{"id":57931,"date":"2018-02-08T00:00:00","date_gmt":"2018-02-07T22:00:00","guid":{"rendered":"https:\/\/richardvanhooijdonk.com\/blog\/google-brain-might-save-lives-but-it-threatens-privacy-at-the-same-time-should-we-take-the-bad-with-the-good\/"},"modified":"2021-07-22T12:17:44","modified_gmt":"2021-07-22T10:17:44","slug":"google-brain-might-save-lives-but-it-threatens-privacy-at-the-same-time-should-we-take-the-bad-with-the-good","status":"publish","type":"post","link":"https:\/\/blog.richardvanhooijdonk.com\/en\/google-brain-might-save-lives-but-it-threatens-privacy-at-the-same-time-should-we-take-the-bad-with-the-good\/","title":{"rendered":"Google Brain might save lives, but it threatens privacy at the same time. Should we take the bad with the good?"},"content":{"rendered":"<ul class=\"bold-list\">\n<li>Google Brain uses patient data to predict outcomes and help care providers<\/li>\n<li>Was the project a huge success? We\u2019ll soon know<\/li>\n<li>DeepMind processed data without consent from any of the patients<\/li>\n<li>The NHS broke privacy laws and Google apologises<\/li>\n<\/ul>\n<p>For hospitals, getting <a href=\"https:\/\/blog.richardvanhooijdonk.com\/en\/blog\/3-incredible-medical-innovations-shape-future-patient-care\/\">patient care<\/a> right is always critical. And to better assess a patient\u2019s needs, healthcare providers can really use an accurate sense of likely outcomes. Will she need to be admitted? Will she get better soon? How long will she stay in hospital? Will she return soon for the same problem? In fact, the range of questions that bear on the allocation of scarce resources like computed tomography (CT) scans or the direct attention of physicians is huge.<\/p>\n<p><iframe title=\"Google Brain might save lives, but it threatens privacy at the same time.\" width=\"800\" height=\"450\" src=\"https:\/\/www.youtube.com\/embed\/mcutqIZ-g0k?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen><\/iframe><\/p>\n<p>In a pilot study in the US, <a href=\"https:\/\/research.google.com\/teams\/brain\/\">Google Brain<\/a> tested its artificial intelligence (AI) and machine learning on anonymised patient records. Drawing personal data from two hospitals over 11 years, Google Brain wanted to demonstrate that a state-of-the-art system could provide the predictive analytics hospitals need to better care for their patients. Google reports astounding results, but they still need to be confirmed by third parties. Simultaneously, recent projects in the UK involving Google have privacy advocates deeply concerned. Which leads us to the question if the risks of using <a href=\"https:\/\/blog.richardvanhooijdonk.com\/en\/blog\/big-data-trends\/\">big data in healthcare<\/a> are really worth the rewards.<\/p>\n<h2>Google Brain uses patient data to predict outcomes and help care providers<\/h2>\n<p><a href=\"https:\/\/qz.com\/1189730\/google-is-using-46-billion-data-points-to-predict-the-medical-outcomes-of-hospital-patients\/\">According<\/a> to Dave Gershgorn at <em>Quartz<\/em>, the data was provided by \u201ctwo hospitals, the University of California San Francisco Medical Center (from 2012-2016) and the University of Chicago Medicine (2009-2016)\u201d. Christina Farr, reporting for <em>CNBC<\/em>, <a href=\"https:\/\/www.cnbc.com\/2017\/05\/17\/google-brain-medical-records-prediction-illness.html\">says<\/a> that these medical centres \u201cstripped millions of patient medical records of personally identifying data and shared them with Google&#8217;s research team\u201d. The goal was to provide Google Brain with the raw data to run predictive analyses.<\/p>\n<figure id=\"attachment_32586\" aria-describedby=\"caption-attachment-32586\" style=\"width: 800px\" class=\"wp-caption aligncenter\"><img fetchpriority=\"high\" decoding=\"async\" class=\"wp-image-32586 size-full\" src=\"https:\/\/blog.richardvanhooijdonk.com\/wp-content\/uploads\/sites\/4\/2019\/05\/google-data-centers-19-1.jpg\" alt=\"The inside of a Google data centre emitting blue light\" width=\"800\" height=\"600\"><figcaption id=\"caption-attachment-32586\" class=\"wp-caption-text\">The goal was to provide Google Brain with the raw data to run predictive analyses.<\/figcaption><\/figure>\n<p>But assessing this data is a lot more difficult than you might imagine. These records provided nearly 47 billion data points, <a href=\"http:\/\/www.businessinsider.com\/digital-health-briefing-google-researchers-use-ai-to-predict-patient-mortality-mental-health-chatbot-launches-on-ios-israel-pm-reveals-national-digital-health-project-2018-1\">reports<\/a> Laurie Beaver for <em>Business Insider<\/em>. That\u2019s an incredible amount of raw information, far beyond what human beings can handle. So Google Brain is using very advanced machine learning to deal with this massive volume of facts. Its AI relies on cognitive networks that act a lot like your brain, sifting and sorting information before passing provisional conclusions to a higher level for more analysis. Essentially mimicking the human mind, these deep learning systems actually\u2026 well\u2026 learn. Given the monumental task they were attempting, Google Brain chose to use three such neural networks, really doubling-down on analytical power.