Slide
Centre Interdisciplinaire
de Recherche et d’Innovation
en Cybersécurité et Société
de Recherche et d’Innovation
en Cybersécurité et Société
1.
Damadi, M. S.; Davoust, A.
Fairness in social machines: a systematic review Article de journal
Dans: Journal of Information, Communication and Ethics in Society, p. 1–40, 2026, ISSN: 1477996X (ISSN).
Résumé | Liens | BibTeX | Étiquettes: Cultural bias, Discrimination, Fairness, Gender bias, Geographic bias, Social machines
@article{damadi_fairness_2026,
title = {Fairness in social machines: a systematic review},
author = {M. S. Damadi and A. Davoust},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105030531101&doi=10.1108%2FJICES-01-2025-0002&partnerID=40&md5=63e2f87ee3852ffe2d49c514e38cba1c},
doi = {10.1108/JICES-01-2025-0002},
issn = {1477996X (ISSN)},
year = {2026},
date = {2026-01-01},
journal = {Journal of Information, Communication and Ethics in Society},
pages = {1–40},
abstract = {Purpose – The purpose of the paper is to provide a systematic review of biases in social machines to better understand the general problem of fairness in these systems. It aims to identify and categorize phenomena described as biases toward specific demographic groups, frame them normatively as harmful and relate them to established fairness concepts originally defined for algorithmic systems. Design/methodology/approach – The phenomenon of algorithmic bias refers to systematic biases against identifiable demographic groups that occur in automated decisions systems. Such biases have mostly been studied in the context of black-box decision systems built using machine learning (ML). However, similar problems have also been reported in complex socio-technical systems such as Wikipedia and Airbnb, known more generally as social machines, where the observed biases cannot necessarily be attributed to specific automated decision systems. Instead, the biases may emerge as a result of complex processes involving numerous users and a computational infrastructure. To gain a better understanding of fairness in social machines, the authors select a representative sample of social machines from six distinct categories, and systematically review the literature reporting biases in these systems, covering 196 papers. The authors classify the reported bias phenomena, identify the affected demographic groups and relate the phenomena to established notions of harm from algorithmic fairness research. Finally, the authors identify the normative expectations of fairness associated with the different problems and discuss the applicability of existing criteria proposed for ML-driven decision systems. The analysis highlights the conceptual similarity of bias phenomena between algorithmic systems and social machines, allowing for a shared vocabulary to describe and compare phenomena across a broad class of systems. Findings – The paper identifies two key biases in social machines: representational harm, from underrepresentation or biased portrayal of disadvantaged groups, and allocative harm, from unfair decision processes, measurable via metrics like demographic parity. Gender bias is prevalent and easier to detect due to explicit markers, offering insights for identifying other biases. Unique biases arise from user categorizations, creating unintended discrimination linked to protected characteristics. These biases result from complex user interactions, not isolated algorithms. Addressing them requires redesigning social machines, focusing on computational infrastructure and interaction norms, such as visibility settings, to mitigate harmful outcomes. Originality/value – The paper’s originality lies in its systematic review of biases in social machines, offering a novel perspective on fairness in these systems. Unlike prior studies focusing solely on algorithmic fairness, this work examines the broader socio-technical interactions within social machines, identifying biases that emerge from user interactions and design choices. By linking these biases to established fairness concepts like demographic parity and representational harm, the paper bridges the gap between algorithmic fairness and social dynamics. © 2025 Emerald Publishing Limited},
keywords = {Cultural bias, Discrimination, Fairness, Gender bias, Geographic bias, Social machines},
pubstate = {published},
tppubtype = {article}
}
Purpose – The purpose of the paper is to provide a systematic review of biases in social machines to better understand the general problem of fairness in these systems. It aims to identify and categorize phenomena described as biases toward specific demographic groups, frame them normatively as harmful and relate them to established fairness concepts originally defined for algorithmic systems. Design/methodology/approach – The phenomenon of algorithmic bias refers to systematic biases against identifiable demographic groups that occur in automated decisions systems. Such biases have mostly been studied in the context of black-box decision systems built using machine learning (ML). However, similar problems have also been reported in complex socio-technical systems such as Wikipedia and Airbnb, known more generally as social machines, where the observed biases cannot necessarily be attributed to specific automated decision systems. Instead, the biases may emerge as a result of complex processes involving numerous users and a computational infrastructure. To gain a better understanding of fairness in social machines, the authors select a representative sample of social machines from six distinct categories, and systematically review the literature reporting biases in these systems, covering 196 papers. The authors classify the reported bias phenomena, identify the affected demographic groups and relate the phenomena to established notions of harm from algorithmic fairness research. Finally, the authors identify the normative expectations of fairness associated with the different problems and discuss the applicability of existing criteria proposed for ML-driven decision systems. The analysis highlights the conceptual similarity of bias phenomena between algorithmic systems and social machines, allowing for a shared vocabulary to describe and compare phenomena across a broad class of systems. Findings – The paper identifies two key biases in social machines: representational harm, from underrepresentation or biased portrayal of disadvantaged groups, and allocative harm, from unfair decision processes, measurable via metrics like demographic parity. Gender bias is prevalent and easier to detect due to explicit markers, offering insights for identifying other biases. Unique biases arise from user categorizations, creating unintended discrimination linked to protected characteristics. These biases result from complex user interactions, not isolated algorithms. Addressing them requires redesigning social machines, focusing on computational infrastructure and interaction norms, such as visibility settings, to mitigate harmful outcomes. Originality/value – The paper’s originality lies in its systematic review of biases in social machines, offering a novel perspective on fairness in these systems. Unlike prior studies focusing solely on algorithmic fairness, this work examines the broader socio-technical interactions within social machines, identifying biases that emerge from user interactions and design choices. By linking these biases to established fairness concepts like demographic parity and representational harm, the paper bridges the gap between algorithmic fairness and social dynamics. © 2025 Emerald Publishing Limited
2.
