Dating apps have transformed how people meet romantic partners. But they seem to be falling out of favour.
The data indicates that last year, the top four dating applications in the UK collectively experienced a loss of more than a million users.
And research my colleague and I worked on suggested that this is because people have become frustrated and bored with digital matchmaking.
The irritation typically stems from the thoughtless actions of other individuals using the same application.
And the boredom appears to stem from a growing belief that the AI used by these apps seems to prioritise short-term engagement metrics over meaningful connections .
This represents a considerable change from previous online practices. dating websites These platforms stood out for their increased transparency in fostering genuine connections. This frequently involved providing thorough responses to compatibility questionnaires or personality tests.
For instance, OkCupid.com (established in 2004) presented users with numerous multiple-choice questions. The platform extended this approach by having individuals indicate which answers they desired their potential matches to provide for these very inquiries.
On the contrary, modern dating applications now heavily depend on opaque artificial intelligence systems. These algorithms appear to focus more on straightforward interaction statistics such as swipe counts, texting frequencies, and time spent within the app instead of fostering true compatibility.
The outcome frequently includes a series of ambiguous and transient connections that fail to develop into significant relationships. Moreover, the business strategy behind modern dating applications—offering enhanced exposure and contact with potential matches for a fee—creates a difficult atmosphere for numerous users seeking suitable partners.
As a result, numerous users encounter feelings of discontentment that unfold through four distinct phases.
It begins with what I call a “boredom cycle”. General boredom prompts many daters to use the app in the first place, but resulting conversations often turn into uninspired and lacklustre exchanges. This adds to the boredom, which then spreads and grows throughout the entire dating app network.
Following this, there’s an overarching feeling of letdown, as individuals grow indifferent towards frequent "ghosting" (suddenly ceasing all contact) and "flaking" (canceling plans at short notice). This is compounded by routine, uneventful conversations that fail to result in genuine meetings.
This culminates in a third phase known as "algorithmic cynicism." Here, users grow more doubtful about the dating app algorithms, believing that these systems' main purpose is to prompt the buying of specific features instead of fostering genuine relationships.
Ultimately, when communication fatigue sets in, users perform the actions of swiping and messaging without much hope for finding superior options. This emptiness often leads them to abandon these platforms entirely.
Swipe on, swipe off
Studies have indicated that the surge in online dating adoption amongst millennials aligned with their early excitement regarding social media. However, this zeal has since waned.
Users of social media platforms have become more wary and watchful regarding the dangers of false information, frauds, and inappropriate material.
Despite all of this, people still seek connections through dating platforms – whether for casual or long-term partnerships. So perhaps the issue is not with digital dating itself, but with how the industry uses AI. And an alternative is possible.
In related research on human-AI joint decision-making, my colleagues and I found that when people interact with an imperfect AI system, but also receive clear feedback about the their own behaviour patterns and how the AI responds, they can help to correct errors.
The study concentrated on financial choices; however, dating applications might adopt a comparable approach by transparently offering users personalized insights into how AI algorithms react to their activities. No current dating app implements this feature.
Rather than solely relying on user-adjusted settings like age, location, and ethnicity, these platforms utilize AI to generate "revealed preferences." This process involves analyzing how individuals interact with the application through actions such as swipes and messages. It appears that these inferred preferences significantly shape the type of profile recommendations provided by the app's artificial intelligence.
For example, even if someone says they are keen to date people across a wide age range, the app may still end up recommending profiles of a narrower age group, because the user has tended to swipe right on those in the past. Because of this, users have expressed concerns that the AI could be adding unwanted limitations to their potential dating pool.
Through the Eyes of Artificial Intelligence
Certainly, our study indicates that a pessimistic perspective toward dating app algorithms plays a crucial role in turning what could be an exhilarating experience of discovering a romantic match into an incredibly tedious process.
By addressing this concern, educating daters about how AI processes their usage within the app—such as swiping patterns, matching preferences, and date interactions—could serve as an appealing feature. Allowing users more control over adjusting additional filters beyond just demographic details, like aligning with specific values and personal interests, might also boost engagement significantly.
This would revert to the clearer matchmaking methods used by older dating sites, yet incorporate the advantages of modern technological advancements.
Our research suggests that as dating app users grow ever more discerning, they will demand greater transparency and an improved overall dating app experience. The industry’s future may ultimately depend on whether companies can shift focus from impersonal engagement metrics to fostering authentic connections.
And platforms which embrace transparency and empower users could make many fall in love with dating apps all over again.
Anh Luong is an Assistant Professor of Business Analytics at the Warwick Business School, part of the University of Warwick, UK. This article is republished from The Conversation under a Creative Commons license. Read the original article
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