AI is the new frontier for dating apps. Here’s proof [Updated]

Filtering fake accounts and inappropriate content. In a world where 72% of dating app users block other people’s profiles for misbehavior and offensive content, more applications turn to artificial intelligence to curb harassment. An example of this is Tinder’s reporting system that detects improper language and asks users how they feel about it. An algorithm developed by a team of researchers from the University of Warwick flags bot accounts with 99% accuracy based on their IP addresses, messages, and stolen images. And a popular live streaming dating app uses machine learning to spot inappropriate content and block users who spread it.

Coming up with personalized recommendations. Sean Rad, Tinder CEO, defines artificial intelligence as a smart filter that knows what people are interested in — and delivers content that best matches their interests. Besides finding users with similar hobbies and life goals, Lara, Match.com’s chatbot that works in sync with Google Assistant, suggests ideal date locations in your area. Another example comes from eHarmony, whose AI studies user behavior to figure out the best time to email each other.

Correcting grammar and spelling mistakes. You may spend weeks choosing perfect photos for your Tinder profile and still get 14% fewer responses just because you’ve made two spelling mistakes in the About Me section! In fact, proper grammar ranks higher on your date’s wishlist than good teeth and self-confidence! To fix typos and grammatical errors in your profile and messages, you can use AI-powered tools like Grammarly’s Mobile Keyboard, which also conducts sentiment analysis to make sure you sound friendly and respectful.

Even it were not for the pandemic, our lives have become more digital, and the amount of data we consume daily continues to grow

Younger people prefer to focus on their education and careers, meaning they have less time for in-person interactions with peers

Our well-being has skyrocketed in the past 20 years — and wealthy, educated individuals tend to socialize less

Dating apps reportedly lead to stronger marriages and higher marital satisfaction

Come up with a unique idea. While making a dating app with artificial intelligence features will certainly give you a competitive edge over your rivals, you still have to bring something new to the table. Tastebuds, for example, matches people based on their musical interests. Applications like Ship and Chorus allow your friends to swipe profiles for you until they find a perfect match. And some apps go totally niche, focussing on LGBTQ+ and non-binary people only.

Avoid feature creep. Although you might be tempted to build a dating app containing all the fancy AI features we mentioned earlier, you should take one step at a time and launch an application that meets the very basic user needs while highlighting your product’s unique selling point. This “less is more” approach would help you better manage your team and budget and release the application faster.

Collect heaps of training data. To create an AI dating app that delivers on its promise, you need training data. Otherwise, your custom machine learning algorithms won’t be able to recognize patterns in user data, make intelligent predictions, and improve their performance over time. Unfortunately, it might be hard to obtain training data for a matching algorithm unless you consider adding AI capabilities to an existing app. Some dating app developers tackle this problem by running fake accounts on popular dating applications and artificially expanding the size of training datasets. Next, you need to beta-test the application with different focus groups and tweak the algorithms based on user feedback.

Make use of third-party AI software. Here at ITRex, we profess the technology-agnostic, vendor-neutral approach to software engineering. We also help our clients keep AI development costs down. That’s why we recommend that you utilize as many off-the-shelf frameworks, libraries, and SDKs as possible. And if you find a suitable SaaS, self-hosted, or open-source facial recognition service to power your intelligent profile image suggestion feature, just go for it! And we’ll be more than happy to assist you with software customization and integration

Eradicate bias and superficial judgment. Just like other AI-powered applications, dating apps are prone to bias. An example of this could be a dating app showing you only profiles of Caucasian partners if you’ve had similar matches in the past or downvoting your profile if you’re a person of color. One way to address this problem could be using representative training data, evaluating algorithm performance in different user groups, and adding an intermediary explainable AI (XAI) layer on top of your algorithms. And it goes without saying that algorithms that slide into users’ direct messages and profile data should be 100% transparent and never leak personal information (let alone sell it to advertising companies).