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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.

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.

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.

This report reveals that Australian organisations lack structured governance around AI systems. Corporate leaders should invest in expertise, create a comprehensive AI strategy, implement addressing risks and support a human-centered culture. The appropriate governance of AI systems is critical for corporate leaders to mitigate risks.

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.

This report examines the impact of digital technology and artificial intelligence on human rights in Europe and Central Asia, with a particular focus on the use of data protection and legislative frameworks. It provides an overview of the relevant international and regional initiatives, and analyses the applicable legal, regulatory, and institutional frameworks.

This analytical essay outlines an agenda for research into the global governance of artificial intelligence (AI). It distinguishes between empirical research, aimed at mapping and explaining global AI governance, and normative research, aimed at developing and applying standards for appropriate global AI governance.

This report documents the location of 96 digital technology industry clusters in Australia’s capital cities, regions, and suburbs. The report draws attention to the variables that affect industry growth and development, from company profit growth to housing affordability and quality of life.

This statement from the European Group on Ethics in Science and New Technologies emphasises the need for a shared international ethical and legal framework for the design and governance of artificial intelligence, robotics, and 'autonomous' systems. It also proposes ethical principles based on EU values to guide the framework's development.

This document provides model clauses for due diligence arrangements and funding agreements related to eSafety for startups. It includes pre-conditions for funding agreements, covering policies, staffing, training, and external communication. Additionally, the document urges startups to complete the eSafety assessment tool and implement safety by design measures.

This investment checklist is a concise guidance document, aimed at investors and venture capitalists considering whether to invest in tech companies. The checklist presents a 12-point criteria touching on design and provision of services, community guidance, safety reviews, user tools, and proactive steps to inform users about safety policies.

This briefing highlights the potential human rights impact of technological advancements and the responsibility of institutional investors to mitigate these risks. Based on the UN Guiding Principles, investors should implement human rights policies, assess risks and divest from companies with inadequate human rights practices.

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.

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.

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.