The amount of data required to train complex artificial intelligence models is staggering — and will only continue to increase as those technologies evolve. But all that data can come with significant risk, from copyright infringement and potential misuse to reconciling its collection with the principle of data minimization.
In the second module of our new AI webinar series, Osler partners Adam Kardash, Barry Fong and Sam Ip explored some of the intellectual property and privacy concerns raised by the data-intensive processes involved in emerging AI technologies.
Topics covered during their discussion included
- the role of different types of data in the development of AI models
- privacy and IP risks related to data scraping, input and output data, and how to allocate and mitigate them
- how Canadian copyright legislation might interact with data used for AI purposes
- cybersecurity issues
- how privacy reforms in Canada could affect AI technologies
- data governance considerations for companies
- expanding sources of legal and regulatory obligations
The next session in the AI webinar series, taking place on May 4, will focus on bias, harm and minimization of risk.
The content of this article is intended to provide a general guide to the subject matter. Specialist advice should be sought about your specific circumstances.
