Leaps and Boundaries

Summary

Advances in artificial intelligence (AI) have the potential to transform the nature of scientific inquiry and lead to significant innovations in engineering. To date, AI has primarily been used alongside existing design and discovery practices to help researchers analyze or interpret data, e.g., predict the structure of proteins, track insect biodiversity, etc. However, AI will play a much bigger role in design and discovery in the near future―developing novel scientific hypotheses and experiments and creating new engineering design processes―all with minimal human involvement.

While AI has the potential to spur innovation and further scientific understanding beyond the limits of the human mind and abilities, it could also exacerbate inequities, perpetuate human biases, and even create new ones. Maximizing the benefits of AI and avoiding its pitfalls, will require addressing real and imminent challenges.

Leaps and Boundaries explores the opportunities, challenges, and implications of deploying AI technologies to enable scientific and engineering research design and discovery in Canada.

Key findings

The state of AI in science and engineering is undergoing rapid growth and change. Due to growing volumes of data, inexpensive computing resources, and a broadening scope of application across all stages of design and discovery, AI has become a widely used tool in science and engineering. However, despite an increasing number of reported breakthroughs demonstrating the promise of AI, several real and imminent challenges must first be overcome. A central tension exists in finding the balance between encouraging the development of this technology — including the associated social and economic benefits — while also protecting human rights and ensuring the ethical and responsible use of AI throughout its life cycle.

Report findings

• The capabilities of AI systems have grown and can be applied to an increasing variety of tasks in science and engineering
• The increased use of AI in science and engineering creates new epistemic, methodological, and ethical challenges for researchers
• The R&D environment in Canada will face challenges in adapting its practices for the assessment of research and researchers using AI
• The increased deployment of AI systems for science and engineering risks perpetuating discrimination or biases both within the Canadian R&D environment and in broader society
• The increased use of AI in science and engineering is likely to have wider social impacts on the science and engineering labour market, public trust in AI and science, the environment, and cybersecurity
• Technological development is outpacing the development of legal and regulatory frameworks that govern AI systems, leading to uncertainty with deployment and commercialization
• The use of AI systems in science and engineering are pushing disciplinary boundaries, collaboration, and coordination towards a transdisciplinary future