3 Changes to Canadian Privacy Law That Will Impact Business, AI, & Healthcare
Whether you are a new Canadian startup
looking to break into the healthcare app or artificial intelligence markets, a
large enterprise that deals in a lot of consumer data, or a business within the
science or education technology sectors, you may find it harder to comply with
Canadian privacy legislation. The government of Canada has announced that they
will be making several major and minor changes to Canadian privacy law, with 3of the most important ones impacting several large sectors. Here is what you
need to know!
1. Privacy
Protections are set to Increase.
The Minister of Innovation, Science, and Economic
Development, the Honourable
Navdeep Bains has introduced the Consumer Privacy
Protection Act, which proposes a new bill to upgrade the Federal Government’s
framework for protecting personal information in private sectors.
·
What does this bill do? This
bill looks at enhancing the control over both personal information and
corresponding data at the highest level.
·
Why is this important? It
means that companies will need to be aggressive and transparent about the
collection of personal information and how it is used and stored. It also
introduces a fine for any company that is not compliant with the Customer Consumer Privacy Protection Act. The
fine is up to 5% of global revenues or up to $25 million.
·
What does this mean? If
passed, it gives the privacy commissioner the ability to handle
Canadian privacy law violation cases without any outside influence.
2. AI Tech
will be Regulated.
The Privacy Commissioner of Canada, Daniel Therrien, introduced steps in November 2020 for ways
to regulate artificial intelligence. He believes that artificial intelligence
has massive potential but that it needs to be implemented with respect to human
rights and security policies. With a “rights-based” approach, Daniel Therrien
believes that AI Tech can be developed responsibly.
Why is this important? The current use of AI Tech is to decipher meaningful
patterns in historical data to help make predictions about future events. This
could be anything from the trend of insurance premiums to how many people
qualify for loans. With tech that can use data in this manner, the lives of
real people can be truly impacted.

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