A critical review of the Online Safety Bill.

The UK Parliament has tabled the Online Safety Bill to make the internet safer for users by requiring providers to regulate legal but harmful content on their platform. This paper critically assesses the draft legislation, surveying its rationale; its scope in terms of lawful and unlawful harms it intends to regulate; and the mechanisms through which it will be enforced. We argue that it requires further refinement if it is to protect free speech and innovation in the digital sphere. We propose four conclusions: further evidence is required to substantiate the necessity and proportionality of the Bill's interventions; the Bill risks a democratic deficit by limiting the opportunity for parliamentary scrutiny; the duties of the bill may be too wide (in terms of burdening providers); and that enforcement of a Code of Practice will likely be insufficient.

Overview and commentary of the CDEI's extended roadmap to an effective AI assurance ecosystem.

In recent years, the field of ethical artificial intelligence (AI), or AI ethics, has gained traction and aims to develop guidelines and best practices for the responsible and ethical use of AI across sectors. As part of this, nations have proposed AI strategies, with the UK releasing both national AI and data strategies, as well as a transparency standard. Extending these efforts, the Centre for Data Ethics and Innovation (CDEI) has published an AI Assurance Roadmap, which is the first of its kind and provides guidance on how to manage the risks that come from the use of AI. In this article, we provide an overview of the document's vision for a "mature AI assurance ecosystem" and how the CDEI will work with other organizations for the development of regulation, industry standards, and the creation of AI assurance practitioners. We also provide a commentary of some key themes identified in the CDEI's roadmap in relation to (i) the complexities of building "justified trust", (ii) the role of research in AI assurance, (iii) the current developments in the AI assurance industry, and (iv) convergence with international regulation.

On the sui generis value capture of new digital technologies: The case of AI.

Much of the academic interest surrounding the emergence of new digital technologies has focused on forwarding the engineering literature, concentrating on the potential opportunities (economic, innovation, etc.) and harms (ethics, climate, etc.), with less focus on the foundational and theoretical shifts brought about by these technologies (e.g., what are "digital things"? What is the ontological nature and state of phenomena produced by and expressed in terms of digital products? Are there distinctions between the traditional conceptions of digital and non-digital technologies?. We investigate the question of what value is being expressed by an algorithm, which we conceptualize in terms of a digital asset, defining a digital asset as a valued digital thing that is derived from a particular digital technology (in this case, an algorithmic system). Our main takeaway is to invite the reader to consider artificial intelligence as a representation of the capture of value sui generis and that this may be a step change in the capture of value vis à vis the emergence of digital technologies.