Blockchain Summer Institute Blockathon 2024

Blockathon: Blockchain & Responsible AI

Artificial intelligence (AI) has rapidly developed in the past two years, largely due to the widespread adoption of ChatGPT and other large language models. This progress has led industry experts and governments to anticipate the dawn of an AI era characterized by heightened automation, efficiency, and productivity. Startups and established organizations have begun to invest billions of dollars into AI development, ranging from infrastructure, industry software, to consumer applications. Many industries are attempting to adopt AI, for example, the pharmaceutical industry seeks to use AI to accelerate drug discovery and the finance industry aims to use AI to automate banking and trading,

Despite AI's immense potential to revolutionize industries and economies, scientists have warned of its risks. Biased AI algorithms, for instance, can reinforce discrimination, while the lack of transparency in AI training models raises concerns about data privacy and usage. Moreover, AI may disrupt the labor market, render many occupations irrelevant, and erode the boundary between human lives and machinery. To harness the benefits of AI while mitigating risks, governments worldwide are actively exploring AI regulations, with the European Union leading the effort by publishing the EU Regulation on Artificial Intelligence (AI Act).

Recently, the concept of responsible AI has gained much attention among scientists and industry leaders. According to IBM, responsible AI refers to “a set of principles guiding the design, development, deployment, and use of AI, fostering trust in solutions that empower organizations and stakeholders” (https://www.ibm.com/topics/responsible-ai). Specifically, responsible AI entails that:

1. AI systems must be aligned with ethical principles, human values, and societal norms. This includes respect for human dignity, privacy, autonomy, fairness, transparency, accountability, and non-discrimination.
2. AI systems need to be explainable and transparent. Developers should be able to explain how they develop AI models, what data they use, how they access the data, and what factors influence outcomes. 
3. AI systems should be fair. It should not reinforce social bias based on gender, ethnicity, sexual orientation, disability etc, especially when it comes to hiring and accessing healthcare. 
4. Responsible AI should not evade people’s rights to privacy. AI systems should only collect, use, and retain personal data for legitimate purposes and with individuals' informed consent, and should not expose people’s sensitive information. 
5. Responsible AI prioritizes security and should be resistant to various security attacks. 
6. AI systems must be held accountable. Mechanisms for auditing, oversight, and recourse in case of adverse impacts or violations must be in place. 

Experts argue that blockchain technology can play a pivotal role in realizing responsible AI. Blockchain, a distributed ledger characterized by immutability, transparency, and tamper-proof nature, offers advantages in enhancing AI systems' security, privacy preservation, and transparency. By integrating blockchain with AI systems, users gain visibility into data sources and model training processes, while regulators can audit compliance with regulatory requirements. Some initiatives aim to develop blockchain-based data marketplaces for AI, where individuals retain control over their data and smart contracts automate data sharing. Others propose applying decentralized governance structures such as DAO to AI development, ensuring democratic decision-making and reflecting the interests of the majority. The emerging field of decentralized physical infrastructure has much overlap with AI development, providing decentralized environments to enable greater security, privacy, and accountability in AI development. 

In this blockathon, you are tasked with identifying a specific problem of responsible AI that blockchain can solve, developing a solution, and providing detailed architectural elaboration. You may develop a simple demo, such as a wireframe or user interface, to illustrate your solution. You may choose any industry verticals that interest you, for example, healthcare, energy, finance, or AI infrastructure, as long as the problem you aim to solve is clear and sensible. You are encouraged to apply discretion and creativity.

Readings:

1. The European Artificial Intelligence Act: The Act Texts | EU Artificial Intelligence Act
2. J. D. Harris and B. Waggoner, "Decentralized and Collaborative AI on Blockchain," 2019 IEEE International Conference on Blockchain (Blockchain), Atlanta, GA, USA, 2019, pp. 368-375, doi: 10.1109/Blockchain.2019.00057. 
3. Nassar M, Salah K, ur Rehman MH, Svetinovic D. Blockchain for explainable and trustworthy artificial intelligence. WIREs Data Mining Knowl Discov. 2020; 10:e1340. https://doi.org/10.1002/widm.1340
4. S. K. Lo et al., "Toward Trustworthy AI: Blockchain-Based Architecture Design for Accountability and Fairness of Federated Learning Systems," in IEEE Internet of Things Journal, vol. 10, no. 4, pp. 3276-3284, 15 Feb.15, 2023, doi: 10.1109/JIOT.2022.3144450.
5. Y. Liu, Q. Lu, L. Zhu and H. -Y. Paik, "Decentralised Governance for Foundation Model based AI Systems: Exploring the Role of Blockchain in Responsible AI," in IEEE Software, doi: 10.1109/MS.2024.3369551.