From Pluralistic Normative Principles to Autonomous-Agent Rules

Townsend, Beverley; Paterson, Colin; Arvind, TT; Nemirovsky, Gabriel; Călinescu, Radu; Cavalcanti, Ana; Habli, Ibrahim; Thomas, Alan

doi:10.1007/s11023-022-09614-w

Cited by 22 publications

(26 citation statements)

References 67 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A critical part of these conversations is not only to establish the nature and scope of the ethical or rights-based principles at stake (that is, what an ethical principle means for the individual person within a context), but also how an ethical principle can be framed, find relevance, and be embedded within the TAS so that the principle can be effectively and appropriately realised (Townsend et al, 2022;Weng & Hirata, 2018).…”

Section: Key Ethical Debates and Tasmentioning

confidence: 99%

“…Any notion of a TAS cannot be separated from important ethical and normative considerations (Townsend et al, 2022). While some work has been done in this regard, reasons of equity, justice, inclusivity, and diversity dictate that much more attention should be placed on the well-being, contribution, and perspectives of disabled young people who are well-positioned to act as critical stakeholders and active participants in establishing, addressing, and resolving key ethical issues.…”

Section: Key Ethical Debates and Tasmentioning

confidence: 99%

“…Our aim for this critical literature review is as follows. In introducing trustworthy autonomous systems and the contemporary debates around them, we sit with these key questions and themes of what it means to be trustworthy, reliable and safe whilst also in alignment with human values, dignity and ethics (Townsend et al, 2022). We frame these considerations in dialogue with critical disability studies.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Trustworthy Autonomous Systems and Disabled Young People: A Critical Literature Review

White¹,

Picardi²,

Paterson³

et al. 2023

Preprint

View full text Add to dashboard Cite

Autonomous robotic and AI assistive systems are becoming increasingly prevalent in public and private spheres—often heralded as having the potential to revolutionise the everyday lives of disabled people. The reality could not be more different: disabled young people are routinely excluded from such spheres and, significantly, from the recent efforts to ensure that autonomous systems are trustworthy. Our critical literature review explores how trustworthy autonomous systems (TAS) can be framed within a critical disability studies perspective. We introduce the field of TAS and explore the interdisciplinary field of critical disability studies. This brings us to a key question: how is disability conceptualised, methodologically explored and represented in the TAS literature? We address this question by considering the ways in which disability and TAS have hitherto connected in the literature. We conclude with suggestions for future research and innovation that place disabled young people at the core of research and innovation in TAS.

show abstract

Section: Key Ethical Debates and Tasmentioning

confidence: 99%

Section: Key Ethical Debates and Tasmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Trustworthy Autonomous Systems and Disabled Young People: A Critical Literature Review

White¹,

Picardi²,

Paterson³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…AI and autonomous robots are being adopted in applications from health and social care, transportation, infrastructure maintenance. In these applications, the autonomous agents are often required to perform normative tasks that raise social, legal, ethical, empathetic, and cultural (SLEEC) concerns [2]. There is widespread agreement that these concerns must be considered throughout the development of the agents [3,4], and numerous guidelines propose high-level principles that reflect them [5,6,7,8].…”

Section: Introductionmentioning

confidence: 99%

Specification and Validation of Normative Rules for Autonomous Agents

Yaman

Burholt

Jones

et al. 2023

Lecture Notes in Computer Science

Self Cite

View full text Add to dashboard Cite

A growing range of applications use autonomous agents such as AI and robotic systems to perform tasks deemed dangerous, tedious or costly for humans. To truly succeed with these tasks, the autonomous agents must perform them without violating the social, legal, ethical, empathetic, and cultural (SLEEC) norms of their users and operators. We introduce SLEECVAL, a tool for specification and validation of rules that reflect these SLEEC norms. Our tool supports the specification of SLEEC rules in a DSL [1] we co-defined with the help of ethicists, lawyers and stakeholders from health and social care, and uses the CSP refinement checker FDR4 to identify redundant and conflicting rules in a SLEEC specification. We illustrate the use of SLEECVAL for two case studies: an assistive dressing robot, and a firefighting drone.

show abstract

“…In that case, this text needs to at least comply with the universal declaration of human rights and, if possible, have values for the culture in which it is used. Sensor data used in autonomous vehicles should be tested with the same meticulousness within the framework of cultural and universal values (Hertweck et al, 2021; Townsend et al, 2022). This important issue about passing a number through a standardized testing machine must be considered, and methodologies and software tools must be developed to validate cultural and normative concerns.…”

Section: Introductionmentioning

confidence: 99%

Bias in human data: A feedback from social sciences

Takan

TAKAN

Yaman

et al. 2023

WIREs Data Min & Knowl

View full text Add to dashboard Cite

The fairness of human-related software has become critical with its widespread use in our daily lives, where life-changing decisions are made. However, with the use of these systems, many erroneous results emerged. Technologies have started to be developed to tackle unexpected results. As for the solution to the issue, companies generally focus on algorithm-oriented errors. The utilized solutions usually only work in some algorithms. Because the cause of the problem is not just the algorithm; it is also the data itself. For instance, deep learning cannot establish the cause-effect relationship quickly. In addition, the boundaries between statistical or heuristic algorithms are unclear. The algorithm's fairness may vary depending on the data related to context. From this point of view, our article focuses on how the data should be, which is not a matter of statistics. In this direction, the picture in question has been revealed through a scenario specific to "vulnerable and disadvantaged" groups, which is one of the most fundamental problems today. With the joint contribution of computer science and social sciences, it aims to predict the possible social dangers that may arise from artificial intelligence algorithms using the clues obtained in this study. To highlight the potential social and mass problems caused by data, Gerbner's "cultivation theory" is reinterpreted. To this end, we conduct an experimental evaluation on popular algorithms and their data sets, such as Word2Vec, GloVe, and ELMO. The article stresses the importance of a holistic approach combining the algorithm, data, and an interdisciplinary assessment.

show abstract

From Pluralistic Normative Principles to Autonomous-Agent Rules

Cited by 22 publications

References 67 publications

Trustworthy Autonomous Systems and Disabled Young People: A Critical Literature Review

Trustworthy Autonomous Systems and Disabled Young People: A Critical Literature Review

Specification and Validation of Normative Rules for Autonomous Agents

Bias in human data: A feedback from social sciences

Contact Info

Product

Resources

About