Papers & Publications

Research on the impact of generative AI on productivity, innovation, and entrepreneurship highlights the extent to which AI automates tasks, enhances skills, and transforms business operations. Findings suggest that AI’s effectiveness depends on the user’s experience and the task carried out, with human-AI collaboration being key to maximising its potential.

Privacy-enhancing technologies (PETs) foster trust in the collaborative development and sharing of AI models while safeguarding privacy, intellectual property, and sensitive information. They can reduce the need for additional data collection, facilitate data-sharing partnerships, and address AI governance risks.

Empirical evidence about AI markets helps show if potential AI users benefit from favourable market developments regarding prices, quality and variety. Extensive data collection covers the characteristics of Generative AI models, like performance and pricing, as well as developers, cloud providers, and downstream applications.

Understanding impact of digital technologies and AI on healthcare occupations across OECD countries, focusing on innovations can support healthcare workers amid rising demand. The study analyses online job postings from Canada, the United Kingdom and the United States, tracking demand for digital and AI skills in healthcare between 2018 and 2023.

The evolution of the digital technology ecosystem is driving economic and societal changes, with the information and communication technology (ICT) sector at its core proving dynamic and resilient in the face of economic headwinds. As digital technologies like artificial intelligence, virtual reality and next generation networks permeate our lives and the economy, it is critical […]

This paper presents a common reporting framework for AI incidents, providing a global benchmark for stakeholders across jurisdictions and sectors. It enables countries to adopt a common reporting approach while allowing them to tailor responses to their domestic policies and legal frameworks.

Analysing the demand for talent proficient in developing or working with AI systems in Canada, using Online Job Postings (OJPs) from 2018 to 2023, reveals a steady increase in demand, which peaked in 2021 but has slowed in 2022 and 2023. But the demand for AI skills in specialised fields has expanded significantly.

As the demand for AI training data surges, certain data collection methods raise concerns about the protection of intellectual property (IP) and other rights. This overview of key issues at the intersection of AI and some IP rights facilitates a greater understanding of data scraping.

There is a need for adaptable governance frameworks to navigate the rapid advancements and complexities of AI. It analyses AI’s potential and challenges and the inclusion of proactive strategies to anticipate developments and ensure responsible innovation.