Upgrading the protection of children from manipulative and addictive
strategies in online games: Legal and technical solutions beyond privacy
regulation
- URL: http://arxiv.org/abs/2207.09928v2
- Date: Thu, 1 Sep 2022 10:26:59 GMT
- Title: Upgrading the protection of children from manipulative and addictive
strategies in online games: Legal and technical solutions beyond privacy
regulation
- Authors: Tommaso Crepax, Jan Tobias Muehlberg
- Abstract summary: We discuss manipulative and exploitative strategies in the context of online games for children.
We propose an upgrade for the regulatory approach to address these risks from the perspective of freedom of thought.
- Score: 0.0
- License: http://creativecommons.org/licenses/by-sa/4.0/
- Abstract: Despite the increasing awareness from academia, civil society and media to
the issue of child manipulation online, the current EU regulatory system fails
at providing sufficient levels of protection. Given the universality of the
issue, there is a need to combine and further these scattered efforts into a
unitary, multidisciplinary theory of digital manipulation that identifies
causes and effects, systematizes the technical and legal knowledge on
manipulative and addictive tactics, and to find effective regulatory mechanisms
to fill the legislative gaps. In this paper we discuss manipulative and
exploitative strategies in the context of online games for children, suggest a
number of possible reasons for the failure of the applicable regulatory system,
propose an "upgrade" for the regulatory approach to address these risks from
the perspective of freedom of thought, and present and discuss technological
approaches that allow for the development of games that verifiably protect the
privacy and freedoms of players.
Related papers
- Towards Resilience and Autonomy-based Approaches for Adolescents Online Safety [7.446834742371107]
We discuss the paradigm shift that has emerged in the literature to move toward resilient-based and privacy-preserving solutions to promote adolescents' online safety.
We highlight the limitations of restrictive mediation strategies, which often induce a trade-off between teens' privacy and online safety.
We present an overview of empirical studies that conceptualized and examined resilience-based approaches to promoting the digital well-being of teens.
arXiv Detail & Related papers (2025-04-22T02:23:48Z) - Media and responsible AI governance: a game-theoretic and LLM analysis [61.132523071109354]
This paper investigates the interplay between AI developers, regulators, users, and the media in fostering trustworthy AI systems.
Using evolutionary game theory and large language models (LLMs), we model the strategic interactions among these actors under different regulatory regimes.
arXiv Detail & Related papers (2025-03-12T21:39:38Z) - Data Sharing, Privacy and Security Considerations in the Energy Sector: A Review from Technical Landscape to Regulatory Specifications [49.567747749614924]
Decarbonization, decentralization and digitalization are the three key elements driving the twin energy transition.
This paper conducts a comprehensive review of the data-related issues for the energy system by integrating both technical and regulatory dimensions.
We classify the issues into three categories: (i) data-sharing among energy end users and stakeholders (ii) privacy of end users, and (iii) cyber security.
arXiv Detail & Related papers (2025-03-05T14:23:56Z) - Advancing Obfuscation Strategies to Counter China's Great Firewall: A Technical and Policy Perspective [4.606106768645647]
China's Great Firewall (GFW) exemplifies one of the most extensive and technologically sophisticated internet censorship frameworks worldwide.
This paper critically examines the GFW's principal detection techniques, including Deep Packet Inspection (DPI), domain name tampering, and traffic fingerprinting.
In parallel, we evaluate emerging countermeasures that leverage obfuscation, encryption, and routing innovations to circumvent these restrictions.
arXiv Detail & Related papers (2025-03-03T19:51:50Z) - The New Anticipatory Governance Culture for Innovation: Regulatory Foresight, Regulatory Experimentation and Regulatory Learning [0.0]
This article advances scholarship on innovation policy and the regulation of technological innovation in the European Union.
It systematically excavates a variety of tools and elements that are being put into use in inventive ways.
It argues that these need to be more cohesively and systemically integrated into the regulatory toolbox.
arXiv Detail & Related papers (2025-01-10T12:26:38Z) - Open Problems in Technical AI Governance [93.89102632003996]
Technical AI governance refers to technical analysis and tools for supporting the effective governance of AI.