Souza, J. V.; Amamou, H.; Chen, R.; Salari, E.; Gubelmann, R.; Niklaus, C.; Serpa, T.; Lima, M. M. F.; Pinto, P. T.; Kshirsagar, S.; Davoust, A.; Handschuh, S.; Avila, A. R.
Cross-Lingual Keyword Extraction for Pesticide Terminology in Brazilian Portuguese and English Article de journal
Dans: Journal of the Brazilian Computer Society, vol. 31, no 1, p. 973–990, 2025, ISSN: 01046500 (ISSN).
Résumé | Liens | BibTeX | Étiquettes: Agriculture, BERT embedding, BERT embeddings, Cross-lingual, Embeddings, extraction, Food consumption, Keywords extraction, Labelings, Low resource languages, Multilingual extraction, Pesticides, Technical terms, Terminology, Word alignment
@article{de_souza_cross-lingual_2025,
title = {Cross-Lingual Keyword Extraction for Pesticide Terminology in Brazilian Portuguese and English},
author = {J. V. Souza and H. Amamou and R. Chen and E. Salari and R. Gubelmann and C. Niklaus and T. Serpa and M. M. F. Lima and P. T. Pinto and S. Kshirsagar and A. Davoust and S. Handschuh and A. R. Avila},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105019700300&doi=10.5753%2Fjbcs.2025.5815&partnerID=40&md5=85ee75baf4550666a307310cd04d1c83},
doi = {10.5753/jbcs.2025.5815},
issn = {01046500 (ISSN)},
year = {2025},
date = {2025-01-01},
journal = {Journal of the Brazilian Computer Society},
volume = {31},
number = {1},
pages = {973–990},
abstract = {Agriculture plays a crucial role in Brazil’s economy. As the country intensifies its activities in the sector, the use of pesticides also increases. Hence, the risks associated with pesticide-laden food consumption have become a concern for chemistry researchers. An issue affecting regulatory standardization of pesticides in Brazil is the difficulty in translating pesticide names, particularly from English. For example, the word malathion can be translated from English to Portuguese as malatiom or malatião, resulting in inconsistent labeling. This issue extends to the broader problem of translating highly technical terms between languages, in particular for low-resource languages. In this work, we investigate terminological variation in the chemistry of organophosphorus pesticides. Our goal is to study strategies for domain-specific multilingual keyword extraction. To that end, two corpora were built based on pesticide-related scientific documents in Brazilian Portuguese and English, which led to a total of 84 and 210 texts, respectively, representing the low-and high-resource languages in this study. We then assessed 6 methods for keyword extraction: Simple Maths, TF-IDF, YAKE, TextRank, MultipartiteRank, and KeyBERT. We relied on a multilingual contextual BERT embedding to retrieve corresponding pesticide names in the target language. Finetuning was also explored to improve the multilingual representation further. Moreover, we evaluated the use of large language models (LLMs) combined with the recent retrieval-augmented generation (RAG) framework. As a result, we found that the contextual approach, combined with fine-tuning, provided the best results, contributing to enhancing Pesticide Terminology Extraction in a multilingual scenario. © 2025, Brazilian Computing Society. All rights reserved.},
keywords = {Agriculture, BERT embedding, BERT embeddings, Cross-lingual, Embeddings, extraction, Food consumption, Keywords extraction, Labelings, Low resource languages, Multilingual extraction, Pesticides, Technical terms, Terminology, Word alignment},
pubstate = {published},
tppubtype = {article}
}
Agriculture plays a crucial role in Brazil’s economy. As the country intensifies its activities in the sector, the use of pesticides also increases. Hence, the risks associated with pesticide-laden food consumption have become a concern for chemistry researchers. An issue affecting regulatory standardization of pesticides in Brazil is the difficulty in translating pesticide names, particularly from English. For example, the word malathion can be translated from English to Portuguese as malatiom or malatião, resulting in inconsistent labeling. This issue extends to the broader problem of translating highly technical terms between languages, in particular for low-resource languages. In this work, we investigate terminological variation in the chemistry of organophosphorus pesticides. Our goal is