In its quest to form a clear data strategy, Canada should find a balance between the privacy-centric model of the GDPR in Europe and the more business-favored strategy in China, according to Deloitte Touche Tohmatsu Limited.
This was one of the steps suggested by Deloitte in its recently published report about what the Canadian federal government should do to claim a top spot in the global AI ecosystem.
Many have called data the new oil of business, so for Canada to be able to be viewed as a business powerhouse, it must learn to harness this data while still considering the privacy of its citizens, according to Jas Jaaj, partner at Omnia AI, Deloitte.
Jaaj said a clearly defined strategy in regards to data and privacy is especially important because many of the current policies are outdated in relation to the modern world we currently live in.
“What we’re seeing is that when it comes to the Canadian policy framework, most of the policies that are in effect were created before the widespread of digitization. Which leaves room for what we call operating risk and legal gray zones for businesses and citizens,” Jaaj pointed out when questioned about the current policies in place. “And it’s time now, considering where we are in the maturity of AI, to modernize them.”
And he points to two specific examples of data strategies that have been successful in their own different ways: Europe and China.
“We always like to strike a balance between the protection aspect of the policy versus policy being used to infuse innovation into an economy. When you look at GDPR, it’s rather stringent when it comes to how the data protection framework has been laid out… where they kind of have done an excellent job in terms of protection and the privacy aspect of it. Having said that, it’s not as optimized for infusing innovation. When you look at China, on the other hand, when it comes to their digital rights frameworks that they use, they are on the other end, where it’s probably not as well protected when it comes to their citizens as it can be but definitely sparks that innovation within the ecosystem.”
And he said this is a perfect opportunity for Canada to define the middle ground between the two extremes of data strategies.
“Canada has an opportunity right now to strike that right balance by learning from these different geographies,” said Jaaj. “To be able to come up with that optimal mix and then lead the globe when it comes to demonstrating how AI can be used not only to protect and safeguard the rights and values of Canadians but also use it as an innovation engine to grow the economy.”
One concept suggested in the report was the idea of data trusts. In such a scenario, an independent organization would be entrusted with the data of multiple organizations (whether they be private corporations or government bodies) and would be responsible for deciding when and how to use the data entrusted to them.
Beyond the privacy concerns that could be allayed through this model of “data custodians”, as he calls them, Jaaj also explained that this could lead to opportunities for collaboration between data sets that may not have been possible without a data trust.
“The way in which you get the most value out of data is by combining data sets that typically don’t sit together. The trusts become a mechanism to be able to bring them together and then provide that incremental value by finding insights at the intersection of the data.”