As blockchain technology finds applications in use cases involving Self-Sovereign Identities (SSI), citizens and public organisations can establish trust in a transparent and direct way without the need for intermediaries. This direct channel of verifying identity and transparency can also extend to use cases involving AI. In the era of generative AI, it is important to be able to trace back AI-generated content to the original creator. The benefit of this is twofold: a) biased content and deep fakes can be detected more easily and b) creators are protected from copyright infringement. Leveraging SSI to provide digital signatures in AI-generated content and demanding that such content is digitally signed achieves both the above objectives and provides an extra layer of protection to end users and organisations.
Self-Sovereign Identity in AI
Self-sovereign identity (SSI) allows individuals to establish and manage their own identity without the need for identity providers. Under the SSI model, identities, whether they belong to an individual or correspond to an organisation, are handled exclusively by the identity holder. Data ownership is proved via the SSI, and transactions that involve presentation of proof, validation of credentials and even transfer of asset ownership do not require a central authority to act as an arbiter between transacting partners. As SSIs are, in practice, decentralized identities, it is evident that blockchain technology is a big enabler for establishing an SSI.
Apart from data ownership and control, which are some of the big benefits of SSI, its application can be easily seen in the field of AI and the way data subjects and content creators can use it for better data control.
First of all, by using third parties for identity provision and verification, data subjects can have their identity details stored at various repositories, the number of which may be difficult to track. While, in theory, they can use the right to be forgotten to remove the relevant entries, their data may meanwhile be used by a data processor and embedded into an AI model that is used, for example, for advertising purposes. It is extremely difficult to have control over this information and even track the various knowledge bases where the subject’s information has been leaked.
Moreover, from a creator’s point of view, generative AI has been increasingly used to create content. Copyright of content can be more easily proved and controlled via an SSI scheme, in which a user signs the document with their SSI keys without delegating this functionality to third parties, which can make dispute claims hard to resolve.
In a more drastic step, the SSI can be applied to the AI models themselves; that is, an AI-generated report can be signed by an SSI that the AI has issued itself. In this way, bias reports will be traced back to the AI that has generated them, thereby increasing transparency. In a similar context, deep fakes based on AI would be detected more efficiently by requiring reports to be signed and tracing back the SSI to confirm the creator’s identity, whether this is a real person or an AI.
As AI4Gov will investigate the development of AI models for bias detection and policy-making, it is very important that these models can be easily linked to the identities of their creators but also to the ones that invoke instances of these models for decision-making. This ability establishes both ownership and accountability, which are two of the main goals of SSI.
Decentralized Applications (dApps) under SSI
AI4Gov will offer organisations the ability to run smart contracts that will execute a mutually endorsed business logic to process data and generate bias reports and policy recommendations. These smart contracts will be accessed via decentralized applications (dApps). To make sure that these dApps are installed and run in a manner that the user completely controls, the dApps will be implemented using SSI; such dApps are often referred to as SSApps and are a key concept of the OpenDSU framework, that the AI4Gov will utilise.
A SSApp allows users not only to control their data but the whole execution environment. In an SSApp, both the running code and the referenced data are anchored under the user’s identity, who has complete control of what is stored but also of what exactly is installed and run on her/his device.
Recognizing the transformative potential of blockchain technology, the European Union (EU) has taken significant strides in establishing the European Blockchain Services Infrastructure (EBSI). Created in 2018, the European Blockchain Services Infrastructure (EBSI) is the EU’s “official” blockchain infrastructure. It operates with nodes across EU countries with the goal of offering its services to organisations and citizens across Europe. With its promise of enhancing transparency, security, and efficiency, EBSI stands as a testament to Europe’s commitment to fostering innovation and digitalization. EBSI operates with the fundamental objective of fostering trust, transparency, and security in digital transactions while promoting interoperability across various sectors.
Although the main use cases demonstrated so far fall under the credential verification category of use cases, it is expected that EBSI will also be adopted for use cases involving supply chains, trust environments, etc. One initiative that tries to integrate SSI with the EBSI is the European Self Sovereign Identity Framework (ESSIF), which aims to become one of the Connecting Europe Facilities (CEF) components. ESSIF’s main objective is to implement SSI capability by leveraging EBSI. AI4Gov will implement its wallet application following the ESSIF and the SSApps principles and will demonstrate that the wallet satisfies the EBSI conformance test requirements.
In this manner, AI4Gov aspires to realise one of the first use cases, which demonstrates the ability to integrate AI and SSI in a manner that is ready to adopt using the EBSI infrastructure.
The EBSI/ESSIF Framework. (Figure by the European Commission)