to study strategies for domain-specific multilingual keyword extraction. To that end, two corpora were built based on pesticide-related scientific documents in Brazilian Portuguese and English, which led to a total of 84 and 210 texts, respectively, representing the low-and high-resource languages in this study. We then assessed 6 methods for keyword extraction: Simple Maths, TF-IDF, YAKE, TextRank, MultipartiteRank, and KeyBERT. We relied on a multilingual contextual BERT embedding to retrieve corresponding pesticide names in the target language. Finetuning was also explored to improve the multilingual representation further. Moreover, we evaluated the use of large language models (LLMs) combined with the recent retrieval-augmented generation (RAG) framework. As a result, we found that the contextual approach, combined with fine-tuning, provided the best results, contributing to enhancing Pesticide Terminology Extraction in a multilingual scenario. © 2025, Brazilian Computing Society. All rights reserved.
3.
Ngouanfouo, C.; Davoust, A.
Detecting Machine-Generated Text using Grammatical Features Article d'actes
Dans: Proc. Int. Conf. Tools Artif. Intell. ICTAI, p. 843–848, IEEE Computer Society, 2025, ISBN: 10823409 (ISSN); 979-833154919-0 (ISBN).
Résumé | Liens | BibTeX | Étiquettes: AI Text Detection, CNN, Computational grammars, Detection methods, Language model, Machine-generated texts, Natural language generation, Natural language processing systems, Neural encoding, Neural modelling, Part Of Speech, Part-of Speech, Speech communication, Text detection, Written texts
@inproceedings{ngouanfouo_detecting_2025,
title = {Detecting Machine-Generated Text using Grammatical Features},
author = {C. Ngouanfouo and A. Davoust},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105031903675&doi=10.1109%2FICTAI66417.2025.00123&partnerID=40&md5=5783b8797a3425f9dfa737343ee757d2},
doi = {10.1109/ICTAI66417.2025.00123},
isbn = {10823409 (ISSN); 979-833154919-0 (ISBN)},
year = {2025},
date = {2025-01-01},
booktitle = {Proc. Int. Conf. Tools Artif. Intell. ICTAI},
pages = {843–848},
publisher = {IEEE Computer Society},
abstract = {Large Language Models (LLMs) have advanced natural language generation but pose ethical and practical challenges, making it crucial to detect machine-generated texts. Traditional detection methods rely on complex, hard-to-interpret neural encodings and model-specific features like perplexity. This study explores whether grammatical patterns-specifically sequences of parts of speech (POS), including punctuation and symbols-can distinguish machine-written texts from human ones. Using a CNN classifier on POS sequences, the approach achieves nearly 90 % accuracy on a benchmark dataset. Combining POS-based features with neural embeddings improves performance, and the model shows robustness against adversarial attacks, though it is less effective on short texts. © 2025 IEEE.},
keywords = {AI Text Detection, CNN, Computational grammars, Detection methods, Language model, Machine-generated texts, Natural language generation, Natural language processing systems, Neural encoding, Neural modelling, Part Of Speech, Part-of Speech, Speech communication, Text detection, Written texts},
pubstate = {published},
tppubtype = {inproceedings}
}
Large Language Models (LLMs) have advanced natural language generation but pose ethical and practical challenges, making it crucial to detect machine-generated texts. Traditional detection methods rely on complex, hard-to-interpret neural encodings and model-specific features like perplexity. This study explores whether grammatical patterns-specifically sequences of parts of speech (POS), including punctuation and symbols-can distinguish machine-written texts from human ones. Using a CNN classifier on POS sequences, the approach achieves nearly 90 % accuracy on a benchmark dataset. Combining POS-based features with neural embeddings improves performance, and the model shows robustness against adversarial attacks, though it is less effective on short texts. © 2025 IEEE.
4.
Damadi, M. S.; Davoust, A.
Fairness in Socio-Technical Systems: A Case Study of Wikipedia Article de journal
Dans: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 14199 LNCS, p. 84–100, 2023, ISSN: 03029743, (ISBN: 9783031421402).
