{"id":176,"date":"2019-05-02T18:11:20","date_gmt":"2019-05-02T18:11:20","guid":{"rendered":"https:\/\/cusjc.ca\/mrp\/dataandthedisplaced\/?page_id=176"},"modified":"2019-06-05T19:58:31","modified_gmt":"2019-06-05T19:58:31","slug":"a-legal-system-unprepared","status":"publish","type":"page","link":"https:\/\/cusjc.ca\/mrp\/dataandthedisplaced\/a-legal-system-unprepared\/","title":{"rendered":"A legal system unprepared"},"content":{"rendered":"

[et_pb_section bb_built=”1″ fullwidth=”on” _builder_version=”3.22.5″ background_image=”https:\/\/cusjc.ca\/mrp\/dataandthedisplaced\/wp-content\/uploads\/sites\/20\/2019\/05\/legal-syst.jpg” custom_margin=”||” custom_padding=”124px||0px|||” min_height=”704px” next_background_color=”#ffffff”][et_pb_fullwidth_header title=”A legal system unprepared” subhead=”If ethical concerns surrounding AI are not fully addressed, the technology may be called into question before Canada\u2019s courts. Whether they are equipped to handle the fallout remains unclear.” content_max_width=”63%” _builder_version=”3.22.5″ title_font=”Jura|600|||||||” title_text_color=”#000000″ title_font_size=”60px” title_line_height=”1.1em” subhead_font=”Georgia||||||||” subhead_text_align=”left” subhead_text_color=”#000000″ subhead_font_size=”22px” subhead_line_height=”1.4em” background_color=”rgba(0,40,150,0)” min_height=”461px” custom_margin=”9px|||||” custom_padding=”0px|||||” text_shadow_style=”preset2″]<\/p>\n

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W<\/span>ith Canada\u2019s development of AI systems and services quietly forging ahead, fears of privacy violations and discrimination are building toward an inevitable flashpoint: a spate of legal challenges to automated decision-making. <\/span><\/p>\n

Given that AI has or will be used to sort through immigrant and visitor applications, analyze immigration litigation data and triage express entry applications, the potential exists for any of these decisions to be challenged in a court of law. \u00a0<\/span><\/p>\n

Decisions made within Canada\u2019s immigration system have already been brought before the courts \u2013 and in some cases, climbed to the top.<\/span><\/p>\n

In a landmark judgement in 1999, the Supreme Court of Canada <\/span>overturned<\/span><\/a> a Jamaican-born woman\u2019s deportation order after determining that the immigration officer overseeing her case failed to properly consider the rights of her children. Mavis Baker \u2013 who birthed four children in Canada and suffered from several mental illnesses \u2013 asked the courts to review her failed bid for permanent residency, which she made on humanitarian and compassionate grounds. <\/span><\/p>\n

 <\/p>\n

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In a judgement written by Justice Claire <\/span>L’Heureux-Dub\u00e9, the<\/span> top court ruled that the interests of Baker\u2019s children were not properly considered, and neither were Baker\u2019s given that she \u201cwas ill and might not be able to obtain treatment in Jamaica, and would necessarily be separated from at least some of her children.\u201d<\/span><\/p>\n

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\u201cStatements in the immigration officer\u2019s notes gave the impression that he may have been drawing conclusions based not on the evidence before him.”<\/span><\/em><\/span><\/h3>\n

\u2013 Justice Claire L’Heureux-Dub\u00e9<\/span><\/em><\/span><\/h3>\n<\/blockquote>\n

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The court also found that the officer\u2019s decision was rooted in bias. The decision was based on notes written by a junior officer handling the case. <\/span><\/p>\n

\u201cStatements in the immigration officer\u2019s notes gave the impression that he may have been drawing conclusions based not on the evidence before him, but on the fact that the appellant was a single mother with several children and had been diagnosed with a psychiatric illness,\u201d the judgement read.<\/span><\/p>\n

<\/span><\/p>\n

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But how might the court have ruled if it wasn\u2019t an immigration officer who dictated Baker\u2019s fate, but a computer determining a potential immigrant or refugee claimant\u2019s future?<\/span><\/p>\n

The question is now being raised by Canadian legal experts who wonder whether the federal government is prepared to handle legal challenges to decision-making services powered by artificial intelligence.<\/span><\/p>\n

