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Soheil Human

Publications and source records attributed to Soheil Human.

7 recordsLinked to original sources

From Digital Accountability to Accountable Digitality Through Needs-Aware Information Systems: The Case of Auditable Child-Welfare Judgments

Digital accountability research asks how digital systems can, among other aims, be made transparent, explainable, auditable, contestable, and supportive of ongoing learning and improvement. This paper reverses the question: how can digital transformation make established human institutions more accountable? It theorizes this reversal as accountable digitality and specifies needs-aware information systems as the mediating mechanism. The hard and paradigmatic case is child-welfare judgment, where best-interest procedures must protect children, preserve confidentiality, and respect judicial independence while enabling aggregate learning about needs, reasons, exceptions, and disparities. The case is used diagnostically and illustratively to derive and examine the design logic, not as empirical evidence or validation. Conceptual design-oriented analysis decomposes and recombines digital and legal accountability under child-rights constraints, deriving a canonical theory-to-design chain, contingent mechanisms, implications, and safeguards. It advances IS responsibility and ethics research by showing how privacy-preserving, co-created, needs-aware information systems can support institutional self-knowledge and auditable justice.

cs.CY

Rights by Architecture: A Human-Compatible Sociotechnical Layer for Digital Protection Across Regulatory Regimes

Digital rights increasingly exist in law but remain difficult to exercise through the information systems that mediate them. Using disciplined conceptual synthesis and problematization, this critical-conceptual IS paper explains the gap through the interaction of legal heterogeneity, conflicting organizational and commercial incentives, fragmented architectures, and asymmetrical control over rights-relevant acts. It then theorizes a human-compatible rights layer: a governed sociotechnical capability for standardized, machine-readable, bidirectional, and jurisdictionally plural communication of requests, consent, refusal, withdrawal, objection, records, and support. Comparing California-style opt-out signals, the EU's mixed lawful-basis regime, and P3P, DNT, GPC, and ADPC, the paper derives seven normative requirements, develops rights by architecture as a bounded emancipatory policy argument, and treats a proposed GDPR provision on automated and machine-readable privacy management as a policy case for moving from banner-based compliance toward rights-supporting digital infrastructure.

cs.CY

SoK: On the Offensive Potential of AI

Our society increasingly benefits from Artificial Intelligence (AI). Unfortunately, more and more evidence shows that AI is also used for offensive purposes. Prior works have revealed various examples of use cases in which the deployment of AI can lead to violation of security and privacy objectives. No extant work, however, has been able to draw a holistic picture of the offensive potential of AI. In this SoK paper we seek to lay the ground for a systematic analysis of the heterogeneous capabilities of offensive AI. In particular we (i) account for AI risks to both humans and systems while (ii) consolidating and distilling knowledge from academic literature, expert opinions, industrial venues, as well as laypeople -- all of which being valuable sources of information on offensive AI. To enable alignment of such diverse sources of knowledge, we devise a common set of criteria reflecting essential technological factors related to offensive AI. With the help of such criteria, we systematically analyze: 95 research papers; 38 InfoSec briefings (from, e.g., BlackHat); the responses of a user study (N=549) entailing individuals with diverse backgrounds and expertise; and the opinion of 12 experts. Our contributions not only reveal concerning ways (some of which overlooked by prior work) in which AI can be offensively used today, but also represent a foothold to address this threat in the years to come.

cs.CR

Advanced Data Protection Control (ADPC): An Interdisciplinary Overview

The Advanced Data Protection Control (ADPC) is a technical specification - and a set of sociotechnical mechanisms surrounding it - that can change the current practice of Internet-based personal data protection and consenting by providing novel and standardized means for the communication of privacy and consenting data, meta-data, information, requests, preferences, and decisions. The ADPC supports humans in practicing their rights to privacy and agency by giving them more human-centric control over the processing of their personal data and consent. It helps the data controllers to improve their users' experiences and provides them with easy-to-adopt means to comply with the relevant legal and ethical requirements and expectations.

cs.NI

Your Consent Is Worth 75 Euros A Year -- Measurement and Lawfulness of Cookie Paywalls

Most websites offer their content for free, though this gratuity often comes with a counterpart: personal data is collected to finance these websites by resorting, mostly, to tracking and thus targeted advertising. Cookie walls and paywalls, used to retrieve consent, recently generated interest from EU DPAs and seemed to have grown in popularity. However, they have been overlooked by scholars. We present in this paper 1) the results of an exploratory study conducted on 2800 Central European websites to measure the presence and practices of cookie paywalls, and 2) a framing of their lawfulness amidst the variety of legal decisions and guidelines.

cs.CY

Needs and Artificial Intelligence

Throughout their history, homo sapiens have used technologies to better satisfy their needs. The relation between needs and technology is so fundamental that the US National Research Council defined the distinguishing characteristic of technology as its goal "to make modifications in the world to meet human needs". Artificial intelligence (AI) is one of the most promising emerging technologies of our time. Similar to other technologies, AI is expected "to meet [human] needs". In this article, we reflect on the relationship between needs and AI, and call for the realisation of needs-aware AI systems. We argue that re-thinking needs for, through, and by AI can be a very useful means towards the development of realistic approaches for Sustainable, Human-centric, Accountable, Lawful, and Ethical (HALE) AI systems. We discuss some of the most critical gaps, barriers, enablers, and drivers of co-creating future AI-based socio-technical systems in which [human] needs are well considered and met. Finally, we provide an overview of potential threats and HALE considerations that should be carefully taken into account, and call for joint, immediate, and interdisciplinary efforts and collaborations.

cs.CY

Needs-aware Artificial Intelligence: AI that 'serves [human] needs'

By defining the current limits (and thereby the frontiers), many boundaries are shaping, and will continue to shape, the future of Artificial Intelligence (AI). We push on these boundaries in order to make further progress into what were yesterday's frontiers. They are both pliable and resilient - always creating new boundaries of what AI can (or should) achieve. Among these are technical boundaries (such as processing capacity), psychological boundaries (such as human trust in AI systems), ethical boundaries (such as with AI weapons), and conceptual boundaries (such as the AI people can imagine). It is within this final category while it can play a fundamental role in all other boundaries} that we find the construct of needs and the limitations that our current concept of need places on the future AI.

cs.AI