Résumé | Liens | BibTeX | Étiquettes: Algorithmics, Bias, Case-studies, Causal relationships, Cultural bias, Fairness, Gender bias, Machine learning, Machine-learning, Parallel processing systems, Sociotechnical systems, Wikipedia
@article{damadi_fairness_2023,
title = {Fairness in Socio-Technical Systems: A Case Study of Wikipedia},
author = {M. S. Damadi and A. Davoust},
editor = {Alvarez C. Marutschke D.M. Takada H.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85172720004&doi=10.1007%2f978-3-031-42141-9_6&partnerID=40&md5=172c8c6ae5b09536efdf983e9be965e7},
doi = {10.1007/978-3-031-42141-9_6},
issn = {03029743},
year = {2023},
date = {2023-01-01},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
volume = {14199 LNCS},
pages = {84–100},
publisher = {Springer Science and Business Media Deutschland GmbH},
abstract = {Wikipedia content is produced by a complex socio-technical systems (STS), and exhibits numerous biases, such as gender and cultural biases. We investigate how these biases relate to the concepts of algorithmic bias and fairness defined in the context of algorithmic systems. We systematically review 75 papers describing different types of bias in Wikipedia, which we classify and relate to established notions of harm and normative expectations of fairness as defined for machine learning-driven algorithmic systems. In addition, by analysing causal relationships between the observed phenomena, we demonstrate the complexity of the socio-technical processes causing harm. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.},
note = {ISBN: 9783031421402},
keywords = {Algorithmics, Bias, Case-studies, Causal relationships, Cultural bias, Fairness, Gender bias, Machine learning, Machine-learning, Parallel processing systems, Sociotechnical systems, Wikipedia},
pubstate = {published},
tppubtype = {article}
}
Wikipedia content is produced by a complex socio-technical systems (STS), and exhibits numerous biases, such as gender and cultural biases. We investigate how these biases relate to the concepts of algorithmic bias and fairness defined in the context of algorithmic systems. We systematically review 75 papers describing different types of bias in Wikipedia, which we classify and relate to established notions of harm and normative expectations of fairness as defined for machine learning-driven algorithmic systems. In addition, by analysing causal relationships between the observed phenomena, we demonstrate the complexity of the socio-technical processes causing harm. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.
5.
Davoust, A.; Rovatsos, M.
Social contracts for non-cooperative games Article d'actes
Dans: AIES 2020 - Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society, p. 43–49, Association for Computing Machinery, Inc, 2020, ISBN: 978-1-4503-7110-0.
Résumé | Liens | BibTeX | Étiquettes: Agent society, Agents, Behavioral research, Ethical aspects, Game theory, Game-theoretic, Moral philosophy, Noncooperative game, Selfish behaviours, Social benefits, Social contract, Social welfare
@inproceedings{davoust_social_2020,
title = {Social contracts for non-cooperative games},
author = {A. Davoust and M. Rovatsos},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85082175399&doi=10.1145%2f3375627.3375829&partnerID=40&md5=972ba2201a1c2450895935dc03ec39b9},
doi = {10.1145/3375627.3375829},
isbn = {978-1-4503-7110-0},
year = {2020},
date = {2020-01-01},
booktitle = {AIES 2020 - Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society},
pages = {43–49},
publisher = {Association for Computing Machinery, Inc},
abstract = {In future agent societies, we might see AI systems engaging in selfish, calculated behavior, furthering their owners' interests instead of socially desirable outcomes. How can we promote morally sound behaviour in such settings, in order to obtain more desirable outcomes? A solution from moral philosophy is the concept of a social contract, a set of rules that people would voluntarily commit to in order to obtain better outcomes than those brought by anarchy. We adapt this concept to a game-theoretic setting, to systematically modify the payoffs of a non-cooperative game, so that agents will rationally pursue socially desirable outcomes. We show that for any game, a suitable social contract can be designed to produce an optimal outcome in terms of social welfare. We then investigate the limitations of applying this approach to alternative moral objectives, and establish that, for any alternative moral objective that is significantly different from social welfare, there are games for which no such social contract will be feasible that produces non-negligible social benefit compared to collective selfish behaviour. © 2020 Copyright held by the owner/author(s).},
keywords = {Agent society, Agents, Behavioral research, Ethical aspects, Game theory, Game-theoretic, Moral philosophy, Noncooperative game, Selfish behaviours, Social benefits, Social contract, Social welfare},
pubstate = {published},
tppubtype = {inproceedings}
}
In future agent societies, we might see AI systems engaging in selfish, calculated behavior, furthering their owners' interests instead of socially desirable outcomes. How can we promote morally sound behaviour in such settings, in order to obtain more desirable outcomes? A solution from moral philosophy is the concept of a social contract, a set of rules that people would voluntarily commit to in order to obtain better outcomes than those brought by anarchy. We adapt this concept to a game-theoretic setting, to systematically modify the payoffs of a non-cooperative game, so that agents will rationally pursue socially desirable outcomes. We show that for any game, a suitable social contract can be designed to produce an optimal outcome in terms of social welfare. We then investigate the limitations of applying this approach to alternative moral objectives, and establish that, for any alternative moral objective that is significantly different from social welfare, there are games for which no such social contract will be feasible that produces non-negligible social benefit compared to collective selfish behaviour. © 2020 Copyright held by the owner/author(s).
