Transparent, explainable, and accountable AI for robotics

To create fair and accountable AI and robotics, we need precise regulation and better methods to certify, explain, and audit inscrutable systems

Proposing a Roadmap for Designing Non-Discriminatory ML Services: Preliminary Results from a Design Science Research Project

Artificial Intelligence (AI) and Machine Learning (ML) algorithms are being developed with ever higher accuracy. However, the use of ML also has its dark side. In the recent past, examples have repeatedly emerged of ML systems learning discriminatory and even racist or sexist patterns and acting accordingly. As ML systems become an integral part of both private and economic spheres of life, academia and practice must address the question of how non-discriminatory ML algorithms can be developed to benefit everyone. This is where our research in progress paper contributes. Using a real-world smart living case study, we investigated discrimination in terms of ethnicity and gender within state-of-the-art pre-trained ML models for face recognition and quantified it using an F1 metric. Building on these empirical findings as well as on the state of the scientific literature, we propose a roadmap for further research on the development of non-discriminatory ML services

Security and Privacy in Resource-constrained Devices

Recent adversarial attacks have been shown IoT devices weaknesses due to their limited computing power. Given also their ubiquitous presence, lower costs and limitations in keeping security measures up-todate, resource-constrained devices represent a growing risk for the security of IT infrastructure. The scope of the research is to investigate the weaknesses of resource-constrained IoT devices. The methodology for the investigation is the legal analysis of existing legal frameworks regulating IoT cybersecurity and data security; afterwards it will be carried out a critical evaluation of the existing best practices. This critical analysis should face the twofold challenge of increasing transparency and trust in resource-constrained systems. Users and companies are two faces of the same coin: accountability of data collectors and user awareness are crucial in the security and data protection debate. Thus, a comprehensive overview of the relevant legal frameworks and guidelines would increase the understanding of risks of the users, whilst data controllers (especially of small and medium enterprises) may have an instrument to implement properly security measures

GOVERNANCE OF ARTIFICIAL INTELLIGENCE IN KSA (NEOM AS A MODEL)

This paper deals with the issue of the governance of artificial intelligence from two aspects; the first one is the artificial intelligence as an essential component of the life of today’s world, whether at the level of individuals or societies; its history, effects, benefits, fields and fears arising from it, and consequently the importance of the principal of the governance of artificial intelligence in maximizing advantages and preventing disadvantages. The second aspect deals with the efforts of the Kingdom of Saudi Arabia in the field of the governance of artificial intelligence as one of the leading countries in Middle East in implementing and investing of artificial intelligence applications for the sake of Saudi society and individuals. As well as to provide opportunities for companies and institutions from entire world to collaborate inside the kingdom and benefit the world. The Kingdom of Saudi Arabia’s efforts are expressed through talking about the Saudi’s giant project NEOM, through the discussion of the founding council’s vision and message, as well as NEOM’s features and sectors

Security Aspects of Social Robots in Public Spaces: A Systematic Mapping Study

Background: As social robots increasingly integrate into public spaces, comprehending their security implications becomes paramount. This study is conducted amidst the growing use of social robots in public spaces (SRPS), emphasising the necessity for tailored security standards for these unique robotic systems. Methods: In this systematic mapping study (SMS), we meticulously review and analyse existing literature from the Web of Science database, following guidelines by Petersen et al. We employ a structured approach to categorise and synthesise literature on SRPS security aspects, including physical safety, data privacy, cybersecurity, and legal/ethical considerations. Results: Our analysis reveals a significant gap in existing safety standards, originally designed for industrial robots, that need to be revised for SRPS. We propose a thematic framework consolidating essential security guidelines for SRPS, substantiated by evidence from a considerable percentage of the primary studies analysed. Conclusions: The study underscores the urgent need for comprehensive, bespoke security standards and frameworks for SRPS. These standards ensure that SRPS operate securely and ethically, respecting individual rights and public safety, while fostering seamless integration into diverse human-centric environments. This work is poised to enhance public trust and acceptance of these robots, offering significant value to developers, policymakers, and the general public.publishedVersio