{"id":36090,"date":"2018-11-13T21:46:21","date_gmt":"2018-11-14T02:46:21","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-rctom\/submission\/is-machine-learning-the-new-wingman\/"},"modified":"2018-11-13T21:46:21","modified_gmt":"2018-11-14T02:46:21","slug":"is-machine-learning-the-new-wingman","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/is-machine-learning-the-new-wingman\/","title":{"rendered":"Is machine learning the new wingman?"},"content":{"rendered":"

Match Group and the Dating Scene\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 <\/strong><\/p>\n

Today, 4% of the global population, utilize online dating for their matchmaking needs. This equates to approximately 291.8 million people.<\/p>\n

Match Group is the \u201cworld\u2019s leading provider of dating products with a global footprint of marque dating assets [1]\u201d. The Match Group operates a portfolio of dating brands, including Tinder<\/em>, Match.com<\/em>, PlentyOfFish<\/em>, Meetic<\/em>, OkCupid<\/em>, OurTime<\/em>, and Pairs<\/em>, each designed to increase its users\u2019 likelihood of finding a meaningful romantic connection. The group provides tailored dating products in 42 languages across more than 190 countries to over approximately 8.1 million subscribers each year [1]. For most consumers, however, the experience can often become never ending swiping sessions [6] filled with \u201cmismatches\u201d (i.e., profile offerings that are not in line with the single user\u2019s dating preferences).<\/p>\n

Artificial intelligence is progressively entering the dating world. Match Group\u2019s size allows the company \u201cto access an unprecedented amount of consumer dating preference data\u201d [5] (e.g., location, age, gender, sexual preferences, online purchasing history and even music playlists), in which the company has decided to leverage by investing heavily in artificial intelligence and machine learning as a part of its business model. \u00a0According to Greg Blatt, former Chairman and CEO of Match Group, \u201cArtificial intelligence is just starting to scratch the surface, but we\u2019re making a huge investment in it\u201d [2]. The investment is aimed to help the company remain the industry leader of the incredibly competitive online dating market. To improve user experience, Match Group has embarked on a journey to implement machine learning to help you find your perfect match.<\/p>\n

How Match Group Uses Artificial Intelligence:<\/strong><\/p>\n

Match Group\u2019s namesake brand, Match.com<\/em>, has introduced Lara<\/em>, \u201dthe first artificial intelligence dating assistant that can help website subscribers optimize their dating profile to attract potential desirable matches\u201d [3]. The company partnered with Google to develop this dynamic service to help singles looking for love. Built with deep artificial intelligence and keyword recognition technologies, Lara is created as a personal wingwoman who can understand your intentions and help you through your dating journey[3]. The chatbot will select a unique member profile based on your search preferences, suggest ideal locations where you and your date can get to know each other based on shared interests and give dating advice to keep your first date jitters at bay. Lara learns from her interactions based on user feedback and will suggest more relevant date locations as well as provide more unique dating advice by leveraging her prior interactions[3].<\/p>\n

Looking Ahead<\/strong><\/p>\n

Looking forward, Tinder has begun to roll out a feature called \u201csuper likeable\u201d. Tinder has leveraged the latest advancements in machine learning and natural language processing to generate behavior data, learn your \u201ctype\u201d of partner and offer a more personalized recommendation. However, according to artificial intelligence consultant, Marina Pavlovic Rivas, this comes with its fair share of risks. \u201cArtificial intelligence is not neutral. It feeds off the information we give it, which can include biases that the algorithm will then generalize. In a society ruled by algorithms, artificial intelligence could, for example, deduce socio-economic status from a ZIP code, and propose only profiles coming from the same background as its users. The same could happen for skin color.\u201d [4]. This could be a societal issue at large and could expose any one of the Match Group\u2019s portfolio companies to legal risk.<\/p>\n

Further, Sean Radd, CEO and Founder of Tinder expects machine learning to help users escape information overload. According to Radd, \u201cFive years from now instead of scrolling, searching, swiping I think these devices will be intelligent enough to just give you the answer through a Siri-style interface\u201d[6]. This adjustment would change the act of swiping right or left as we\u2019ve come to know it and essentially create an interactive matchmaker that can be carried anywhere in your pocket.<\/p>\n

Recommendations<\/strong>:<\/p>\n

With these innovations in dating technology, Match Group needs to remember the societal implications of their algorithms. The company\u2019s platforms are becoming increasingly aware of the impact they have on dating discrimination. In the short term, I recommend they remove certain assumptions from their data sets (e.g., zip codes). This could combat the likelihood of associating certain inputs with a negative connotation. Further, to deepen its innovative strategy, Match Group should increasingly use face recognition to identify if an uploaded profile picture would be seen as attractive by another user. This will allow for more positive matches and an overall beneficial user experience, further increasing the company\u2019s competitive advantage.<\/p>\n

What\u2019s Next?<\/strong><\/p>\n

The question remains \u2013 how do you program algorithms to disregard biased consumer data that could potentially negatively impact both your consumers and society at large? Given such risks, should Match invest more heavily in machine learning? Do we even still need humans to know what the heart truly wants?<\/p>\n

[1] Iac.com. (2018).\u00a0Match Group | IAC<\/em>. [online] Available at: http:\/\/www.iac.com\/brand\/match-group [Accessed 13 Nov. 2018].<\/p>\n

[2 Bary, E. (2018). Tinder Has Big Plans for Artificial Intelligence. [online] Barrons.com. Available at: https:\/\/www.barrons.com\/articles\/tinder-has-big-plans-for-artificial-intelligence-1493850214 [Accessed 13 Nov. 2018].<\/p>\n

[3] Match UK. (2018).\u00a0Match launches UK\u2019s first AI Dating Chatbot, Lara, on the Google Assistant – Match UK<\/em>. [online] Available at: https:\/\/uk.match.com\/pages\/advice\/ai-dating-chatbot-lara [Accessed 13 Nov. 2018].<\/p>\n

[4] Greenacre, M. (2018).\u00a0For Dating Sites, Artificial Intelligence v. The Human Heart<\/em>. [online] Worldcrunch.com. Available at: https:\/\/www.worldcrunch.com\/tech-science\/for-dating-sites-artificial-intelligence-v-the-human-heart [Accessed 13 Nov. 2018].<\/p>\n

[5] The Economist. (2018).\u00a0How the internet has changed dating<\/em>. [online] Available at: https:\/\/www.economist.com\/briefing\/2018\/08\/18\/how-the-internet-has-changed-dating [Accessed 13 Nov. 2018].<\/p>\n

[6] Startupgrind.com. (2018).\u00a0The Future of Dating Is Artificial Intelligence<\/em>. [online] Available at: https:\/\/www.startupgrind.com\/blog\/the-future-of-dating-is-artificial-intelligence\/ [Accessed 13 Nov. 2018].<\/p>\n","protected":false},"excerpt":{"rendered":"

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