Privacy & Confidentiality In An AI-Driven World…
I’ve just submitted the following abstract for a book on Artificial Intelligence, Intellectual Property, Crypto and Social Media:
This chapter investigates the intersections of property, platforms, and artificial intelligence (AI), tracing their historical evolution in order to critique how centralised digital systems have concentrated wealth and limited individual agency. By examining the transformative potential of Web3 and blockchain technologies, it posits that property and value creation in a decentralised, AI-driven economy is a realistic way to foster equitable and user-driven digital ecosystems.
It begins by tracing the origins of private property rights to the Agricultural Revolution. This shift introduced the concept of tangible and intangible property as foundational platforms for economic growth and innovation. These assets provided the basis for industries and networks that drive wealth creation.
The chapter situates this historical perspective within the so-called “digital age,” exploring how the rise of Web1 and Web2 reshaped property dynamics. In Web2, users became renters of their own content, relinquishing ownership to centralised platforms in exchange for participation. Social media giants transformed user-generated content into first-party data, building economic value through network effects while excluding users from the resulting financial benefits. This model of centralised ownership is critiqued for perpetuating wealth inequality, emphasising the need for a new paradigm.
The discussion transitions to the transformative potential of Web3, a decentralised system where individuals regain control over their digital assets through tokenisation. Web3 offers economic agency and the ability to monetise personal data on their own terms. This shift promises a redistribution of economic value from centralised entities to individual users, fostering a more equitable digital economy.
Against this backdrop, the chapter critically examines the advancements of generative AI and their implications for property, ownership, and economic systems. Generative AI, trained on massive datasets sourced from publicly available content, raises ethical concerns regarding intellectual property and compensation. Through case studies, the chapter argues that blockchain technology could provide solutions by ensuring transparency, provenance, and fair compensation for data sources. The chapter illustrates the growing shift toward user-owned content and the role of blockchain in facilitating interoperability and trust. These case studies underscore the importance of decentralisation in addressing the exploitative nature of current digital systems.
The chapter also addresses the broader societal and economic impacts of generative AI. It critiques the disruption of traditional economic growth drivers, such as population decline and productivity and explores the potential for AI to usher in a post-scarcity economy characterised by abundant knowledge and resources. In this context, the chapter reimagines the role of property, wealth, and agency, suggesting that value may shift from ownership of tangible and intangible assets to human-centred experiences, relationships, and community.
Concluding with actionable recommendations, the chapter advocates for leveraging Web3 technologies to empower individuals and foster community-driven economies. It emphasises the need to design systems that prioritise user control, compensation, and inclusivity while addressing the ethical challenges posed by AI. By bridging theoretical perspectives with practical applications, the chapter offers a framework for rethinking wealth, ownership, and agency in an era defined by AI-driven abundance and decentralisation.
