If you thought Seema Aunty from ‘Indian Matchmaking’ was the ideal choice for sorting out your love life, think again. Online dating apps like Tinder, Bumble, and Hinge are increasingly becoming a popular choice, with AI and ML playing the modern-day matchmaker. 

Besides, for those open to exploring other options, AI romantic partners are now a real bet, and the concept of dating and hooking up is undergoing a sea change. These are available on platforms such as Romantic AI, Talkie Soulful AI, Replika, Anima: AI Boyfriend, iGirl: AI Girlfriend, and CrushOn.AI.

“Digital addiction is spiralling out of control as people attempt to combat loneliness by falling in love with AI girlfriends,” said Gregory Jantz, a mental health expert who specialises in technology addiction, anxiety, and depression. 

Further, he said the number of people who would rather be intimate with an AI object than a real human is alarmingly high. With generative AI taking centre stage in 2023, we have seen a burgeoning rise of apparent “romantic” AI chatbots, bringing Spike Jonze’s ‘Her’ to life. 

Now, you can either have your romantic AI chatbots or use models like ChatGPT to craft romantic texts for your human partner. So, startups specialising in AI-generated messages for dating are also experiencing high demand. This has gone to the extent that a Russian man, who created a chatbot to interact with over 5,000 women on Tinder, is now engaged to one of them.

Even OpenAI’s GPT Store was flooded with numerous romantic bots breaching OpenAI’s guidelines. According to a recent report by Quartz, the search for ‘girlfriend’ yields numerous AI chatbots, such as ‘Your AI girlfriend, Tsu’, allowing users to customise virtual romantic partners. 

Echoing similar thoughts is a research by Mozilla Firefox, which showed that the rise of romantic AI chatbots has caused major privacy issues. Out of 11 chatbots tested, 10 failed to meet basic security standards outlined by Mozilla, lacking features like strong passwords and proper handling of security flaws.

Despite their empathetic marketing, these chatbots sell the cure for loneliness. However, they prioritise data collection over user privacy. Moreover, they may share or sell personal data without clear user consent. 

Even worse is when users blindly follow what the chatbots suggest, like in the case where a chatbot allegedly persuaded a man to take his own life. Similarly, the Replika AI chatbot reportedly encouraged a man to attempt an assassination on the Queen. 

Dating Apps, Anyone? 

Dating apps—the likes of Tinder, Bumble, and Hinge—traditionally reliant on basic proximity-based algorithms, have evolved with AI integration. They analyse user data to offer personalised matches. Machine learning algorithms decode user behaviour, fueling recommender systems that suggest compatible matches through collaborative and content-based filtering techniques.

NLP enables chatbots to understand and respond to natural language, while sentiment analysis assesses emotional tones in conversations. Facial recognition technology adds a layer of security by verifying identities and, controversially, claims to analyse compatibility based on facial features.

“The problem with these early matching systems is that they assumed users knew precisely what they desired in a partner. However, people’s stated preferences for an ideal mate do not always align with what they find attractive in person,” believes Professor Liesel Sharabi of Arizona State University. 

So, when it comes to finding a partner, it’s no surprise that dating apps leverage your preferences, likes, and dislikes to recommend the most-suitable match.

In February, Bumble introduced a new AI tool, the Deception Detector, to tackle spam, scams, and fake profiles. It blocked 95% of such accounts during testing and reduced reports by 45%. This initiative follows the 2019 launch of the Private Detector, an AI feature that blurs explicit images, later made available as open-source code by Bumble.

“Our users are looking for authentic connections, and I believe AI also has exciting potential related to safety,” Bumble CEO Lidiane Jones told BBC recently. Similarly, in Bumble’s secondary app, Bumble For Friends, one can create AI-generated icebreaker suggestions to start conversations. 

The app rose to fame because of its women-centric approach, differentiating it from the rest.

Meanwhile, Hinge, born in 2012 and “designed to be deleted”, focuses on long-term relationships. It employs the Gale-Shapley algorithm to suggest compatible matches. It prioritises safe, ethical, and responsible AI use, focusing on eliminating the casual dating culture created by Tinder and Pure Dating. 

The Nobel prize-winning Gale-Shapley algorithm solves the problem of creating stable matches between two groups when both sides prefer some partners over others. 

The platform uses AI to assist users in finding compatible matches without turning the dating experience into a game. Currently, AI enhances the app’s features, with future exploration into integrating generative AI. Recently, CEO Justin McLeod told BBC that AI is “really going to change the game” for dating apps. 

The app’s recommendation algorithms suggest potential matches based on user preferences and past interactions. Additionally, AI helps identify and address potential risks such as scams and harassment to maintain a safe community environment—this is similar to Bumble’s approach. 

While Hinge has not yet dived into generative AI, it plans to do so in the coming months. 

Now, moving on to the OG player in the space—Tinder. Founded in 2012 to have fun and make dating casual, it employs VecTec, an ML algorithm paired with AI to tailor personalised recommendations. Swipes are mapped onto vectors representing user traits like hobbies and education, facilitating matches when commonalities are detected. 

Another algorithm, Word2Vec, acts as Tinder’s linguist, analysing communication styles. By grouping similar swipes based on language, the system enhances match recommendations. ML aids in automatically screening offensive messages improving safety, yet challenges arise in discerning context and user sensitivities. 

Additionally, Tinder’s ‘Smart Photos’ feature, driven by the Epsilon Greedy algorithm in reinforcement learning, optimises profile picture selection based on user responses, increasing match likelihood by 12%. 

On the one hand, while we have romantic generative AI chatbots creating a ruckus while providing temporary relief, on the other hand, we have dating apps experimenting with AI and ML to find you meaningful matches. It would be interesting to see how the two spectrums evolve, especially when dating apps switch to generative AI.