6.
Davoust, A.; Gavigan, P.; Ruiz-Martin, C.; Trabes, G.; Esfandiari, B.; Wainer, G.; James, J.
An architecture for integrating BDI agents with a simulation environment Article de journal
Dans: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12058 LNAI, p. 67–84, 2020, ISSN: 03029743, (ISBN: 9783030514167).
Résumé | Liens | BibTeX | Étiquettes: Antennas, Architecture, Autonomous agents, Belief-desire-intentions, Impedance mismatch, Modelling and simulations, Multi agent systems, Open source architecture, Real time simulations, Separation of concerns, Simulated environment, Simulation environment
@article{davoust_architecture_2020,
title = {An architecture for integrating BDI agents with a simulation environment},
author = {A. Davoust and P. Gavigan and C. Ruiz-Martin and G. Trabes and B. Esfandiari and G. Wainer and J. James},
editor = {Lesperance Y. Bordini R.H. Dennis L.A.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85088750329&doi=10.1007%2f978-3-030-51417-4_4&partnerID=40&md5=2f742500bcd9cac1bf054bbc8802e39c},
doi = {10.1007/978-3-030-51417-4_4},
issn = {03029743},
year = {2020},
date = {2020-01-01},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
volume = {12058 LNAI},
pages = {67–84},
publisher = {Springer},
abstract = {We present Simulated Autonomous Vehicle Infrastructure (SAVI), an open source architecture for integrating Belief-Desire-Intention (BDI) agents with a simulation platform. This allows for separation of concerns between the development of complex multi-agent behaviours and simulated environments to test them in. We identify and address the impedance mismatch between modelling and simulation, where time is explicitly modelled and differs from “wall clock” time, and BDI systems, where time is not explicitly managed. Our approach avoids linking the environment’s simulation time step to the agents’ reasoning cycles, relying instead on real time simulation where possible, and ensuring that the reasoning module does not get ahead of the simulation. This contributes to a realistic approximation of a real environment for the simulated BDI agents. This is accomplished by running the simulation cycles and the agent reasoning cycles each in their own threads of execution, and managing a single point of contact between these threads. Finally, we illustrate the use of our architecture with a case study involving the simulation of Unmanned Aerial Vehicles (UAVs) following birds. © Springer Nature Switzerland AG 2020.},
note = {ISBN: 9783030514167},
keywords = {Antennas, Architecture, Autonomous agents, Belief-desire-intentions, Impedance mismatch, Modelling and simulations, Multi agent systems, Open source architecture, Real time simulations, Separation of concerns, Simulated environment, Simulation environment},
pubstate = {published},
tppubtype = {article}
}
We present Simulated Autonomous Vehicle Infrastructure (SAVI), an open source architecture for integrating Belief-Desire-Intention (BDI) agents with a simulation platform. This allows for separation of concerns between the development of complex multi-agent behaviours and simulated environments to test them in. We identify and address the impedance mismatch between modelling and simulation, where time is explicitly modelled and differs from “wall clock” time, and BDI systems, where time is not explicitly managed. Our approach avoids linking the environment’s simulation time step to the agents’ reasoning cycles, relying instead on real time simulation where possible, and ensuring that the reasoning module does not get ahead of the simulation. This contributes to a realistic approximation of a real environment for the simulated BDI agents. This is accomplished by running the simulation cycles and the agent reasoning cycles each in their own threads of execution, and managing a single point of contact between these threads. Finally, we illustrate the use of our architecture with a case study involving the simulation of Unmanned Aerial Vehicles (UAVs) following birds. © Springer Nature Switzerland AG 2020.
7.
Webb, H.; Patel, M.; Rovatsos, M.; Davoust, A.; Ceppi, S.; Koene, A.; Dowthwaite, L.; Portillo, V.; Jirotka, M.; Cano, M.
