoundly affected by the adoption of au- tomated decision making (ADM) systems due to the ongoing tendency of humans to delegate machines to take decisions. The unleashed usage of ADM systems was facilitated by the availability of large-scale data, alongside with the deployment of devices and equipment. This trend re- sulted in an increasing influence of ADM systems’ output over several aspects of our life, with possible discriminatory consequences towards certain individuals or groups. In this context, we focus on input data by investigating measurable characteristics which can lead to discriminating automated decisions. In particular, we identified two indexes of hetero- geneity and diversity, and tested them on two datasets. A limitation we found is the index sensitivity to a large number of categories, but on the whole results show that the indexes reflect well imbalances in the input data. Future work is required to further assess the reliability of these indexes as indicators of discrimination risks in the context of ADM, in order to foster a more conscious and responsible use of ADM systems through an immediate investigation on input data.},
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Our daily life is profoundly affected by the adoption of au- tomated decision making (ADM) systems due to the ongoing tendency of humans to delegate machines to take decisions. The unleashed usage of ADM systems was facilitated by the availability of large-scale data, alongside with the deployment of devices and equipment. This trend re- sulted in an increasing influence of ADM systems’ output over several aspects of our life, with possible discriminatory consequences towards certain individuals or groups. In this context, we focus on input data by investigating measurable characteristics which can lead to discriminating automated decisions. In particular, we identified two indexes of hetero- geneity and diversity, and tested them on two datasets. A limitation we found is the index sensitivity to a large number of categories, but on the whole results show that the indexes reflect well imbalances in the input data. Future work is required to further assess the reliability of these indexes as indicators of discrimination risks in the context of ADM, in order to foster a more conscious and responsible use of ADM systems through an immediate investigation on input data.
Giuseppe Futia; Antonio Vetro
On the Integration of Knowledge Graphs into Deep Learning Models for a More Comprehensible AI—Three Challenges for Future Research Journal Article
In: INFORMATION, vol. 11, no. 2, 2020.
@article{<LineBreak> 11583_2797449,
title = {On the Integration of Knowledge Graphs into Deep Learning Models for a More Comprehensible AI—Three Challenges for Future Research},
author = {Giuseppe Futia and Antonio Vetro},
url = {https://www.mdpi.com/2078-2489/11/2/122},
doi = {10.3390/info11020122},
year = {2020},
date = {2020-01-01},
urldate = {2020-01-01},
journal = {INFORMATION},
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publisher = {MDPI},
abstract = {Deep learning models contributed to reaching unprecedented results in prediction and classification tasks of Artificial Intelligence (AI) systems. However, alongside this notable progress, they do not provide human-understandable insights on how a specific result was achieved. In contexts where the impact of AI on human life is relevant (e.g., recruitment tools, medical diagnoses, etc.), explainability is not only a desirable property, but it is -or, in some cases, it will be soon-a legal requirement. Most of the available approaches to implement eXplainable Artificial Intelligence (XAI) focus on technical solutions usable only by experts able to manipulate the recursive mathematical functions in deep learning algorithms. A complementary approach is represented by symbolic AI, where symbols are elements of a lingua franca between humans and deep learning. In this context, Knowledge Graphs (KGs) and their underlying semantic technologies are the modern implementation of symbolic AI—while being less flexible and robust to noise compared to deep learning models, KGs are natively developed to be explainable. In this paper, we review the main XAI approaches existing in the literature, underlying their strengths and limitations, and we propose neural-symbolic integration as a cornerstone to design an AI which is closer to non-insiders comprehension. Within such a general direction, we identify three specific challenges for future research—knowledge matching, cross-disciplinary explanations and interactive explanations.},
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Deep learning models contributed to reaching unprecedented results in prediction and classification tasks of Artificial Intelligence (AI) systems. However, alongside this notable progress, they do not provide human-understandable insights on how a specific result was achieved. In contexts where the impact of AI on human life is relevant (e.g., recruitment tools, medical diagnoses, etc.), explainability is not only a desirable property, but it is -or, in some cases, it will be soon-a legal requirement. Most of the available approaches to implement eXplainable Artificial Intelligence (XAI) focus on technical solutions usable only by experts able to manipulate the recursive mathematical functions in deep learning algorithms. A complementary approach is represented by symbolic AI, where symbols are elements of a lingua franca between humans and deep learning. In this context, Knowledge Graphs (KGs) and their underlying semantic technologies are the modern implementation of symbolic AI—while being less flexible and robust to noise compared to deep learning models, KGs are natively developed to be explainable. In this paper, we review the main XAI approaches existing in the literature, underlying their strengths and limitations, and we propose neural-symbolic integration as a cornerstone to design an AI which is closer to non-insiders comprehension. Within such a general direction, we identify three specific challenges for future research—knowledge matching, cross-disciplinary explanations and interactive explanations.
Mariachiara Mecati; Flavio Emanuele Cannavò; Antonio Vetrò; Marco Torchiano
Reproducibility Package for ‘Identifying risks in datasets for automated decision–making’ Miscellaneous
2020.
@misc{ 11583_2844474,
title = {Reproducibility Package for 'Identifying risks in datasets for automated decision–making'},
author = {Mariachiara Mecati and Flavio Emanuele Cannavò and Antonio Vetrò and Marco Torchiano},
url = {https://dx.doi.org/10.24433/CO.5067135.v2},
doi = {10.24433/CO.5067135.v2},
year = {2020},
date = {2020-01-01},
abstract = {Our daily life is profoundly affected by the adoption of automated decision making (ADM) systems due to the ongoing tendency of humans to delegate machines to take decisions. The unleashed usage of ADM systems was facilitated by the availability of large-scale data, alongside with the deployment of devices and equipment. This trend resulted in an increasing influence of ADM systems' output over several aspects of our life, with possible discriminatory consequences towards certain individuals or groups. In this context, we focus on input data by investigating measurable characteristics which can lead to discriminating automated decisions. In particular, we identified two indexes of heterogeneity and diversity, and tested them on two datasets. A limitation we found is the index sensitivity to a large number of categories, but on the whole results show that the indexes reflect well imbalances in the input data.
Future work is required to further assess the reliability of these indexes as indicators of discrimination risks in the context of ADM, in order to foster a more conscious and responsible use of ADM systems through an immediate investigation on input data.},
keywords = {},
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tppubtype = {misc}
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Our daily life is profoundly affected by the adoption of automated decision making (ADM) systems due to the ongoing tendency of humans to delegate machines to take decisions. The unleashed usage of ADM systems was facilitated by the availability of large-scale data, alongside with the deployment of devices and equipment. This trend resulted in an increasing influence of ADM systems’ output over several aspects of our life, with possible discriminatory consequences towards certain individuals or groups. In this context, we focus on input data by investigating measurable characteristics which can lead to discriminating automated decisions. In particular, we identified two indexes of heterogeneity and diversity, and tested them on two datasets. A limitation we found is the index sensitivity to a large number of categories, but on the whole results show that the indexes reflect well imbalances in the input data.
Future work is required to further assess the reliability of these indexes as indicators of discrimination risks in the context of ADM, in order to foster a more conscious and responsible use of ADM systems through an immediate investigation on input data.
Future work is required to further assess the reliability of these indexes as indicators of discrimination risks in the context of ADM, in order to foster a more conscious and responsible use of ADM systems through an immediate investigation on input data.
Giuseppe Futia; Antonio Vetrò; Juan Carlos De Martin
SeMi: A SEmantic Modeling machIne to build Knowledge Graphs with graph neural networks Journal Article
In: SOFTWAREX, vol. 12, 2020.