This paper is intended as a resource for technical researchers or research funders looking to contribute to AI governance.
arXiv Detail & Related papers (2024-07-20T21:13:56Z) - Demarked: A Strategy for Enhanced Abusive Speech Moderation through Counterspeech, Detoxification, and Message Management [71.99446449877038]
We propose a more comprehensive approach called Demarcation scoring abusive speech based on four aspect -- (i) severity scale; (ii) presence of a target; (iii) context scale; (iv) legal scale.
Our work aims to inform future strategies for effectively addressing abusive speech online.
arXiv Detail & Related papers (2024-06-27T21:45:33Z) - Securing the Future of GenAI: Policy and Technology [50.586585729683776]
Governments globally are grappling with the challenge of regulating GenAI, balancing innovation against safety.
A workshop co-organized by Google, University of Wisconsin, Madison, and Stanford University aimed to bridge this gap between GenAI policy and technology.
This paper summarizes the discussions during the workshop which addressed questions, such as: How regulation can be designed without hindering technological progress?
arXiv Detail & Related papers (2024-05-21T20:30:01Z) - Regulating Chatbot Output via Inter-Informational Competition [8.168523242105763]
This Article develops a yardstick for reevaluating both AI-related content risks and corresponding regulatory proposals.
It argues that sufficient competition among information outlets in the information marketplace can sufficiently mitigate and even resolve most content risks posed by generative AI technologies.
arXiv Detail & Related papers (2024-03-17T00:11:15Z) - SoK: Technical Implementation and Human Impact of Internet Privacy
Regulations [2.797211052758564]
We analyze a set of Internet privacy and data protection regulations drawn from around the world.
We develop a taxonomy of rights granted and obligations imposed by these laws.
We then leverage this taxonomy to systematize 270 technical research papers.
arXiv Detail & Related papers (2023-12-24T01:48:07Z) - The risks of risk-based AI regulation: taking liability seriously [46.90451304069951]
The development and regulation of AI seems to have reached a critical stage.
Some experts are calling for a moratorium on the training of AI systems more powerful than GPT-4.
This paper analyses the most advanced legal proposal, the European Union's AI Act.
arXiv Detail & Related papers (2023-11-03T12:51:37Z) - Regulation and NLP (RegNLP): Taming Large Language Models [51.41095330188972]
We argue how NLP research can benefit from proximity to regulatory studies and adjacent fields.
We advocate for the development of a new multidisciplinary research space on regulation and NLP.
arXiv Detail & Related papers (2023-10-09T09:22:40Z) - Dual Governance: The intersection of centralized regulation and
crowdsourced safety mechanisms for Generative AI [1.2691047660244335]
Generative Artificial Intelligence (AI) has seen mainstream adoption lately, especially in the form of consumer-facing, open-ended, text and image generating models.
The potential for generative AI to displace human creativity and livelihoods has also been under intense scrutiny.
Existing and proposed centralized regulations by governments to rein in AI face criticisms such as not having sufficient clarity or uniformity.
Decentralized protections via crowdsourced safety tools and mechanisms are a potential alternative.
arXiv Detail & Related papers (2023-08-02T23:25:21Z) - Distributed Machine Learning and the Semblance of Trust [66.1227776348216]
Federated Learning (FL) allows the data owner to maintain data governance and perform model training locally without having to share their data.
FL and related techniques are often described as privacy-preserving.
We explain why this term is not appropriate and outline the risks associated with over-reliance on protocols that were not designed with formal definitions of privacy in mind.
arXiv Detail & Related papers (2021-12-21T08:44:05Z) - Beyond Ads: Sequential Decision-Making Algorithms in Law and Public
Policy [2.762239258559568]
We explore the promises and challenges of employing sequential decision-making algorithms in law and public policy.
Our main thesis is that law and public policy pose distinct methodological challenges that the machine learning community has not yet addressed.
We discuss a wide range of potential applications of sequential decision-making algorithms in regulation and governance.
arXiv Detail & Related papers (2021-12-13T17:45:21Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.