One of them is Adam Goldenberg, a Toronto-based lawyer who advises clients about AI issues including ethics and emerging legal frameworks.<\/span><\/p>\n

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Goldenberg says resolving this dilemma begins with the legal system\u2019s definition of \u201creasonableness\u201d, or expected standards of human conduct. <\/span><\/p>\n

\u201cWhat the court looks at when they look at whether a decision was reasonable is a range of factors that give some wiggle room to the decision-maker not to be held to a standard of perfection,\u201d explained Goldenberg.<\/span><\/p>\n

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\n

\u201cWhat does it mean to\u00a0be reasonable if a system is making decisions on the basis of assimilating billions of data points at a rate far quicker than any human brain could ever do?\u201d <\/span><\/em><\/h3>\n

\u2013 Adam Goldenberg<\/span><\/em><\/span><\/h3>\n<\/blockquote>\n

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At FWD50, an Ottawa conference about digital government last November, Goldenberg posed a critical question about this concept to his audience of public servants. <\/span><\/p>\n

\u201cWhat does it mean to\u00a0be reasonable if a system is making decisions on the basis of assimilating billions of data points at a rate far quicker than any human brain could ever do?\u201d <\/span><\/p>\n

The short answer? We don\u2019t know. <\/span><\/p>\n

But considering that AI initiatives are unrolling across a number of federal departments, we should.<\/span><\/p>\n

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Goldenberg delivers a presentation on ethical AI in government during Ottawa\u2019s FWD50 conference in November 2018. [Photo \u00a9 Raisa Patel]<\/span><\/em><\/p>\n

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According to Petra Molnar, it\u2019s already difficult to challenge a decision made within Canada\u2019s immigration and refugee system.<\/span><\/p>\n

\u201cIt really does have life or death impacts in some ways,\u201d Molnar said. \u201cThese are well-known sectors for being more opaque, more discretionary and for people being less able to exercise their procedural and substantive rights.\u201d<\/span><\/p>\n

In a <\/span>notice of tender<\/span><\/a> published last spring, IRCC indicated that Pre-Removal Risk Assessments and Humanitarian and Compassionate applications \u2013 typically last resort options used by people in particularly dire situations \u2013 would be potential targets for automated processing. Molnar said the department has since told her it is not planning to use AI for such applications, but she is not entirely convinced. <\/span><\/p>\n

\u201cOur major concern is moving ahead with experimenting with these technologies before having an accountability and an oversight mechanism in place,\u201d Molnar said.<\/span><\/p>\n

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Treasury Board\u2019s directive is the closest document to such a mechanism, but federal departments don\u2019t need to comply with the guidelines until April 1, 2020. And because the directive is a piece of policy, it\u2019s not as strong as legislation.<\/span><\/p>\n

\u201cIt’s not binding like it would be legislation. Nobody is going to jail if they don’t [follow] it,\u201d said Ashley Casovan.<\/span><\/p>\n

There are some consequences associated with a failure to comply. Depending on <\/span>how severely<\/span><\/a> the directive is disregarded, fallout for individuals ranges from receiving more training to losing their job, while institutions might be asked to work more collaboratively or face reorganization. <\/span><\/p>\n

Federal departments have until 2020 to work on their AI projects before Treasury Board begins to monitor compliance, but it\u2019s unclear whether adhering to the directive is required for decision-making processes already subjected to the technology. <\/span><\/p>\n

Goldenberg is certain that decisions made by computer will be challenged on the basis of being \u201cprocedurally unfair\u201d. He\u2019s referring to a legal principle within administrative law, the area of law that involves government operations and decisions. It concerns a person\u2019s right to be heard, to due process, to appeal and to have an impartial decision-maker. Respecting this concept is a key component of Treasury Board\u2019s directive. <\/span><\/p>\n

It was also the guiding principle behind the court\u2019s judgment in Mavis Baker\u2019s Supreme Court case. In the same way that judges analyzed notes written by an immigration officer involved with Baker\u2019s file, so too will they need to understand an AI system\u2019s algorithms and how they were created. <\/span><\/p>\n

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Tech under wraps<\/strong><\/span><\/h3>\n

<\/strong><\/span><\/p>\n

But while Goldenberg highlights government transparency as one of the most necessary paths forward, Molnar identified another roadblock.<\/span><\/p>\n

\u201cThe whole other piece to this is the role of the private sector,\u201d she said. <\/span><\/p>\n