@article{<LineBreak> 11583_2834234,
title = {SeMi: A SEmantic Modeling machIne to build Knowledge Graphs with graph neural networks},
author = {Giuseppe Futia and Antonio Vetrò and Juan Carlos De Martin},
url = {https://www.sciencedirect.com/science/article/pii/S2352711019302626},
doi = {10.1016/j.softx.2020.100516},
year = {2020},
date = {2020-01-01},
urldate = {2020-01-01},
journal = {SOFTWAREX},
volume = {12},
publisher = {Elsevier},
abstract = {SeMi (SEmantic Modeling machIne) is a tool to semi-automatically build large-scale Knowledge Graphs from structured sources such as CSV, JSON, and XML files. To achieve such a goal, SeMi builds the semantic models of the data sources, in terms of concepts and relations within a domain ontology. Most of the research contributions on automatic semantic modeling is focused on the detection of semantic types of source attributes. However, the inference of the correct semantic relations between these attributes is critical to reconstruct the precise meaning of the data. SeMi covers the entire process of semantic modeling: (i) it provides a semi-automatic step to detect semantic types; (ii) it exploits a novel approach to inference semantic relations, based on a graph neural network trained on background linked data. At the best of our knowledge, this is the first technique that exploits a graph neural network to support the semantic modeling process. Furthermore, the pipeline implemented in SeMi is modular and each component can be replaced to tailor the process to very specific domains or requirements. This contribution can be considered as a step ahead towards automatic and scalable approaches for building Knowledge Graphs.},
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SeMi (SEmantic Modeling machIne) is a tool to semi-automatically build large-scale Knowledge Graphs from structured sources such as CSV, JSON, and XML files. To achieve such a goal, SeMi builds the semantic models of the data sources, in terms of concepts and relations within a domain ontology. Most of the research contributions on automatic semantic modeling is focused on the detection of semantic types of source attributes. However, the inference of the correct semantic relations between these attributes is critical to reconstruct the precise meaning of the data. SeMi covers the entire process of semantic modeling: (i) it provides a semi-automatic step to detect semantic types; (ii) it exploits a novel approach to inference semantic relations, based on a graph neural network trained on background linked data. At the best of our knowledge, this is the first technique that exploits a graph neural network to support the semantic modeling process. Furthermore, the pipeline implemented in SeMi is modular and each component can be replaced to tailor the process to very specific domains or requirements. This contribution can be considered as a step ahead towards automatic and scalable approaches for building Knowledge Graphs.
Giuseppe Futia; Giovanni Garifo; Antonio Vetro’; Juan Carlos De Martin
Modeling the semantics of data sources with graph neural networks Conference
2020.
@conference{<LineBreak> 11583_2855045,
title = {Modeling the semantics of data sources with graph neural networks},
author = {Giuseppe Futia and Giovanni Garifo and Antonio Vetro' and Juan Carlos De Martin},
url = {https://logicalreasoninggnn.github.io/papers/5.pdf},
year = {2020},
date = {2020-01-01},
urldate = {2020-01-01},
abstract = {Semantic models are fundamental to publish datainto Knowledge Graphs (KGs), since they encodethe precise meaning of data sources, through con-cepts and properties defined within reference on-tologies. However, building semantic models re-quires significant manual effort and expertise. Inthis paper, we present a novel approach based onGraph Neural Networks (GNNs) to build seman-tic models of data sources. GNNs are trained onLinked Data (LD) graphs, which serve as back-ground knowledge to automatically infer the se-mantic relations connecting the attributes of a datasource. At the best of our knowledge, this is thefirst approach that employs GNNs to identify thesemantic relations. We tested our approach on 15target sources from the advertising domain (usedin other studies in the literature), and comparedits performance against two baselines and a tech-nique largely used in the state of the art. Theevaluation showed that our approach outperformsthe state of the art in cases of data source withthe largest amount of semantic relations definedin the ground truth.},
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Semantic models are fundamental to publish datainto Knowledge Graphs (KGs), since they encodethe precise meaning of data sources, through con-cepts and properties defined within reference on-tologies. However, building semantic models re-quires significant manual effort and expertise. Inthis paper, we present a novel approach based onGraph Neural Networks (GNNs) to build seman-tic models of data sources. GNNs are trained onLinked Data (LD) graphs, which serve as back-ground knowledge to automatically infer the se-mantic relations connecting the attributes of a datasource. At the best of our knowledge, this is thefirst approach that employs GNNs to identify thesemantic relations. We tested our approach on 15target sources from the advertising domain (usedin other studies in the literature), and comparedits performance against two baselines and a tech-nique largely used in the state of the art. Theevaluation showed that our approach outperformsthe state of the art in cases of data source withthe largest amount of semantic relations definedin the ground truth.
2019
Marco Conoscenti; Antonio Vetro; Juan Carlos De Martin
Hubs, Rebalancing and Service Providers in the Lightning Network Journal Article
In: IEEE Access, vol. 7, pp. 132828–132840, 2019.
@article{<LineBreak> 11583_2757472,
title = {Hubs, Rebalancing and Service Providers in the Lightning Network},
author = {Marco Conoscenti and Antonio Vetro and Juan Carlos De Martin},
url = {https://ieeexplore.ieee.org/document/8839024},
doi = {10.1109/ACCESS.2019.2941448},
year = {2019},
date = {2019-09-16},
urldate = {2019-01-01},
journal = {IEEE Access},
volume = {7},
pages = {132828–132840},
publisher = {IEEE},
abstract = {Payment channel networks are the most developed proposal to address the well-known issue of blockchain scalability. Currently, the Lightning Network (LN) is the mainstream and most used payment channel network. In a previous work we introduced CLoTH, a payment channel network simulator we developed to analyze capabilities and limitations of such networks. In this work, using CLoTH, we present results of three groups of simulations on a recent snapshot of the LN, aimed to shed a light on the following aspects. Firstly, we investigated how hubs influence the LN performance. Then, we analyzed the effectiveness of two different channel rebalancing approaches, an active and a passive one. Eventually, we studied performance of the LN when a few service-providers nodes receive payments from the other network nodes, which is a typical use case of payment channel networks. We found that the LN is resilient to the removal of hubs, that our passive rebalancing approach reduces of about one fourth the payments failures due to channel unbalancing, and that in the service-providers scenario a consistent part of payments fails because channels directing to the service providers become unbalanced. Our work contributes to prove the strengthen of the Lightning Network when removing hubs and its weakness in the service-provider scenario. In addition, the passive rebalancing approach proposed in this work is a good candidate for the implementation in the Lightning Network protocol to mitigate channel unbalancing.},
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Payment channel networks are the most developed proposal to address the well-known issue of blockchain scalability. Currently, the Lightning Network (LN) is the mainstream and most used payment channel network. In a previous work we introduced CLoTH, a payment channel network simulator we developed to analyze capabilities and limitations of such networks. In this work, using CLoTH, we present results of three groups of simulations on a recent snapshot of the LN, aimed to shed a light on the following aspects. Firstly, we investigated how hubs influence the LN performance. Then, we analyzed the effectiveness of two different channel rebalancing approaches, an active and a passive one. Eventually, we studied performance of the LN when a few service-providers nodes receive payments from the other network nodes, which is a typical use case of payment channel networks. We found that the LN is resilient to the removal of hubs, that our passive rebalancing approach reduces of about one fourth the payments failures due to channel unbalancing, and that in the service-providers scenario a consistent part of payments fails because channels directing to the service providers become unbalanced. Our work contributes to prove the strengthen of the Lightning Network when removing hubs and its weakness in the service-provider scenario. In addition, the passive rebalancing approach proposed in this work is a good candidate for the implementation in the Lightning Network protocol to mitigate channel unbalancing.