“It would be pretty immoral to choose a random algorithm”: Opening up algorithmic interpretability and transparency Article de journal
Dans: Journal of Information, Communication and Ethics in Society, vol. 17, no 2, p. 210–228, 2019, ISSN: 1477996X, (Publisher: Emerald Group Holdings Ltd.).
Résumé | Liens | BibTeX | Étiquettes:
@article{webb_it_2019,
title = {“It would be pretty immoral to choose a random algorithm”: Opening up algorithmic interpretability and transparency},
author = {H. Webb and M. Patel and M. Rovatsos and A. Davoust and S. Ceppi and A. Koene and L. Dowthwaite and V. Portillo and M. Jirotka and M. Cano},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85064059515&doi=10.1108%2fJICES-11-2018-0092&partnerID=40&md5=34ce2e453a8c57f7f80b38e6237052aa},
doi = {10.1108/JICES-11-2018-0092},
issn = {1477996X},
year = {2019},
date = {2019-01-01},
journal = {Journal of Information, Communication and Ethics in Society},
volume = {17},
number = {2},
pages = {210–228},
publisher = {Emerald Group Holdings Ltd.},
abstract = {Purpose: The purpose of this paper is to report on empirical work conducted to open up algorithmic interpretability and transparency. In recent years, significant concerns have arisen regarding the increasing pervasiveness of algorithms and the impact of automated decision-making in our lives. Particularly problematic is the lack of transparency surrounding the development of these algorithmic systems and their use. It is often suggested that to make algorithms more fair, they should be made more transparent, but exactly how this can be achieved remains unclear. Design/methodology/approach: An empirical study was conducted to begin unpacking issues around algorithmic interpretability and transparency. The study involved discussion-based experiments centred around a limited resource allocation scenario which required participants to select their most and least preferred algorithms in a particular context. In addition to collecting quantitative data about preferences, qualitative data captured participants’ expressed reasoning behind their selections. Findings: Even when provided with the same information about the scenario, participants made different algorithm preference selections and rationalised their selections differently. The study results revealed diversity in participant responses but consistency in the emphasis they placed on normative concerns and the importance of context when accounting for their selections. The issues raised by participants as important to their selections resonate closely with values that have come to the fore in current debates over algorithm prevalence. Originality/value: This work developed a novel empirical approach that demonstrates the value in pursuing algorithmic interpretability and transparency while also highlighting the complexities surrounding their accomplishment. © 2019, Emerald Publishing Limited.},
note = {Publisher: Emerald Group Holdings Ltd.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Purpose: The purpose of this paper is to report on empirical work conducted to open up algorithmic interpretability and transparency. In recent years, significant concerns have arisen regarding the increasing pervasiveness of algorithms and the impact of automated decision-making in our lives. Particularly problematic is the lack of transparency surrounding the development of these algorithmic systems and their use. It is often suggested that to make algorithms more fair, they should be made more transparent, but exactly how this can be achieved remains unclear. Design/methodology/approach: An empirical study was conducted to begin unpacking issues around algorithmic interpretability and transparency. The study involved discussion-based experiments centred around a limited resource allocation scenario which required participants to select their most and least preferred algorithms in a particular context. In addition to collecting quantitative data about preferences, qualitative data captured participants’ expressed reasoning behind their selections. Findings: Even when provided with the same information about the scenario, participants made different algorithm preference selections and rationalised their selections differently. The study results revealed diversity in participant responses but consistency in the emphasis they placed on normative concerns and the importance of context when accounting for their selections. The issues raised by participants as important to their selections resonate closely with values that have come to the fore in current debates over algorithm prevalence. Originality/value: This work developed a novel empirical approach that demonstrates the value in pursuing algorithmic interpretability and transparency while also highlighting the complexities surrounding their accomplishment. © 2019, Emerald Publishing Limited.
8.
Murray-Rust, D.; Davoust, A.; Papapanagiotou, P.; Manataki, A.; Kleek, M. Van; Shadbolt, N.; Robertson, D.
Towards executable representations of social machines Article de journal
Dans: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10871 LNAI, p. 765–769, 2018, ISSN: 03029743, (ISBN: 9783319913759).
