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Digital business world and ethical dilemmas: A systematic literature review
This report systematically reviews ethical challenges in the digital business world, focusing on the intersection of digitalisation, corporate responsibility, and technology adoption. It highlights ethical dilemmas, such as AI transparency and sustainability, emphasising the need for tailored ethical guidelines to foster trust, innovation, and social responsibility in digital transformations.
Infrastructure tokenization: Does blockchain have a role in the financing of infrastructure?
The report explores the potential of blockchain technology in financing infrastructure projects. It evaluates blockchain's capabilities in enhancing efficiency, transparency, and accessibility in infrastructure tokenisation, while addressing challenges like regulatory constraints, market adoption, and technical barriers. The findings highlight both opportunities and limitations for integrating blockchain into infrastructure financing.
The financial stability implications of artificial intelligence
The report discusses the rapid adoption and integration of artificial intelligence (AI) in the financial sector, driven by advancements in technology and increasing operational efficiency. Key risks include dependencies on third-party providers, market correlations, and cyber vulnerabilities. Generative AI's accessibility could amplify systemic risks, necessitating enhanced regulatory frameworks, vigilant monitoring, and robust governance to ensure financial stability amid evolving AI technologies.
Synthetic content: Exploring the risks, technical approaches, and regulatory responses
Generative AI enables the rapid creation of synthetic content, offering both opportunities and risks. This report examines challenges like disinformation and fraud, outlines technical and regulatory strategies, and explores trade-offs with privacy. Techniques discussed include watermarking, provenance tracking, and legal frameworks, aiming to enhance transparency while safeguarding privacy.
Finternet: the financial system for the future
The report outlines a vision of interconnected financial ecosystems powered by digital innovation. By leveraging technologies like tokenisation and unified ledgers, it aims to create a user-centric, inclusive financial system that lowers costs, improves access, and increases efficiency globally.
Intelligent financial system: How AI is transforming finance
The report explores the transformative role of AI in the financial sector, focusing on financial intermediation, insurance, asset management, and payments. It highlights both opportunities and challenges, including implications for financial stability and the need for upgraded financial regulation to manage the risks associated with AI's growing influence.
The intersection of Responsible AI and ESG: A framework for investors
This report provides actionable insights for investors exploring the integration of Responsible AI (RAI) in their investment decisions. It offers a framework to assess the environmental, social, and governance (ESG) implications of Artificial Intelligence (AI) usage by companies. The report includes case studies of globally listed companies and a set of templates to support investors in implementing the framework.
Concrete problems in AI safety
This paper explores practical research issues associated with accidents in machine learning and artificial intelligence (AI) systems, due to incorrect objectives, scalability, or choice of behaviour. The authors present five research problems in the field, suggesting ways to mitigate risks in modern machine learning systems.
Toward a G20 framework for artificial intelligence in the workplace
This report advocates for creating a high-level, G20 framework using a set of principles for the introduction and management of big data and AI in the workplace. The paper identifies main issues and suggests two paths towards adoption.
Top 10 principles for ethical artificial intelligence
This report provides 10 principles for ethical artificial intelligence. From transparency in decision-making to ensuring a just transition and support for fundamental freedoms and rights, the report aims to empower workers and maintain a healthy balance of power in the workplace.
The state of AI in 2022 - and a half decade in review
The adoption of AI has more than doubled, with a peak of 58% in past years. The report highlights the importance of best practices and investing in AI as it is shown to bring financial returns. However, the majority of organisations are not mitigating risks associated with AI despite increasing use.
The Japanese society for artificial intelligence ethical guidelines
The Japanese Society for Artificial Intelligence has released ethical guidelines that aims to protect basic human rights and promote the peace, welfare, and public interest of humanity. The eight guidelines include: contributing to humanity, abiding by laws and regulations, respecting others' privacy, being fair, maintaining security, acting with integrity, being accountable and socially responsible, and communicating with society and self-development.
The implications of AI across sectors and against 6 key ESG considerations
AI offers great positive impacts and risks. This report helps to understand the risks associated with developing and using AI tech. Scoping exercise identifies opportunities and threats across sectors. Six core ESG considerations including trust and security, data privacy, and sentience are evaluated for potential impact.
Report of COMEST on robotics ethics
COMEST has released a report on robotics ethics which covers the history, development, and social impact of robots. It also offers recommendations for the ethical use of robotics.
Montreal declaration for a responsible development of artificial intelligence
This report outlines a framework for responsible development of artificial intelligence. It provides principles that should guide ethical use of AI for the well-being of sentient beings, respect for autonomy, protection of privacy and intimacy, solidarity, democratic participation, equity, diversity inclusion, caution, responsibility, and sustainable development.
Investors' expectations on responsible artificial intelligence and data governance
This report outlines responsible AI and data governance principles and engagement framework for investors across multiple sectors. The six core principles aim to enhance machine learning, auditability, explainability, and transparency, while taking into account legal, regulatory, ethical, and reputational risks.