Mattia Plazio; Francesco Ruggiero; Roberto Mastroianni
Opera Viva di Alessandro Bulgini. L’arte (relazionale) ai tempi dei social network Journal Article
In: DigitCult-Scientific Journal on Digital Cultures, vol. 4, no. 3, pp. 15–26, 2019.
@article{plazio2019opera,
title = {Opera Viva di Alessandro Bulgini. L'arte (relazionale) ai tempi dei social network},
author = {Mattia Plazio and Francesco Ruggiero and Roberto Mastroianni},
year = {2019},
date = {2019-01-01},
journal = {DigitCult-Scientific Journal on Digital Cultures},
volume = {4},
number = {3},
pages = {15–26},
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pubstate = {published},
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Marco Ricolfi
Studi per Luigi Carlo Ubertazzi Proprietà intellettuale e concorrenza Book Chapter
In: Studi per Luigi Carlo Ubertazzi, Proprietà intellettuale e concorrenza, pp. 655–681, Giuffrè Francis Lefevre, Milano, 2019, ISBN: 9788828812098.
@inbook{ 2318_1719191,
title = {Studi per Luigi Carlo Ubertazzi Proprietà intellettuale e concorrenza},
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year = {2019},
date = {2019-01-01},
booktitle = {Studi per Luigi Carlo Ubertazzi, Proprietà intellettuale e concorrenza},
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Marco Ricolfi
Le “caratteristiche tecniche di un prodotto determinate unicamente dalla sua funzione tecnica” nella giurisprudenza europea in tema di disegni e di modelli Journal Article
In: RIVISTA DI DIRITTO INDUSTRIALE, vol. LXVIII, no. 3, pp. 189–199, 2019.
@article{ 2318_1719189,
title = {Le “caratteristiche tecniche di un prodotto determinate unicamente dalla sua funzione tecnica” nella giurisprudenza europea in tema di disegni e di modelli},
author = {Marco Ricolfi},
year = {2019},
date = {2019-01-01},
journal = {RIVISTA DI DIRITTO INDUSTRIALE},
volume = {LXVIII},
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pages = {189–199},
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}
Marco Ricolfi
La proprietà intellettuale e le libertà antagoniste Book Chapter
In: I diritti fondamentali e il diritto privato, vol. 5, pp. 203–211, Roma Tre Press, Roma, 2019, ISBN: 9788832136135.
@inbook{ 2318_1708602,
title = {La proprietà intellettuale e le libertà antagoniste},
author = {Marco Ricolfi},
isbn = {9788832136135},
year = {2019},
date = {2019-01-01},
booktitle = {I diritti fondamentali e il diritto privato},
volume = {5},
pages = {203–211},
publisher = {Roma Tre Press},
address = {Roma},
keywords = {},
pubstate = {published},
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MARCO RICOLFI
Il futuro della proprietà intellettuale nella società algoritmica Journal Article
In: GIURISPRUDENZA ITALIANA, no. Supplemento, pp. 10–36, 2019.
@article{ 2318_1781275,
title = {Il futuro della proprietà intellettuale nella società algoritmica},
author = {MARCO RICOLFI},
year = {2019},
date = {2019-01-01},
journal = {GIURISPRUDENZA ITALIANA},
number = {Supplemento},
pages = {10–36},
abstract = {il saggio mostra come la proprietà intellettuale sia trasformata da algoritmi, Machine learning, Internet of Things, Intelligenza Artificiale e Piattaforme},
keywords = {},
pubstate = {published},
tppubtype = {article}
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il saggio mostra come la proprietà intellettuale sia trasformata da algoritmi, Machine learning, Internet of Things, Intelligenza Artificiale e Piattaforme
Rodrigo O. Spínola; Nico Zazworka; Antonio Vetro; Forrest Shull; Carolyn Seaman
Understanding automated and human-based technical debt identification approaches-a two-phase study Journal Article
In: JOURNAL OF THE BRAZILIAN COMPUTER SOCIETY, vol. 25, no. 1, 2019.
@article{ 11583_2735916,
title = {Understanding automated and human-based technical debt identification approaches-a two-phase study},
author = {Rodrigo O. Spínola and Nico Zazworka and Antonio Vetro and Forrest Shull and Carolyn Seaman},
url = {https://link.springer.com/article/10.1186/s13173-019-0087-5},
doi = {10.1186/s13173-019-0087-5},
year = {2019},
date = {2019-01-01},
journal = {JOURNAL OF THE BRAZILIAN COMPUTER SOCIETY},
volume = {25},
number = {1},
publisher = {SpringerOpen},
abstract = {Context: The technical debt (TD) concept inspires the development of useful methods and tools that support TD identification and management. However, there is a lack of evidence on how different TD identification tools could be complementary and, also, how human-based identification compares with them.
Objective: To understand how to effectively elicit TD from humans, to investigate several types of tools for TD identification, and to understand the developers’ point of view about TD indicators and items reported by tools.
Method: We asked developers to identify TD items from a real software project. We also collected the output of three tools to automatically identify TD and compared the results in terms of their locations in the source code. Then, we collected developers’ opinions on the identification process through a focus group.
Results: Aggregation seems to be an appropriate way to combine TD reported by developers. The tools used cannot help in identifying many important TD types, so involving humans is necessary. Developers reported that the tools would help them to identify TD faster or more accurately and that project priorities and current development activities are important to be considered together, along with the values of principal and interest, when deciding to pay off a debt.
Conclusion: This work contributes to the TD landscape, which depicts an understanding between different TD types and how they are best discovered.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Context: The technical debt (TD) concept inspires the development of useful methods and tools that support TD identification and management. However, there is a lack of evidence on how different TD identification tools could be complementary and, also, how human-based identification compares with them.
Objective: To understand how to effectively elicit TD from humans, to investigate several types of tools for TD identification, and to understand the developers’ point of view about TD indicators and items reported by tools.
Method: We asked developers to identify TD items from a real software project. We also collected the output of three tools to automatically identify TD and compared the results in terms of their locations in the source code. Then, we collected developers’ opinions on the identification process through a focus group.
Results: Aggregation seems to be an appropriate way to combine TD reported by developers. The tools used cannot help in identifying many important TD types, so involving humans is necessary. Developers reported that the tools would help them to identify TD faster or more accurately and that project priorities and current development activities are important to be considered together, along with the values of principal and interest, when deciding to pay off a debt.
Conclusion: This work contributes to the TD landscape, which depicts an understanding between different TD types and how they are best discovered.
Objective: To understand how to effectively elicit TD from humans, to investigate several types of tools for TD identification, and to understand the developers’ point of view about TD indicators and items reported by tools.
Method: We asked developers to identify TD items from a real software project. We also collected the output of three tools to automatically identify TD and compared the results in terms of their locations in the source code. Then, we collected developers’ opinions on the identification process through a focus group.
Results: Aggregation seems to be an appropriate way to combine TD reported by developers. The tools used cannot help in identifying many important TD types, so involving humans is necessary. Developers reported that the tools would help them to identify TD faster or more accurately and that project priorities and current development activities are important to be considered together, along with the values of principal and interest, when deciding to pay off a debt.
Conclusion: This work contributes to the TD landscape, which depicts an understanding between different TD types and how they are best discovered.
M. Conoscenti; V. Besner; A. Vetro; D. M. Fernandez
Combining data analytics and developers feedback for identifying reasons of inaccurate estimations in agile software development Journal Article
In: THE JOURNAL OF SYSTEMS AND SOFTWARE, vol. 156, pp. 126–135, 2019.
