Value is as value does?

https://www.ft.com/content/f964fe30-cb6e-427d-b7a7-9adf2ab8a457?shareType=nongift

The MicroStrategy copycats: companies turn to bitcoin to boost share price

Firms buy ‘kryptonite for short sellers’ as they try to emulate US software group’s success

Software business-turned-bitcoin hoarder MicroStrategy is inspiring a host of companies to buy the cryptocurrency and hold it in their corporate treasuries, in a manoeuvre aimed at boosting their flagging share prices.

Pharmaceutical companies and advertisers are among 78 listed companies around the world that are following the US group’s example in buying the coins to hold in place of cash, according to data from crypto security company Coinkite.

MicroStrategy’s founder Michael Saylor has made bitcoin his company’s primary treasury reserve with an aggressive buying spree since 2020. Saylor believes bitcoin’s value will keep rising, saying: “We are going to Mars.”

Having strapped its share price to the fortunes of bitcoin, MicroStrategy is now the world’s largest corporate holder.

New thinking?

https://www.yalelawjournal.org/pdf/DubalYLJForumEssay_hrhm14dd.pdf

Data Laws at Work

In recognition of the material, physical, and psychological harms arising from the growing use of automated monitoring and decision-making systems for labor control, jurisdictions around the world are considering new digital-rights protections for workers. Unsurprisingly, legislatures frequently turn to the European Union (EU) for inspiration. The EU, through the passage of the General Data Protection Regulation in 2016, the Artificial Intelligence Act in 2024, and the Platform Work Directive in 2024, has positioned itself as the leader in digital rights, and, in particular, in providing affirmative digital rights for workers whose labor is mediated by “a platform.” However, little is known about the efficacy of these laws.

This Essay begins to fill this knowledge gap. Through close analyses of the laws and successful strategic litigation by platform workers under these laws, I argue that the current EU framework contains two significant shortcomings. First, the laws primarily position workers as liberal, autonomous subjects, and in doing so, they make a category error: workers, unlike consumers, are subordinated by law and doctrine to the firms for which they labor. As a result, the liberal rights that these laws privilege—such as transparency and consent—are insufficient to mitigate the material harms produced through automated labor management. Second, this Essay argues that by leaning primarily on transparency principles to detect, prevent, and stop violations of labor and employment law, EU data laws do not account for the ways in which workplace algorithmic management systems often create new harms that existing laws of work do not address. These harms, which fundamentally disrupt norms about worker pay, evaluation, and termination, arise from the relational logic of data-processing systems—that is, the way that these systems evaluate workers by dynamically comparing them to others, rather than by evaluating them objectively based on fulfillment of ascribed duties. Based on these analyses, I propose that future data laws should be modeled on older approaches to workplace regulation: rather than merely seeking to elucidate or assess problematic data processes, they should aim to restrict these processes. The normative north star of these laws should be proscribing the digital practices that cause the harms, rather than merely shining a light on their existence.

Can we do it without an AI assistant?

https://academic.oup.com/policyandsociety/advance-article/doi/10.1093/polsoc/puaf001/7997395

Governance of Generative AI

The rapid and widespread diffusion of generative artificial intelligence (AI) has unlocked new capabilities and changed how content and services are created, shared, and consumed. This special issue builds on the 2021 Policy and Society special issue on the governance of AI by focusing on the legal, organizational, political, regulatory, and social challenges of governing generative AI. This introductory article lays the foundation for understanding generative AI and underscores its key risks, including hallucination, jailbreaking, data training and validation issues, sensitive information leakage, opacity, control challenges, and design and implementation risks. It then examines the governance challenges of generative AI, such as data governance, intellectual property concerns, bias amplification, privacy violations, misinformation, fraud, societal impacts, power imbalances, limited public engagement, public sector challenges, and the need for international cooperation. The article then highlights a comprehensive framework to govern generative AI, emphasizing the need for adaptive, participatory, and proactive approaches. The articles in this special issue stress the urgency of developing innovative and inclusive approaches to ensure that generative AI development is aligned with societal values. They explore the need for adaptation of data governance and intellectual property laws, propose a complexity-based approach for responsible governance, analyze how the dominance of Big Tech is exacerbated by generative AI developments and how this affects policy processes, highlight the shortcomings of technocratic governance and the need for broader stakeholder participation, propose new regulatory frameworks informed by AI safety research and learning from other industries, and highlight the societal impacts of generative AI.

To contrast AI wrongs? I think, therefore I have rights?

https://link.springer.com/article/10.1007/s00146-025-02184-2

Human rights for robots? The moral foundations and epistemic challenges

As we step into an era in which artificial intelligence systems are predicted to surpass human capabilities, a number of profound ethical questions have emerged. One such question, which has gained some traction in recent scholarship, concerns the ethics of human treatment of robots and the thought-provoking possibility of robot rights. The present article explores this very aspect, with a particular focus on the notion of human rights for robots. It argues that if we accept the widely held view that moral status and rights (including human rights) are grounded in certain cognitive capacities, then it follows that intelligent machines could, in principle, acquire these entitlements once they come to possess the requisite properties. In support of this perspective, the article outlines the moral foundations of human rights and examines several main objections, arguing that they do not successfully negate the prospect of considering robots as potential holders of human rights. Subsequently, it turns to the key epistemic challenges associated with moral status and rights for robots, outlining the main difficulties in discerning the presence of mental states in artificial entities and offering some practical considerations for approaching these challenges. The article concludes by emphasizing the importance of establishing a suitable framework for moral decision-making under uncertainty in the context of human treatment of artificial entities, given the gravity of the epistemic problems surrounding the concepts of artificial consciousness, moral status, and rights.