\u201cYou can’t really develop all these innovative new tools without direct involvement of the private sector, but then you get into issues of intellectual property and proprietary rights. Asking for a full transparency mechanism has a lot of pushback.\u201d<\/span><\/p>\n

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A key section of Molnar\u2019s Citizen Lab report, warning of the dangers of AI in Canada\u2019s \u00a0immigration and refugee system, is about transparency in the private sector. [Photo \u00a9 Raisa Patel]<\/span><\/em><\/p>\n

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Across our southern border, the clash between technology firms and the legal system has already begun.<\/span><\/p>\n

In 2013, a judge sentenced a Wisconsin man named Eric Loomis to six years in prison \u2013 a number determined after considering both Loomis\u2019 criminal record and a risk-assessment algorithm. The policing tool used was designed to measure the likelihood of a defendant committing another crime and it identified Loomis as high risk. He appealed the ruling on the grounds that his rights to due process were violated because the algorithm itself was created by a private company and was therefore not open to scrutiny. While Loomis was white, the algorithm had also been independently determined to falsely rate offenders of colour at a higher risk of reoffending than white offenders. \u00a0<\/span><\/p>\n

The Wisconsin Supreme Court <\/span>ruled against<\/span><\/a> Loomis. It was found that without using the tool, his high-risk rating still stood. But Justice Ann Walsh Bradley, writing for the court, warned that such assessments \u201cmust be subject to certain cautions.\u201d Besides unfairly rating minority offenders, such cautions included the fact that the assessments were based on a national sample of offenders, which might not be accurate at the state level. <\/span><\/p>\n

Loomis appealed to the Supreme Court of the United States to overturn the decision, but the country\u2019s top court declined to hear the case. <\/span><\/p>\n

In Canada, the Directive on Automated Decision-Making addresses the issue, stating that proprietary technology should be made publicly available when possible. It notes that the government will have access to systems if they are required for a \u201cspecific audit, investigation, inspection, examination, enforcement action, or judicial proceeding, subject to safeguards against unauthorized disclosure.\u201d It\u2019s not clear, however, whether private companies will be forced to follow this policy. <\/span><\/p>\n

As for those affected by AI-based decisions, Casovan said systems of redress will differ across departments. <\/span><\/p>\n

\u201cIt\u2019s really <\/span>going to depend on the nature of what that decision is,\u201d she said. <\/span><\/p>\n

\u201cFor people being able to have some recourse associated with whether or not they got a visa to cross the border, then I would hope that that would be the case, and that’s what we’ve tried to encourage.\u201d<\/span><\/p>\n

In the legal system itself, the bulk of the responsibility currently lies with litigators to explain new technologies to judges. But Goldenberg said technological literacy is already being taught in some in law schools and that judicial education should follow suit. The lawyer suggested that in the future, certain divisions of the court or particular judges could handle technical matters related to AI. Or, federal and provincial governments might create specialized courts to deal with AI, as Canada did with its tax court, though such cases could still wind up at the Supreme Court of Canada. <\/span><\/p>\n

For now, Molnar continues to spark discussions on stronger AI regulation with legal experts, academics and the immigrants and refugees at the heart of the debate. <\/span><\/p>\n

\u201cThat’s why we wanted to raise this conversation now, before five, ten years down the line when real issues are going to start coming to the table,\u201d she said. <\/span><\/p>\n

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W<\/span>ith Canada\u2019s development of AI systems and services quietly forging ahead, fears of privacy violations and discrimination are building toward an inevitable flashpoint: a spate of legal challenges to automated decision-making. Given that AI has or will be used to sort through immigrant and visitor applications, analyze immigration litigation data and triage express entry applications, […]<\/p>\n","protected":false},"author":22,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":"","ngg_post_thumbnail":0,"footnotes":""},"class_list":["post-176","page","type-page","status-publish","hentry"],"yoast_head":"\nA legal system unprepared - Data and the displaced<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/cusjc.ca\/mrp\/dataandthedisplaced\/a-legal-system-unprepared\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"A legal system unprepared - Data and the displaced\" \/>\n<meta property=\"og:description\" content=\"ith Canada\u2019s development of AI systems and services quietly forging ahead, fears of privacy violations and discrimination are building toward an inevitable flashpoint: a spate of legal challenges to automated decision-making. 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