Résumé | Liens | BibTeX | Étiquettes: Calculations, Computation theory, Computational infrastructure, Executable architecture, Graphical formalisms, Inter-action protocols, Network architecture, Participatory design, Sociotechnical systems, Software prototyping, Technological system, Workshop participants
@article{murray-rust_towards_2018,
title = {Towards executable representations of social machines},
author = {D. Murray-Rust and A. Davoust and P. Papapanagiotou and A. Manataki and M. Van Kleek and N. Shadbolt and D. Robertson},
editor = {Moktefi A. Bellucci F. Stapleton G.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85048637678&doi=10.1007%2f978-3-319-91376-6_77&partnerID=40&md5=09d785d483cad1b02b5767278b08836b},
doi = {10.1007/978-3-319-91376-6_77},
issn = {03029743},
year = {2018},
date = {2018-01-01},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
volume = {10871 LNAI},
pages = {765–769},
publisher = {Springer Verlag},
abstract = {Human interaction is increasingly mediated through technological systems, resulting in the emergence of a new class of socio-technical systems, often called Social Machines. However, many systems are designed and managed in a centralised way, limiting the participants’ autonomy and ability to shape the systems they are part of. In this paper we are concerned with creating a graphical formalism that allows novice users to simply draw the patterns of interaction that they desire, and have computational infrastructure assemble around the diagram. Our work includes a series of participatory design workshops, that help to understand the levels and types of abstraction that the general public are comfortable with when designing socio-technical systems. These design studies lead to a novel formalism that allows us to compose rich interaction protocols into functioning, executable architecture. We demonstrate this by translating one of the designs produced by workshop participants into an a running agent institution using the Lightweight Social Calculus (LSC). © Springer International Publishing AG, part of Springer Nature 2018.},
note = {ISBN: 9783319913759},
keywords = {Calculations, Computation theory, Computational infrastructure, Executable architecture, Graphical formalisms, Inter-action protocols, Network architecture, Participatory design, Sociotechnical systems, Software prototyping, Technological system, Workshop participants},
pubstate = {published},
tppubtype = {article}
}
Human interaction is increasingly mediated through technological systems, resulting in the emergence of a new class of socio-technical systems, often called Social Machines. However, many systems are designed and managed in a centralised way, limiting the participants’ autonomy and ability to shape the systems they are part of. In this paper we are concerned with creating a graphical formalism that allows novice users to simply draw the patterns of interaction that they desire, and have computational infrastructure assemble around the diagram. Our work includes a series of participatory design workshops, that help to understand the levels and types of abstraction that the general public are comfortable with when designing socio-technical systems. These design studies lead to a novel formalism that allows us to compose rich interaction protocols into functioning, executable architecture. We demonstrate this by translating one of the designs produced by workshop participants into an a running agent institution using the Lightweight Social Calculus (LSC). © Springer International Publishing AG, part of Springer Nature 2018.
9.
Papapanagiotou, P.; Manataki, A.; Davoust, A.; Kleek, M. Van; Robertson, D.; Murray-Rust, D.; Shadbolt, N.
Social machines for all: Blue sky ideas track Article d'actes
Dans: Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS, p. 1208–1212, International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), 2018, ISSN: 15488403, (ISSN: 15488403).
Résumé | Liens | BibTeX | Étiquettes: Agent based simulation, Analysis, Autonomous agents, Design, Development method, Distributed agents, Distributed computer systems, Easy-to-use systems, Economic and social effects, Electronic institutions, Intelligent agents, Model driven development, Model-driven Engineering, Models, Multi agent systems, Systems analysis
@inproceedings{papapanagiotou_social_2018,
title = {Social machines for all: Blue sky ideas track},
author = {P. Papapanagiotou and A. Manataki and A. Davoust and M. Van Kleek and D. Robertson and D. Murray-Rust and N. Shadbolt},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85054668594&partnerID=40&md5=77eba348dbafa30aef9d016186b46804},
issn = {15488403},
year = {2018},
date = {2018-01-01},
booktitle = {Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS},
volume = {2},
pages = {1208–1212},
publisher = {International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)},
abstract = {In today's interconnected world, people interact to a unprecedented degree through the use of digital platforms and services, forming complex 'social machines'. These are now homes to autonomous agents as well as people, providing an open space where human and computational intelligence can mingle-a new frontier for distributed agent systems. However, participants typically have limited autonomy to define and shape the machines they are part of. In this paper, we envision a future where individuals are able to develop their own Social Machines, enabling them to interact in a trustworthy, decentralized way. To make this possible, development methods and tools must see their barriers-to-entry dramatically lowered. People should be able to specify the agent roles and inte-raction patterns in an intuitive, visual way, analyse and test their designs and deploy them as easy to use systems. We argue that this is a challenging but realistic goal, which should be tackled by navigating the trade-off between the accessibility of the design methods -primarily the modelling formalisms- And their expressive power. We support our arguments by drawing ideas from different research areas including electronic institutions, agent-based simulation, process modelling, formal verification, and model-driven engineering. © 2018 International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.},
note = {ISSN: 15488403},
keywords = {Agent based simulation, Analysis, Autonomous agents, Design, Development method, Distributed agents, Distributed computer systems, Easy-to-use systems, Economic and social effects, Electronic institutions, Intelligent agents, Model driven development, Model-driven Engineering, Models, Multi agent systems, Systems analysis},
pubstate = {published},
tppubtype = {inproceedings}
}
In today's interconnected world, people interact to a unprecedented degree through the use of digital platforms and services, forming complex 'social machines'. These are now homes to autonomous agents as well as people, providing an open space where human and computational intelligence can mingle-a new frontier for distributed agent systems. However, participants typically have limited autonomy to define and shape the machines they are part of. In this paper, we envision a future where individuals are able to develop their own Social Machines, enabling them to interact in a trustworthy, decentralized way. To make this possible, development methods and tools must see their barriers-to-entry dramatically lowered. People should be able to specify the agent roles and inte-raction patterns in an intuitive, visual way, analyse and test their designs and deploy them as easy to use systems. We argue that this is a challenging but realistic goal, which should be tackled by navigating the trade-off between the accessibility of the design methods -primarily the modelling formalisms- And their expressive power. We support our arguments by drawing ideas from different research areas including electronic institutions, agent-based simulation, process modelling, formal verification, and model-driven engineering. © 2018 International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.