<\/p>\n<p>In this case, to sort what matters from what doesn\u2019t, these machine learning systems assessed the data against known outcomes, working out the details that matter in patient records. But this introduced a second layer of complexity. Many of these patient files are hand-written notes, and since each doctor and nurse has different handwriting, and since they can all take notes differently, Google Brain\u2019s AI had to learn to decode script, find which words were important, and link them to important events. But \u201cAfter analyzing thousands of patients\u201d, Gershgorn <a href=\"https:\/\/qz.com\/1198671\/depression-warning-signs-pay-attention-to-the-words-they-use\/\">writes<\/a>, \u201cthe system identified which words and events associated closest with outcomes, and learned to pay less attention to what it determined to be extraneous data\u201d.<\/p>\n<h2>Was the project a huge success? We\u2019ll soon know<\/h2>\n<p>In a <a href=\"https:\/\/arxiv.org\/abs\/1801.07860\">paper<\/a> that has yet to be peer-reviewed, Google claims an enormous success. \u201cWhile the results have not been independently validated, Google claims vast improvements over traditional models used today for predicting medical outcomes. Its biggest claim is the ability to predict patient deaths 24-48 hours before current methods, which could allow time for doctors to administer life-saving procedures.\u201d If this result is real, that\u2019s huge. But don\u2019t start your standing ovation just yet.<\/p>\n<p>If you paused for a second when you read that the University of San Francisco Medical Center and the University of Chicago Medicine shared sensitive patient information, we don\u2019t blame you. This patient data was stripped of personal information, but was it the hospitals\u2019 to share? There are real reasons for concern here, and in the UK, Google and its subsidiary, <a href=\"https:\/\/deepmind.com\/\">DeepMind Technologies Ltd.<\/a>, are now embroiled in a controversy centred on this technology and their approach.<\/p>\n<h2>DeepMind processed data without consent from any of the patients<\/h2>\n<p>In 2015, a deal was struck between Google and the Royal Free London NHS Foundation Trust to develop an app called Streams that would help doctors treat acute kidney injury (AKI), a health problem that kills as many as 40,000 people in the UK alone. But in a <a href=\"https:\/\/link.springer.com\/article\/10.1007\/s12553-017-0179-1\">peer-reviewed paper<\/a>, published in the journal <em>Health and Technology<\/em>, Julia Powles and Hal Hodson note that this \u201cinvolved the transfer of identifiable patient records across the entire Trust, without explicit consent, for the purpose of developing a clinical alert app for kidney injury\u201d. To understand the scope of the controversy, it\u2019s important to <a href=\"https:\/\/link.springer.com\/article\/10.1007\/s12553-017-0179-1\">realise<\/a> that Royal Free is \u201cone of the largest healthcare providers in Britain\u2019s publicly funded National Health Service\u201d, and that this data compromised the records of millions of patients in the UK.<\/p>\n<figure id=\"attachment_32590\" aria-describedby=\"caption-attachment-32590\" style=\"width: 800px\" class=\"wp-caption aligncenter\"><img decoding=\"async\" class=\"wp-image-32590 size-full\" src=\"https:\/\/blog.richardvanhooijdonk.com\/wp-content\/uploads\/sites\/4\/2019\/05\/app_streams-2.jpg\" alt=\"Hand holding a smartphone with the app featuring medical records for a patient named Robert Jones\" width=\"800\" height=\"600\"><figcaption id=\"caption-attachment-32590\" class=\"wp-caption-text\">In 2015, a deal was struck between Google and the Royal Free London NHS Foundation Trust to develop an app called Streams that would help doctors treat acute kidney injury (AKI), a health problem that kills as many as 40,000 people in the UK alone.<\/figcaption><\/figure>\n<p>And as these researchers caution, the legal restrictions on what Google could do with this data were less than robust: these limitations \u201cappear to have been given little to no legal foundation in Google and DeepMind\u2019s dealings with Royal Free\u201d, they <a href=\"https:\/\/link.springer.com\/article\/10.1007\/s12553-017-0179-1\">warn<\/a>. Worse still, patients weren\u2019t required to consent to this transfer. As Powles and Hodson <a href=\"https:\/\/link.springer.com\/article\/10.1007\/s12553-017-0179-1\">observe<\/a>, \u201cThe data that DeepMind processed under the Royal Free project was transferred to it without obtaining explicit consent from \u2014 or even giving any notice to \u2014 any of the patients in the dataset\u2026 [that] included every patient admission, discharge and transfer within constituent hospitals of Royal Free over a more than five-year period (dating back to 2010).