@article{ 11583_2747492,
title = {Combining data analytics and developers feedback for identifying reasons of inaccurate estimations in agile software development},
author = {M. Conoscenti and V. Besner and A. Vetro and D. M. Fernandez},
url = {http://www.sciencedirect.com/science/article/pii/S0164121219301372},
doi = {10.1016/j.jss.2019.06.075},
year = {2019},
date = {2019-01-01},
journal = {THE JOURNAL OF SYSTEMS AND SOFTWARE},
volume = {156},
pages = {126–135},
publisher = {Elsevier Inc.},
abstract = {Background: Effort estimations are critical tasks greatly influencing the accomplishment of software projects. Despite their recognized relevance, little is yet known what indicators for inaccurate estimations exist, and which are the reasons of inaccurate estimations. Aims: In this manuscript, we aim at contributing to this existing gap. To this end, we implemented a tool that combines data analytics and developers’ feedback, and we employed that tool in a study. In that study, we explored the most common reasons of inaccurate user story estimations and the possible indicators of inaccurate estimations. Method: We relied on a mixed method approach used to study reasons and indicators for the identification and prediction of inaccurate estimations in practical agile software development contexts. Results: Our results add to the existing body of knowledge in multiple ways. We elaborate causes for inaccurate estimations going beyond the borders of existing literature; for instance, we show that lack of developers’ experience is the most common reason of inaccurate estimations. Further, our results suggest, for example, that the higher the complexity, the higher the uncertainty in the estimation. Conclusions: Overall, our results strengthen our confidence in the usefulness of using data analytics with human-in-the-loop mechanisms to improve effort estimations.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Background: Effort estimations are critical tasks greatly influencing the accomplishment of software projects. Despite their recognized relevance, little is yet known what indicators for inaccurate estimations exist, and which are the reasons of inaccurate estimations. Aims: In this manuscript, we aim at contributing to this existing gap. To this end, we implemented a tool that combines data analytics and developers’ feedback, and we employed that tool in a study. In that study, we explored the most common reasons of inaccurate user story estimations and the possible indicators of inaccurate estimations. Method: We relied on a mixed method approach used to study reasons and indicators for the identification and prediction of inaccurate estimations in practical agile software development contexts. Results: Our results add to the existing body of knowledge in multiple ways. We elaborate causes for inaccurate estimations going beyond the borders of existing literature; for instance, we show that lack of developers’ experience is the most common reason of inaccurate estimations. Further, our results suggest, for example, that the higher the complexity, the higher the uncertainty in the estimation. Conclusions: Overall, our results strengthen our confidence in the usefulness of using data analytics with human-in-the-loop mechanisms to improve effort estimations.
Stefan Wagner; Daniel Méndez Fernández; Michael Felderer; Antonio Vetrò; Marcos Kalinowski; Roel Wieringa; Dietmar Pfahl; Tayana Conte; Marie-Therese Christiansson; Desmond Greer; Casper Lassenius; Tomi Männistö; Maleknaz Nayebi; Markku Oivo; Birgit Penzenstadler; Rafael Prikladnicki; Guenther Ruhe; André Schekelmann; Sagar Sen; Rodrigo Spínola; Ahmed Tuzcu; Jose Luis De La Vara; Dietmar Winkler
Status quo in requirements engineering: A theory and a global family of surveys Journal Article
In: ACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY, vol. 28, no. 2, pp. 1–48, 2019.
@article{ 11583_2729234,
title = {Status quo in requirements engineering: A theory and a global family of surveys},
author = {Stefan Wagner and Daniel Méndez Fernández and Michael Felderer and Antonio Vetrò and Marcos Kalinowski and Roel Wieringa and Dietmar Pfahl and Tayana Conte and Marie-Therese Christiansson and Desmond Greer and Casper Lassenius and Tomi Männistö and Maleknaz Nayebi and Markku Oivo and Birgit Penzenstadler and Rafael Prikladnicki and Guenther Ruhe and André Schekelmann and Sagar Sen and Rodrigo Spínola and Ahmed Tuzcu and Jose Luis De La Vara and Dietmar Winkler},
url = {https://dl.acm.org/citation.cfm?doid=3316413.3306607},
doi = {10.1145/3306607},
year = {2019},
date = {2019-01-01},
journal = {ACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY},
volume = {28},
number = {2},
pages = {1–48},
publisher = {Association for Computing Machinery},
abstract = {Requirements Engineering (RE) has established itself as a software engineering discipline over the past decades. While researchers have been investigating the RE discipline with a plethora of empirical studies, attempts to systematically derive an empirical theory in context of the RE discipline have just recently been started. However, such a theory is needed if we are to define and motivate guidance in performing high quality RE research and practice.We aim at providing an empirical and externally valid foundation for a theory of RE practice, which helps software engineers establish effective and efficient RE processes in a problem-driven manner.We designed a survey instrument and an engineer-focused theory that was first piloted in Germany and, after making substantial modifications, has now been replicated in 10 countries worldwide. We have a theory in the form of a set of propositions inferred from our experiences and available studies, as well as the results from our pilot study in Germany. We evaluate the propositions with bootstrapped confidence intervals and derive potential explanations for the propositions.
In this article, we report on the design of the family of surveys, its underlying theory, and the full results obtained from the replication studies conducted in 10 countries with participants from 228 organisations. Our results represent a substantial step forward towards developing an empirical theory of RE practice. The results reveal, for example, that there are no strong differences between organisations in different countries and regions, that interviews, facilitated meetings and prototyping are the most used elicitation techniques, that requirements are often documented textually, that traces between requirements and code or design documents are common, that requirements specifications themselves are rarely changed and that requirements engineering (process) improvement endeavours are mostly internally driven. Our study establishes a theory that can be used as starting point for many further studies for more detailed investigations. Practitioners can use the results as theory-supported guidance on selecting suitable RE methods and techniques.},
keywords = {},
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Requirements Engineering (RE) has established itself as a software engineering discipline over the past decades. While researchers have been investigating the RE discipline with a plethora of empirical studies, attempts to systematically derive an empirical theory in context of the RE discipline have just recently been started. However, such a theory is needed if we are to define and motivate guidance in performing high quality RE research and practice.We aim at providing an empirical and externally valid foundation for a theory of RE practice, which helps software engineers establish effective and efficient RE processes in a problem-driven manner.We designed a survey instrument and an engineer-focused theory that was first piloted in Germany and, after making substantial modifications, has now been replicated in 10 countries worldwide. We have a theory in the form of a set of propositions inferred from our experiences and available studies, as well as the results from our pilot study in Germany. We evaluate the propositions with bootstrapped confidence intervals and derive potential explanations for the propositions.
In this article, we report on the design of the family of surveys, its underlying theory, and the full results obtained from the replication studies conducted in 10 countries with participants from 228 organisations. Our results represent a substantial step forward towards developing an empirical theory of RE practice. The results reveal, for example, that there are no strong differences between organisations in different countries and regions, that interviews, facilitated meetings and prototyping are the most used elicitation techniques, that requirements are often documented textually, that traces between requirements and code or design documents are common, that requirements specifications themselves are rarely changed and that requirements engineering (process) improvement endeavours are mostly internally driven. Our study establishes a theory that can be used as starting point for many further studies for more detailed investigations. Practitioners can use the results as theory-supported guidance on selecting suitable RE methods and techniques.
