New Zealand's Privacy Commissioner, John Edwards, is firing on all cylinders, tackling some of the most vexing issues facing technology developers and users alike.
With a new Privacy bill before Parliament, Edwards has still found time to comment and act on new EU data protection regulations and what could be the debate of the century - the role of artificial intelligence and automated decision making.
This week, Edwards fired a warning salvo across the bows of supermarket operator Foodstuffs after the company admitted it had deployed facial recognition technology to tackle shoplifting.
The Commissioner even took a stand late last year in a long running privacy case involving Microsoft, supported by other cloud providers, before the US Supreme Court.
In a speech to the Privacy Forum at Te Papa last week, Edwards suggested the country's own Privacy Act could benefit from the adoption of aspects of the EU's General Data Protection Regulation (GDPR), which comes into effect next week.
Among other issues, GDPR addresses automated decision making and artificial intelligence, giving individuals the right to human intervention in cases where adverse decisions are made.
The controller of the data used to make the decision under GDPR will have a duty to safeguard the rights, freedoms and interests of the subjects of those decisions, at least to the point of being able to contest the decision and receive human review of it.
"These protections are significant in the context of international benchmark setting," Edwards said. "They are an influential signpost to future regulatory settings on automated decision making for greater transparency.
"I’m going to draw them to Parliament’s attention when we make our submission on the Privacy Bill and suggest that they might make a useful addition to the regulatory framework here, now that we have that rare opportunity."
Edwards said the use of algorithmic decision making might affect resource allocation, the availability of goods or services to particular individuals in the economy provided by commercial or government agencies.
CEOs and ministers are asking about automation, he said. What can be learned from datasets to inform policy, or business strategy?
"The pressure to look to technology to provide answers to complex social problems is increasing, and is supported by consultancies, data scientists and software vendors," he added.
And that brings the conversation back to the facial recognition technology used by the likes of Foodstuffs because it works through the use of AI and machine learning.
Edwards cited a study on bias in facial recognition software by Joy Buolamwini at the MIT Media Lab, which showed that gender was misidentified in less than one per cent of lighter-skinned males; in up to seven per cent of lighter-skinned females; up to 12 per cent of darker skinned males; and up to 35 per cent in darker-skinned females.
“Overall, male subjects were more accurately classified than female subjects and lighter subjects were more accurately classified than darker individuals,” Edwards said.
It was one of the problems the Commissioner foresaw when reporting reservations about the now cancelled Ministry of Social Development plan to tie funding to data in the NGO sector.
"If you drive away the most vulnerable, their data won’t be in your system," Edwards said. "They won’t be reported on, and therefore they’ll be less likely to be targeted for assistance."
It could even make the problem disappear, he said: "No data, no problem!"
Even a small error rate can create big problems, Edwards said.
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