10.
Davoust, A.; Gagnon, F.; Esfandiari, B.; Kunz, T.; Cormier, A.
Towards Securing Peer-to-Peer SIP in the MANET Context: Existing Work and Perspectives Article d'actes
Dans: Y., Georgalas N. Min G. Wu (Ed.): Proceedings - 2017 IEEE International Conference on Internet of Things, IEEE Green Computing and Communications, IEEE Cyber, Physical and Social Computing, IEEE Smart Data, iThings-GreenCom-CPSCom-SmartData 2017, p. 223–229, Institute of Electrical and Electronics Engineers Inc., 2017, ISBN: 978-1-5386-3065-5.
Résumé | Liens | BibTeX | Étiquettes: Ad-hoc networks, Building blockes, Instant messaging, Internet protocols, Mobile ad-hoc networks, Mobile telecommunication systems, Network contexts, Network security, P2P, Peer to peer networks, Peer-to-peer session initiation protocols, Radio links, Security, Session Initiation Protocols, Social applications, Vehicular ad hoc networks
@inproceedings{davoust_towards_2017,
title = {Towards Securing Peer-to-Peer SIP in the MANET Context: Existing Work and Perspectives},
author = {A. Davoust and F. Gagnon and B. Esfandiari and T. Kunz and A. Cormier},
editor = {Georgalas N. Min G. Wu Y.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85047394150&doi=10.1109%2fiThings-GreenCom-CPSCom-SmartData.2017.38&partnerID=40&md5=738bee95270122e76104e7afc52fe946},
doi = {10.1109/iThings-GreenCom-CPSCom-SmartData.2017.38},
isbn = {978-1-5386-3065-5},
year = {2017},
date = {2017-01-01},
booktitle = {Proceedings - 2017 IEEE International Conference on Internet of Things, IEEE Green Computing and Communications, IEEE Cyber, Physical and Social Computing, IEEE Smart Data, iThings-GreenCom-CPSCom-SmartData 2017},
volume = {2018-January},
pages = {223–229},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {The Session Initiation Protocol (SIP) is a key building block of many social applications, including VoIP communication and instant messaging. In its original architecture, SIP heavily relies on servers such as proxies and registrars. Mobile Ad hoc NETworks (MANETs) are networks comprised of mobile devices that communicate over wireless links, such as tactical radio networks or vehicular networks. In such networks, no fixed infrastructure exists and server-based solutions need to be redesigned to work in a peer-to-peer fashion. We survey existing proposals for the implementation of SIP over such MANETs and analyze their security issues. We then discuss potential solutions and their suitability in the MANET context. © 2017 IEEE.},
keywords = {Ad-hoc networks, Building blockes, Instant messaging, Internet protocols, Mobile ad-hoc networks, Mobile telecommunication systems, Network contexts, Network security, P2P, Peer to peer networks, Peer-to-peer session initiation protocols, Radio links, Security, Session Initiation Protocols, Social applications, Vehicular ad hoc networks},
pubstate = {published},
tppubtype = {inproceedings}
}
The Session Initiation Protocol (SIP) is a key building block of many social applications, including VoIP communication and instant messaging. In its original architecture, SIP heavily relies on servers such as proxies and registrars. Mobile Ad hoc NETworks (MANETs) are networks comprised of mobile devices that communicate over wireless links, such as tactical radio networks or vehicular networks. In such networks, no fixed infrastructure exists and server-based solutions need to be redesigned to work in a peer-to-peer fashion. We survey existing proposals for the implementation of SIP over such MANETs and analyze their security issues. We then discuss potential solutions and their suitability in the MANET context. © 2017 IEEE.