In this article, we report on the design of the family of surveys, its underlying theory, and the full results obtained from the replication studies conducted in 10 countries with participants from 228 organisations. Our results represent a substantial step forward towards developing an empirical theory of RE practice. The results reveal, for example, that there are no strong differences between organisations in different countries and regions, that interviews, facilitated meetings and prototyping are the most used elicitation techniques, that requirements are often documented textually, that traces between requirements and code or design documents are common, that requirements specifications themselves are rarely changed and that requirements engineering (process) improvement endeavours are mostly internally driven. Our study establishes a theory that can be used as starting point for many further studies for more detailed investigations. Practitioners can use the results as theory-supported guidance on selecting suitable RE methods and techniques.
E. Beretta; A. Santangelo; B. Lepri; A. Vetro; J. C. De Martin
The Invisible Power of Fairness. How Machine Learning Shapes Democracy Conference
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11489, Springer Verlag, 2019, ISBN: 978-3-030-18305-9.
@conference{<LineBreak> 11583_2735174,
title = {The Invisible Power of Fairness. How Machine Learning Shapes Democracy},
author = {E. Beretta and A. Santangelo and B. Lepri and A. Vetro and J. C. De Martin},
url = {https://www.springer.com/series/558},
doi = {10.1007/978-3-030-18305-9_19},
isbn = {978-3-030-18305-9},
year = {2019},
date = {2019-01-01},
urldate = {2019-01-01},
booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
volume = {11489},
pages = {238–250},
publisher = {Springer Verlag},
abstract = {Many machine learning systems make extensive use of large amounts of data regarding human behaviors. Several researchers have found various discriminatory practices related to the use of human-related machine learning systems, for example in the field of criminal justice, credit scoring and advertising. Fair machine learning is therefore emerging as a new field of study to mitigate biases that are inadvertently incorporated into algorithms. Data scientists and computer engineers are making various efforts to provide definitions of fairness. In this paper, we provide an overview of the most widespread definitions of fairness in the field of machine learning, arguing that the ideas highlighting each formalization are closely related to different ideas of justice and to different interpretations of democracy embedded in our culture. This work intends to analyze the definitions of fairness that have been proposed to date to interpret the underlying criteria and to relate them to different ideas of democracy.},
keywords = {},
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Many machine learning systems make extensive use of large amounts of data regarding human behaviors. Several researchers have found various discriminatory practices related to the use of human-related machine learning systems, for example in the field of criminal justice, credit scoring and advertising. Fair machine learning is therefore emerging as a new field of study to mitigate biases that are inadvertently incorporated into algorithms. Data scientists and computer engineers are making various efforts to provide definitions of fairness. In this paper, we provide an overview of the most widespread definitions of fairness in the field of machine learning, arguing that the ideas highlighting each formalization are closely related to different ideas of justice and to different interpretations of democracy embedded in our culture. This work intends to analyze the definitions of fairness that have been proposed to date to interpret the underlying criteria and to relate them to different ideas of democracy.
Mina Roohnavazfar; Daniele Manerba; Juan Carlos De Martin; Roberto Tadei
Optimal paths in multi-stage stochastic decision networks Journal Article
In: OPERATIONS RESEARCH PERSPECTIVES, vol. 6, no. 100124, pp. 1–10, 2019.
@article{<LineBreak> 11583_2752646,
title = {Optimal paths in multi-stage stochastic decision networks},
author = {Mina Roohnavazfar and Daniele Manerba and Juan Carlos De Martin and Roberto Tadei},
url = {https://www.sciencedirect.com/science/article/pii/S221471601930096X},
doi = {10.1016/j.orp.2019.100124},
year = {2019},
date = {2019-01-01},
urldate = {2019-01-01},
journal = {OPERATIONS RESEARCH PERSPECTIVES},
volume = {6},
number = {100124},
pages = {1–10},
publisher = {Elsevier},
abstract = {This paper deals with the search of optimal paths in a multi-stage stochastic decision network as a first application of the deterministic approximation approach proposed by Tadei et al. (2019). In the network, the involved utilities are stage-dependent and contain random oscillations with an unknown probability distribution. The problem is modeled as a sequential choice of nodes in a graph layered into stages, in order to find the optimal path value in a recursive fashion. It is also shown that an optimal path solution can be derived by using a Nested Multinomial Logit model, which represents the choice probability at the different stages. The accuracy and efficiency of the proposed method are experimentally proved on a large set of randomly generated instances. Moreover, insights on the calibration of a critical parameter of the deterministic approximation are also provided.},
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This paper deals with the search of optimal paths in a multi-stage stochastic decision network as a first application of the deterministic approximation approach proposed by Tadei et al. (2019). In the network, the involved utilities are stage-dependent and contain random oscillations with an unknown probability distribution. The problem is modeled as a sequential choice of nodes in a graph layered into stages, in order to find the optimal path value in a recursive fashion. It is also shown that an optimal path solution can be derived by using a Nested Multinomial Logit model, which represents the choice probability at the different stages. The accuracy and efficiency of the proposed method are experimentally proved on a large set of randomly generated instances. Moreover, insights on the calibration of a critical parameter of the deterministic approximation are also provided.
Antonio Vetrò; Antonio Santangelo; Elena Beretta; Juan Carlos De Martin
AI: from rational agents to socially responsible agents Journal Article
In: DIGITAL POLICY, REGULATION AND GOVERNANCE, vol. 21, no. 3, pp. 291–304, 2019.
@article{ 11583_2729235,
title = {AI: from rational agents to socially responsible agents},
author = {Antonio Vetrò and Antonio Santangelo and Elena Beretta and Juan Carlos De Martin},
url = {https://doi.org/10.1108/DPRG-08-2018-0049},
doi = {10.1108/DPRG-08-2018-0049},
year = {2019},
date = {2019-01-01},
journal = {DIGITAL POLICY, REGULATION AND GOVERNANCE},
volume = {21},
number = {3},
pages = {291–304},
publisher = {Emerald Group Publishing Ltd.},
abstract = {Purpose: This paper aims to analyze the limitations of the mainstream definition of artificial intelligence (AI) as a rational agent, which currently drives the development of most AI systems. The authors advocate the need of a wider range of driving ethical principles for designing more socially responsible AI agents.
Design/methodology/approach: The authors follow an experience-based line of reasoning by argument to identify the limitations of the mainstream definition of AI, which is based on the concept of rational agents that select, among their designed actions, those which produce the maximum expected utility in the environment in which they operate. The problem of biases in the data used by AI is taken as example, and a small proof of concept with real datasets is provided.
Findings: The authors observe that biases measurements on the datasets are sufficient to demonstrate potential risks of discriminations when using those data in AI rational agents. Starting from this example, the authors discuss other open issues connected to AI rational agents and provide a few general ethical principles derived from the White Paper AI at the service of the citizen, recently published by Agid, the agency of the Italian Government which designs and monitors the evolution of the IT systems of the Public Administration.
Originality/value: The paper contributes to the scientific debate on the governance and the ethics of AI with a critical analysis of the mainstream definition of AI.},
keywords = {},
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Purpose: This paper aims to analyze the limitations of the mainstream definition of artificial intelligence (AI) as a rational agent, which currently drives the development of most AI systems. The authors advocate the need of a wider range of driving ethical principles for designing more socially responsible AI agents.
Design/methodology/approach: The authors follow an experience-based line of reasoning by argument to identify the limitations of the mainstream definition of AI, which is based on the concept of rational agents that select, among their designed actions, those which produce the maximum expected utility in the environment in which they operate. The problem of biases in the data used by AI is taken as example, and a small proof of concept with real datasets is provided.
Findings: The authors observe that biases measurements on the datasets are sufficient to demonstrate potential risks of discriminations when using those data in AI rational agents. Starting from this example, the authors discuss other open issues connected to AI rational agents and provide a few general ethical principles derived from the White Paper AI at the service of the citizen, recently published by Agid, the agency of the Italian Government which designs and monitors the evolution of the IT systems of the Public Administration.
