Hon. Caroline Pham

This roundtable reflects Elevandi’s commitment to developing the infrastructure to support the adoption of new technologies.

Distributed Ledger Technology (DLT) is revolutionising the financial sector, with the potential to streamline processes, enhance security, and democratise access to financial services. However, as DLT-based solutions transition from traditional models towards algorithmic governance, a critical juncture has emerged.

Operating under the theme of Decoding Digital Assets and Payments, this roundtable brings together policymakers, academics, and financial experts to navigate the legal and regulatory complexities arising from the transition towards AI and algorithmic governance in DLT-based finance.

This discussion will delve into the specific challenges and opportunities that arise with this shift, including issues of sustainability, transparency, accountability, and potential biases within the algorithms themselves. By exploring these key areas and considering the potential integration with Artificial Intelligence (AI) and eventually Internet of Things (IoT), the roundtable seeks to contribute to the creation of a sustainable, robust and secure future for this transformative technology. For example, a DLT-based micro-loan platform could leverage on AI algorithms to automate document verification, creditworthiness assessment and loan approvals, potentially reducing processing times, fraud risks and increasing financial inclusion. However, ensuring that these algorithms are unbiased is crucial to prevent discrimination against certain borrowers.

Attendees who wish to familiarise themselves with the topic may refer to the reference materials here.

President of France said ‘we are regulating things that we have not yet produced or invented. It is not a good idea.’ CEO of CB Insights echoed the thought ‘The EU now has more AI regulations than meaningful AI companies.’

The questions:
- The risk of a larger non-EU-based partner using its market power to pull high-potential EU-based AI startups out of the EU. Mistral-Ai proves that risk. Germany’s Aleph Alphi and UK-based Synthesia and StabilityAI too.
- Voluntary flight of startups to non-EU locations including US, in search of capital, and more open to innovation policies. E.g. USA, Japan
- EU-based startups having to develop new code bases if they wish to sell outside of the EU, which means more time, cost, and risk
- Foundation models such as GPT-4 have been termed ‘systemic’. Has this aggressive categorization come too early?
- Need for greater transparency. To publish publicly available summaries of training data which might affect competitiveness and IP
- How does one go about educating citizens of how algorithmic harms happen if citizens have been given more agency to complain about AI systems.

Join global policymakers in a dialogue on the regulatory landscape for digital money - EU's MiCA and beyond, while unravelling the intricacies of integrating wholesale CBDCs into banking and payment systems for enhanced efficiency and resilience.