\u201d<\/p>\n<p><iframe title=\"DeepMind Health \u2013\u00a0Partnership with the Royal Free London NHS Foundation Trust\" width=\"800\" height=\"450\" src=\"https:\/\/www.youtube.com\/embed\/wQU9wsFnO4k?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen><\/iframe><\/p>\n<p>You don\u2019t need to be a privacy watchdog to be worried by that, and Powles and Hodson make it abundantly clear that these weren\u2019t innocent \u2018mistakes\u2019. Millions of records, with identities intact, were transferred by the NHS to Google. Worse still, given the scope of the project uncovered by freedom of information requests, what Google and the NHS planned to do was quite a bit wider than their public statements indicated. Perhaps most troubling, however, are the unanswered questions. As Powles and Hodson <a href=\"https:\/\/link.springer.com\/article\/10.1007\/s12553-017-0179-1\">write<\/a>, \u201cWhy DeepMind, an artificial intelligence company wholly owned by data mining and advertising giant Google, was a good choice to build an app that functions primarily as a data-integrating user interface, has never been adequately explained by either DeepMind or Royal Free.\u201d<\/p>\n<h2>The NHS broke privacy laws and Google apologises<\/h2>\n<p>When this article was made public, neither the NHS nor Google\u2019s DeepMind admitted any wrong-doing. As <em>BBC News<\/em> <a href=\"http:\/\/www.bbc.com\/news\/technology-40483202\">reports<\/a>, \u201cAt the time, Google DeepMind said the report had \u2018major errors\u2019 that misrepresented the way it and the Royal Free had used data.\u201d Later, Dominic King, DeepMind&#8217;s clinical lead on health, and Mustafa Suleyman, its co-founder, repented. &#8220;We underestimated the complexity of the NHS and of the rules around patient data\u201d, they <a href=\"http:\/\/www.bbc.com\/news\/technology-40483202\">said<\/a> in a statement quoted by the <em>BBC<\/em>, \u201cas well as the potential fears about a well-known tech company working in health\u2026 We got that wrong, and we need to do better&#8221;. For its part, the Free Trust <a href=\"http:\/\/www.bbc.com\/news\/technology-40483202\">indicated<\/a> that it accepted \u201cthe ICO&#8217;s findings and have already made good progress to address the areas where they have concerns&#8221;. But is that enough to satisfy those concerned about data security and privacy?<\/p>\n<p><iframe title=\"DeepMind Health - What Patients Want From Tech: Patient Engagement Events 2017\" width=\"800\" height=\"450\" src=\"https:\/\/www.youtube.com\/embed\/WCjBXEjm4Cg?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen><\/iframe><\/p>\n<p>DeepMind says that it\u2019s now committed to including patients and the public in the process. And as Suleyman <a href=\"https:\/\/www.cnbc.com\/2017\/07\/03\/google-deepmind-nhs-deal-health-data-illegal-ico-says.html\">sees it<\/a>, &#8220;This is an amazing opportunity for us to prove what we have always believed: that if we get the ethics, accountability and engagement right, then new technology systems can have an incredible positive social impact.\u201d Perhaps this is a historic moment for both patient care and privacy. Time will tell.<\/p>\n<p>If Google\u2019s success is confirmed, it\u2019s a major step forward for patient care, for sure. And shorter stays in hospital, better treatment, and longer, healthier lives are something we all want. But without robust safeguards in place, advances in AI healthcare may threaten our privacy as they save lives. And although Google\u2019s corporate motto is \u201c<a href=\"https:\/\/en.wikipedia.org\/wiki\/Don%27t_be_evil\">Don\u2019t be evil<\/a>\u201d, trusting business to self-regulate is probably unwise.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Google Brain uses patient data to predict outcomes and help care providers Was the project a huge success? We\u2019ll soon know DeepMind processed data without consent from any of the patients The NHS broke privacy laws and Google apologises For hospitals, getting patient care right is always critical. And to better assess a patient\u2019s needs, [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":45427,"parent":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_coblocks_attr":"","_coblocks_dimensions":"","_coblocks_responsive_height":"","_coblocks_accordion_ie_support":"","footnotes":""},"categories":[2872],"tags":[4379],"article-type":[],"trends":[5472],"class_list":["post-57931","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-healthcare","tag-predictive-analytics","trends-big-data-en"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.5 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Google Brain might save lives, but it threatens privacy at the same time. 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