Originality/value: The paper contributes to the scientific debate on the governance and the ethics of AI with a critical analysis of the mainstream definition of AI.
Design/methodology/approach: The authors follow an experience-based line of reasoning by argument to identify the limitations of the mainstream definition of AI, which is based on the concept of rational agents that select, among their designed actions, those which produce the maximum expected utility in the environment in which they operate. The problem of biases in the data used by AI is taken as example, and a small proof of concept with real datasets is provided.
Findings: The authors observe that biases measurements on the datasets are sufficient to demonstrate potential risks of discriminations when using those data in AI rational agents. Starting from this example, the authors discuss other open issues connected to AI rational agents and provide a few general ethical principles derived from the White Paper AI at the service of the citizen, recently published by Agid, the agency of the Italian Government which designs and monitors the evolution of the IT systems of the Public Administration.
Originality/value: The paper contributes to the scientific debate on the governance and the ethics of AI with a critical analysis of the mainstream definition of AI.
Elena Beretta; Antonio Vetro’; Lepri Bruno; Juan Carlos De Martin
Ethical and Socially-Aware Data Labels Conference
Information Management and Big Data, vol. 898, Springer International Publishing, Cham, 2019, ISBN: 978-3-030-11679-8.
@conference{<LineBreak> 11583_2713217,
title = {Ethical and Socially-Aware Data Labels},
author = {Elena Beretta and Antonio Vetro' and Lepri Bruno and Juan Carlos De Martin},
url = {https://link.springer.com/chapter/10.1007%2F978-3-030-11680-4_30},
doi = {10.1007/978-3-030-11680-4_30},
isbn = {978-3-030-11679-8},
year = {2019},
date = {2019-01-01},
urldate = {2019-01-01},
booktitle = {Information Management and Big Data},
volume = {898},
pages = {320–327},
publisher = {Springer International Publishing},
address = {Cham},
abstract = {Many software systems today make use of large amount of personal data to make recommendations or decisions that affect our daily lives. These software systems generally operate without guarantees of non-discriminatory practices, as instead often required to human decision-makers, and therefore are attracting increasing scrutiny. Our research is focused on the specific problem of biased software-based decisions caused from biased input data. In this regard, we propose a data labeling framework based on the identification of measurable data characteristics that could lead to downstream discriminating effects. We test the proposed framework on a real dataset, which allowed us to detect risks of discrimination for the case of population groups.},
keywords = {},
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tppubtype = {conference}
}
Many software systems today make use of large amount of personal data to make recommendations or decisions that affect our daily lives. These software systems generally operate without guarantees of non-discriminatory practices, as instead often required to human decision-makers, and therefore are attracting increasing scrutiny. Our research is focused on the specific problem of biased software-based decisions caused from biased input data. In this regard, we propose a data labeling framework based on the identification of measurable data characteristics that could lead to downstream discriminating effects. We test the proposed framework on a real dataset, which allowed us to detect risks of discrimination for the case of population groups.
2018
Emanuele Mottola; Marco Pietro Abrate; Diego Mariani; Antonio Vetrò
Power Aware final report Technical Report
2018.
@techreport{nokey,
title = {Power Aware final report},
author = {Emanuele Mottola and Marco Pietro Abrate and Diego Mariani and Antonio Vetrò },
url = {https://nexa.polito.it/wp-content/uploads/2024/07/PowerAware-finale-DEF.pdf},
year = {2018},
date = {2018-10-12},
abstract = {Power Aware is a research project aimed at understating the key requirements for building up a CAP focused on the development of a network of knowledge shared among citizens about energy consumption issues and possible solutions. It has been funded by the Siebel Energy Foundation.
The project exploits Aritificial Intelligence techniques and data visualization in order to drive behavioral changes at individual and collective level, encouraging participation of users through competition and cooperation among them. Therefore, the goal of the platform is to engage citizens in changing their consumption patterns.
The report summarizes the findings of the feasibility study for the platform.},
keywords = {},
pubstate = {published},
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}
Power Aware is a research project aimed at understating the key requirements for building up a CAP focused on the development of a network of knowledge shared among citizens about energy consumption issues and possible solutions. It has been funded by the Siebel Energy Foundation.
The project exploits Aritificial Intelligence techniques and data visualization in order to drive behavioral changes at individual and collective level, encouraging participation of users through competition and cooperation among them. Therefore, the goal of the platform is to engage citizens in changing their consumption patterns.
The report summarizes the findings of the feasibility study for the platform.
The project exploits Aritificial Intelligence techniques and data visualization in order to drive behavioral changes at individual and collective level, encouraging participation of users through competition and cooperation among them. Therefore, the goal of the platform is to engage citizens in changing their consumption patterns.
The report summarizes the findings of the feasibility study for the platform.
Marco Conoscenti; Antonio Vetrò; Juan Carlos De Martin; Federico Spini
The CLoTH Simulator for HTLC Payment Networks with Introductory Lightning Network Performance Results Journal Article
In: Information, vol. 9, no. 223, pp. 1–26, 2018.
@article{<LineBreak> 11583_2712593,
title = {The CLoTH Simulator for HTLC Payment Networks with Introductory Lightning Network Performance Results},
author = {Marco Conoscenti and Antonio Vetrò and Juan Carlos De Martin and Federico Spini},
url = {www.mdpi.com/2078-2489/9/9/223/pdf},
doi = {10.3390/info9090223},
year = {2018},
date = {2018-09-01},
urldate = {2018-01-01},
journal = {Information},
volume = {9},
number = {223},
pages = {1–26},
publisher = {MDPI},
abstract = {The Lightning Network (LN) is one of the most promising off-chain scaling solutions for Bitcoin, as it enables off-chain payments which are not subject to the well-known blockchain scalability limit. In this work, we introduce CLoTH, a simulator for HTLC payment networks (of which LN is the best working example). It simulates input-defined payments on an input-defined HTLC network and produces performance measures in terms of payment-related statistics (such as time to complete payments and probability of payment failure). CLoTH helps to predict issues and obstacles that might emerge in the development stages of an HTLC payment network and to estimate the effects of an optimisation action before deploying it. We conducted simulations on a recent snapshot of the HTLC payment network of LN. These simulations allowed us to identify network and payments configurations for which a payment is more likely to fail than to succeed. We proposed viable solutions to avoid such configurations.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The Lightning Network (LN) is one of the most promising off-chain scaling solutions for Bitcoin, as it enables off-chain payments which are not subject to the well-known blockchain scalability limit. In this work, we introduce CLoTH, a simulator for HTLC payment networks (of which LN is the best working example). It simulates input-defined payments on an input-defined HTLC network and produces performance measures in terms of payment-related statistics (such as time to complete payments and probability of payment failure). CLoTH helps to predict issues and obstacles that might emerge in the development stages of an HTLC payment network and to estimate the effects of an optimisation action before deploying it. We conducted simulations on a recent snapshot of the HTLC payment network of LN. These simulations allowed us to identify network and payments configurations for which a payment is more likely to fail than to succeed. We proposed viable solutions to avoid such configurations.
Fabio Chiusi; Antonio Santangelo
Persuasori Social Technical Report
2018.
