{"id":17309,"date":"2022-11-29T13:22:49","date_gmt":"2022-11-29T18:22:49","guid":{"rendered":"https:\/\/d3.harvard.edu\/platform-digit\/?post_type=hck-submission&#038;p=17309"},"modified":"2022-11-29T13:23:43","modified_gmt":"2022-11-29T18:23:43","slug":"sexyface-and-recognizing-refugees-dr-vivienne-mings-journey-of-using-ai-for-good","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-digit\/submission\/sexyface-and-recognizing-refugees-dr-vivienne-mings-journey-of-using-ai-for-good\/","title":{"rendered":"SexyFace and Recognizing Refugees \u2013 Dr. Vivienne Ming\u2019s Journey of Using AI for Good"},"content":{"rendered":"\n\n\n<p>Dr. Vivienne Ming is one of the most inspiring scientists I have had the privilege of listening to in the Bay Area when I was a student at UC Berkeley. A theoretical neuroscientist \u2013 or as she would say in her talks, a \u201cmad scientist\u201d by profession, she has worked on a range of devices, applications, programs, and pieces of content in a remarkable journey that has intersected her personal journey with the limits of technology as well as its implications around her.<\/p>\n\n\n\n<p>One of her programs \u2013 SexyFace, started off as a program where people would select faces that they find attractive \u2013 within a few clicks, the program could identify the kinds of people that someone found attractive; it was free to play, but priced to get a recommendation of someone you found pretty. The underlying mechanism was a deep neural network that learnt a language of faces, understood players\u2019 preferences and more. However, the underlying \u2018deep density component model\u2019 that was developed for this program could go beyond just identifying sexy (a category) and be applied to recognizing facial expressions and more. Dr. Ming decided that her technology could be applied to something much more important.<\/p>\n\n\n\n<p>The UN (as of when Dr. Ming worked on this project in the late 2000s \/ early 2010s) had a book with over a million photographs of orphaned refugees worldwide. Dr. Ming\u2019s model learnt from people playing SexyFace, and once trained, was applied to try to reunite orphans with their families by having people selecting between pictures on what their lost, loved ones looked like. A few iterations of playing the game later, the AI would be able to point out the lost kids to families and a process to reunite them could be started. The company had not even set out to do this \u2013 while Dr. Ming always intended to use SexyFace for better purposes than dating applications, she was more focused on helping students learn better by creating a new form of interactive learning and testing that replaced the SATs and GREs. The refugee application came from a connection at Ericsson, who connected Dr. Ming to <strong><em>Technology for Good<\/em><\/strong> and the<strong> <em>Refugees United <\/em><\/strong>campaigns run by the UN.<\/p>\n\n\n\n<p>It is worth noting how monumental the effort put in by Dr. Ming was in changing refugee relocation \u2013 before the application was put forth on tablets to people, recognition would usually be done by searching physical books, page after page, hoping not to miss the crucial picture of your loved one as you scrolled past millions.<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><a href=\"https:\/\/d3.harvard.edu\/platform-digit\/wp-content\/uploads\/sites\/2\/2022\/11\/SexyFace.website-1-.png\"><img loading=\"lazy\" decoding=\"async\" width=\"1000\" height=\"750\" src=\"https:\/\/d3.harvard.edu\/platform-digit\/wp-content\/uploads\/sites\/2\/2022\/11\/SexyFace.website-1-.png\" alt=\"\" class=\"wp-image-17313\" srcset=\"https:\/\/d3.harvard.edu\/platform-digit\/wp-content\/uploads\/sites\/2\/2022\/11\/SexyFace.website-1-.png 1000w, https:\/\/d3.harvard.edu\/platform-digit\/wp-content\/uploads\/sites\/2\/2022\/11\/SexyFace.website-1--300x225.png 300w, https:\/\/d3.harvard.edu\/platform-digit\/wp-content\/uploads\/sites\/2\/2022\/11\/SexyFace.website-1--768x576.png 768w, https:\/\/d3.harvard.edu\/platform-digit\/wp-content\/uploads\/sites\/2\/2022\/11\/SexyFace.website-1--600x450.png 600w\" sizes=\"auto, (max-width: 1000px) 100vw, 1000px\" \/><\/a><figcaption>Source: Socos Labs Website<\/figcaption><\/figure>\n\n\n\n<p>The tragedy of this story is in its clash with capitalism if I may say. Dr. Ming was running an unfunded startup trying to prove to VCs that the app could be used for education related purposes, earning fixed revenue, and was pushed to say no to working with the Ericsson team. By the time other ways of monetizing the technology had failed and she returned, the moment had passed and while Ericsson saved many lives, the impact was lesser than it could have been. She had been doing this work under a company named Augniscient, which according to Pitchbook was sold to a company named Rabbit. When clicking through, I discovered that Rabbit, a video chat application to help share experiences, had gone out of business in 2019, so I assume that the company failed to make a dent into other applications of Dr. Ming\u2019s technology. If one was to diagnose what could have been done better from a business perspective, the technology could have been monetized by being licensed to companies lacking technical talent for various use cases (beyond the realm of dating) while also continuing to use the core trained model for refugee recognition applications.<\/p>\n\n\n\n<p>To me, Dr. Ming\u2019s journey is inspirational \u2013 she had the courage to push an AI application for good, utilize deep neural networks in one way externally (by having people play SexyFace) to train her models and deploy them for other refugee \/ humanitarian use cases that pose the most challenging issues of our times. The GTM here was despite not being entirely monetizable, a genius approach, and opens the realm of questioning: \u201cAre there other ways of training models for our application by gathering data outside of the particular application we are trying to aim for\u201d \u2013 something that was extremely unique ten years ago.<\/p>\n\n\n\n<p>Dr. Ming\u2019s advocacy also extends to another problem with AI \u2013 \u201cdo the benefits of AI flow disproportionately to the rich?\u201d Dr. Ming argues in her work that AI should be thought of as a human right, in the way we view vaccines, rather than to enhance SAT scores by 2 points or makes a wristband buzz when an Amazon employee packages something wrong. Dr. Ming has responsibly scrapped several projects where her AI has shown signs of bias.<\/p>\n\n\n\n<p>Sources:<\/p>\n\n\n\n<p><a href=\"https:\/\/www.socos.org\/sexyface-part-1\/\">https:\/\/www.socos.org\/sexyface-part-1\/<\/a><\/p>\n\n\n\n<p><a href=\"https:\/\/www.socos.org\/sexyface-part-2\/\">https:\/\/www.socos.org\/sexyface-part-2\/<\/a><\/p>\n\n\n\n<p><a href=\"https:\/\/www.theguardian.com\/technology\/2018\/dec\/07\/technologist-vivienne-ming-ai-inequality-silicon-valley\">https:\/\/www.theguardian.com\/technology\/2018\/dec\/07\/technologist-vivienne-ming-ai-inequality-silicon-valley<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Dr. Ming trained an AI model to recognize humans a player found attractive &#8211; but rather than apply it to dating, used it for lost refugee reconnection &amp; education. <\/p>\n","protected":false},"author":19343,"featured_media":17318,"comment_status":"open","ping_status":"closed","template":"","categories":[],"class_list":["post-17309","hck-submission","type-hck-submission","status-publish","has-post-thumbnail","hentry"],"connected_submission_link":"https:\/\/d3.harvard.edu\/platform-digit\/assignment\/machine-learning-3\/","yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.5 - 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