@techreport{nokey,
title = {Persuasori Social},
author = {Fabio Chiusi and Antonio Santangelo },
url = {https://nexa.polito.it/wp-content/uploads/2024/07/Persuasori-Social-Finale.pdf},
year = {2018},
date = {2018-05-30},
urldate = {2018-05-30},
abstract = {Questo documento è il risultato del primo laboratorio sull’innovazione critica del Progetto Punto Zero, ‘Persuasori social’, svoltosi tra novembre 2017 e aprile 2018, che ha visto la partecipazione di una serie di portatori di interesse, tra cui partiti politici, agenzie di comunicazione, autorità indipendenti, iattaforme digitali, sindacati, ordini professionali, giornalisti ed esperti. Tutti questi soggetti sono stati coinvolti per stimolare un dibattito informato su come, concretamente, ciascuno può contribuire alla creazione di strumenti e soluzioni che garantiscano il buon funzionamento dei meccanismi democratici.
Con il lavoro del team di Punto Zero, e grazie alla collaborazione attiva degli stakeholder, il progetto ha affrontato il tema, oggi più spinoso che mai, della trasparenza e del rispetto delle tutele democratiche nelle campagne politiche digitali:
— fornendo un rapporto dettagliato sullo stato dell’arte delle conoscenze scientifiche e dei fatti di attualità rilevanti in materia, così da costruire un terreno di conoscenze comuni per una successiva discussione informata e consapevole con e tra i partecipanti (gli “stakeholder”);
— riassumendo i contributi forniti dagli stakeholder, sia nelle interviste individuali a loro effettuate dal team di Punto Zero nel corso dei mesi di febbraio e marzo 2018, sia negli incontri plenari tenutisi a gennaio, marzo e aprile 2018;
— formulando una serie di raccomandazioni concretamente attuabili, nella politica come nelle istituzioni, che distillino quanto emerso nel dibattito ragionato tra stakeholder; tali raccomandazioni sono organizzate secondo tre categorie: interventi e soluzioni positive più o meno largamente condivise dai partecipanti, interventi e soluzioni comunemente ritenute da evitare, e temi su cui invece si è riscontrato un più ampio spettro di opinioni divergenti.
Il team di progetto ha inoltre partecipato ai lavori del “Tavolo Tecnico per la garanzia del pluralismo e della correttezza dell’informazione sulle piattaforme digitali” istituito dall’Autorità per le Garanzie nelle Comunicazioni.},
howpublished = {Trasparenza e democrazia nelle campagne elettorali digitali},
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pubstate = {published},
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}
Questo documento è il risultato del primo laboratorio sull’innovazione critica del Progetto Punto Zero, ‘Persuasori social’, svoltosi tra novembre 2017 e aprile 2018, che ha visto la partecipazione di una serie di portatori di interesse, tra cui partiti politici, agenzie di comunicazione, autorità indipendenti, iattaforme digitali, sindacati, ordini professionali, giornalisti ed esperti. Tutti questi soggetti sono stati coinvolti per stimolare un dibattito informato su come, concretamente, ciascuno può contribuire alla creazione di strumenti e soluzioni che garantiscano il buon funzionamento dei meccanismi democratici.
Con il lavoro del team di Punto Zero, e grazie alla collaborazione attiva degli stakeholder, il progetto ha affrontato il tema, oggi più spinoso che mai, della trasparenza e del rispetto delle tutele democratiche nelle campagne politiche digitali:
— fornendo un rapporto dettagliato sullo stato dell’arte delle conoscenze scientifiche e dei fatti di attualità rilevanti in materia, così da costruire un terreno di conoscenze comuni per una successiva discussione informata e consapevole con e tra i partecipanti (gli “stakeholder”);
— riassumendo i contributi forniti dagli stakeholder, sia nelle interviste individuali a loro effettuate dal team di Punto Zero nel corso dei mesi di febbraio e marzo 2018, sia negli incontri plenari tenutisi a gennaio, marzo e aprile 2018;
— formulando una serie di raccomandazioni concretamente attuabili, nella politica come nelle istituzioni, che distillino quanto emerso nel dibattito ragionato tra stakeholder; tali raccomandazioni sono organizzate secondo tre categorie: interventi e soluzioni positive più o meno largamente condivise dai partecipanti, interventi e soluzioni comunemente ritenute da evitare, e temi su cui invece si è riscontrato un più ampio spettro di opinioni divergenti.
Il team di progetto ha inoltre partecipato ai lavori del “Tavolo Tecnico per la garanzia del pluralismo e della correttezza dell’informazione sulle piattaforme digitali” istituito dall’Autorità per le Garanzie nelle Comunicazioni.
Con il lavoro del team di Punto Zero, e grazie alla collaborazione attiva degli stakeholder, il progetto ha affrontato il tema, oggi più spinoso che mai, della trasparenza e del rispetto delle tutele democratiche nelle campagne politiche digitali:
— fornendo un rapporto dettagliato sullo stato dell’arte delle conoscenze scientifiche e dei fatti di attualità rilevanti in materia, così da costruire un terreno di conoscenze comuni per una successiva discussione informata e consapevole con e tra i partecipanti (gli “stakeholder”);
— riassumendo i contributi forniti dagli stakeholder, sia nelle interviste individuali a loro effettuate dal team di Punto Zero nel corso dei mesi di febbraio e marzo 2018, sia negli incontri plenari tenutisi a gennaio, marzo e aprile 2018;
— formulando una serie di raccomandazioni concretamente attuabili, nella politica come nelle istituzioni, che distillino quanto emerso nel dibattito ragionato tra stakeholder; tali raccomandazioni sono organizzate secondo tre categorie: interventi e soluzioni positive più o meno largamente condivise dai partecipanti, interventi e soluzioni comunemente ritenute da evitare, e temi su cui invece si è riscontrato un più ampio spettro di opinioni divergenti.
Il team di progetto ha inoltre partecipato ai lavori del “Tavolo Tecnico per la garanzia del pluralismo e della correttezza dell’informazione sulle piattaforme digitali” istituito dall’Autorità per le Garanzie nelle Comunicazioni.
Task Force IA dell’Agenzia per l’Italia digitale
L’Intelligenza Artificiale. Il Libro Bianco dell’AGID Technical Report
2018.
@techreport{nokey,
title = {L'Intelligenza Artificiale. Il Libro Bianco dell'AGID},
author = {Task Force IA dell’Agenzia per l’Italia digitale},
url = {https://nexa.polito.it/wp-content/uploads/2024/06/librobianco_AI.pdf},
year = {2018},
date = {2018-03-01},
urldate = {2018-03-01},
abstract = {L’obiettivo di questo Libro Bianco è quello di analizzare l’impatto dell’Intelligenza Artificiale (IA) sulla nostra società e, nello specifico, come queste tecnologie possano essere utilizzate dalla Pubblica amministrazione (PA) per migliorare i servizi destinati ai cittadini e alle imprese. Tutto questo si inserisce all’interno di un quadro più ampio di riflessione sulle politiche da mettere in atto per favorire la trasformazione digitale, motore di sviluppo sociale, economico e culturale.
Per accelerare questo processo di trasformazione è possibile ispirarsi a esperienze internazionali che hanno portato risultati tangibili: l’Italia deve eccellere nella ricerca di strategie innovative, magari capaci di nutrirsi della ricchezza storica, culturale e sociale del Paese e del Mediterraneo e allo stesso tempo riuscire a cogliere quanto di meglio sia emerso dalle strategie di quegli Stati che, per primi, hanno saputo fare dell’evoluzione dell’informatica pubblica la leva per la transizione verso un nuovo assetto globale di economia e società.
È, quindi, necessario sostenere le forze di innovazione del Paese per ottenere modelli sempre più competitivi e avviare un cambiamento radicale delle modalità di relazione tra cittadini, amministrazioni e mercato. L’obiettivo finale di questo processo è la creazione di servizi pubblici moderni, di semplice utilizzo, accessibili, di qualità, orientati dunque alla comprensione dei bisogni degli utenti, che permettano quindi di accrescere il livello di soddisfazione del cittadino e la fiducia nelle istituzioni.
Il documento intende delineare le prospettive di sviluppo dei servizi pubblici digitali e le sfide che il Paese dovrà affrontare per implementare e adoperare le nuove tecnologie nel rispetto dell’etica e delle leggi mettendo il cittadino al centro di questo percorso evolutivo.},
keywords = {},
pubstate = {published},
tppubtype = {techreport}
}
L’obiettivo di questo Libro Bianco è quello di analizzare l’impatto dell’Intelligenza Artificiale (IA) sulla nostra società e, nello specifico, come queste tecnologie possano essere utilizzate dalla Pubblica amministrazione (PA) per migliorare i servizi destinati ai cittadini e alle imprese. Tutto questo si inserisce all’interno di un quadro più ampio di riflessione sulle politiche da mettere in atto per favorire la trasformazione digitale, motore di sviluppo sociale, economico e culturale.
Per accelerare questo processo di trasformazione è possibile ispirarsi a esperienze internazionali che hanno portato risultati tangibili: l’Italia deve eccellere nella ricerca di strategie innovative, magari capaci di nutrirsi della ricchezza storica, culturale e sociale del Paese e del Mediterraneo e allo stesso tempo riuscire a cogliere quanto di meglio sia emerso dalle strategie di quegli Stati che, per primi, hanno saputo fare dell’evoluzione dell’informatica pubblica la leva per la transizione verso un nuovo assetto globale di economia e società.
È, quindi, necessario sostenere le forze di innovazione del Paese per ottenere modelli sempre più competitivi e avviare un cambiamento radicale delle modalità di relazione tra cittadini, amministrazioni e mercato. L’obiettivo finale di questo processo è la creazione di servizi pubblici moderni, di semplice utilizzo, accessibili, di qualità, orientati dunque alla comprensione dei bisogni degli utenti, che permettano quindi di accrescere il livello di soddisfazione del cittadino e la fiducia nelle istituzioni.
Il documento intende delineare le prospettive di sviluppo dei servizi pubblici digitali e le sfide che il Paese dovrà affrontare per implementare e adoperare le nuove tecnologie nel rispetto dell’etica e delle leggi mettendo il cittadino al centro di questo percorso evolutivo.
Per accelerare questo processo di trasformazione è possibile ispirarsi a esperienze internazionali che hanno portato risultati tangibili: l’Italia deve eccellere nella ricerca di strategie innovative, magari capaci di nutrirsi della ricchezza storica, culturale e sociale del Paese e del Mediterraneo e allo stesso tempo riuscire a cogliere quanto di meglio sia emerso dalle strategie di quegli Stati che, per primi, hanno saputo fare dell’evoluzione dell’informatica pubblica la leva per la transizione verso un nuovo assetto globale di economia e società.
È, quindi, necessario sostenere le forze di innovazione del Paese per ottenere modelli sempre più competitivi e avviare un cambiamento radicale delle modalità di relazione tra cittadini, amministrazioni e mercato. L’obiettivo finale di questo processo è la creazione di servizi pubblici moderni, di semplice utilizzo, accessibili, di qualità, orientati dunque alla comprensione dei bisogni degli utenti, che permettano quindi di accrescere il livello di soddisfazione del cittadino e la fiducia nelle istituzioni.
Il documento intende delineare le prospettive di sviluppo dei servizi pubblici digitali e le sfide che il Paese dovrà affrontare per implementare e adoperare le nuove tecnologie nel rispetto dell’etica e delle leggi mettendo il cittadino al centro di questo percorso evolutivo.
Massimiliano Nuccio
Contestable markets and price discrimination in data-driven businesses Journal Article
In: 2018.
@article{nucciocontestable,
title = {Contestable markets and price discrimination in data-driven businesses},
author = {Massimiliano Nuccio},
year = {2018},
date = {2018-01-01},
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Mattia Plazio; Francesco Ruggiero; Juan Carlos De Martin
Navigando (a vista) sul Lete Journal Article
In: DigitCult-Scientific Journal on Digital Cultures, vol. 3, no. 1, pp. 13–24, 2018.
@article{plazio2018navigando,
title = {Navigando (a vista) sul Lete},
author = {Mattia Plazio and Francesco Ruggiero and Juan Carlos De Martin},
year = {2018},
date = {2018-01-01},
journal = {DigitCult-Scientific Journal on Digital Cultures},
volume = {3},
number = {1},
pages = {13–24},
keywords = {},
pubstate = {published},
tppubtype = {article}
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Pasquale Pellegrino
“Don’t Break Those Norms.” WhatsApp Socio-Technical Practices in Light of Contextual Integrity and Technology Affordances Journal Article
In: DigitCult-Scientific Journal on Digital Cultures, vol. 3, no. 1, pp. 73–88, 2018.
@article{pellegrino2018don,
title = {“Don't Break Those Norms.” WhatsApp Socio-Technical Practices in Light of Contextual Integrity and Technology Affordances},
author = {Pasquale Pellegrino},
year = {2018},
date = {2018-01-01},
journal = {DigitCult-Scientific Journal on Digital Cultures},
volume = {3},
number = {1},
pages = {73–88},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Giuseppe Futia; Federico Morando; Alessio Melandri; Lorenzo Canova; Francesco Ruggiero
ContrattiPubblici.org, a Semantic Knowledge Graph on Public Procurement Information Conference
AI Approaches to the Complexity of Legal Systems, Springer, 2018, ISBN: 978-3-030-00177-3.
@conference{<LineBreak> 11583_2659315,
title = {ContrattiPubblici.org, a Semantic Knowledge Graph on Public Procurement Information},
author = {Giuseppe Futia and Federico Morando and Alessio Melandri and Lorenzo Canova and Francesco Ruggiero},
url = {https://link.springer.com/chapter/10.1007/978-3-030-00178-0_26},
doi = {10.1007/978-3-030-00178-0_26},
isbn = {978-3-030-00177-3},
year = {2018},
date = {2018-01-01},
urldate = {2018-01-01},
booktitle = {AI Approaches to the Complexity of Legal Systems},
pages = {380–393},
publisher = {Springer},
abstract = {The Italian anti-corruption Act (law n. 190/2012) requires all public administrations to spread procurement information as open data. Each body is therefore obliged to yearly release standardized XML files, on its public website, containing data that describe all issued public contracts. Though this information is currently available on a machine- readable format, the data is fragmented and published in different files on different websites, without a unified and human-readable view of the information. The ContrattiPubblici.org project aims at developing a se- mantic knowledge graph based on linked open data principles in order to overcome the fragmentation of existent datasets and to allow easy anal- ysis and the reuse of information. The objectives are to increase public awareness about public spending, to improve transparency on the public procurement chain and to help companies to retrieve useful knowledge for their business activities.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
The Italian anti-corruption Act (law n. 190/2012) requires all public administrations to spread procurement information as open data. Each body is therefore obliged to yearly release standardized XML files, on its public website, containing data that describe all issued public contracts. Though this information is currently available on a machine- readable format, the data is fragmented and published in different files on different websites, without a unified and human-readable view of the information. The ContrattiPubblici.org project aims at developing a se- mantic knowledge graph based on linked open data principles in order to overcome the fragmentation of existent datasets and to allow easy anal- ysis and the reuse of information. The objectives are to increase public awareness about public spending, to improve transparency on the public procurement chain and to help companies to retrieve useful knowledge for their business activities.