Authenticity in the Age of Algorithms

In a world increasingly shaped by algorithms, curating our playlists, predicting our purchases, and filtering our feeds, the concept of authenticity has never felt more urgent or elusive. We crave realness, yet we move through digital spaces designed to optimise and smooth every interaction.

How can authenticity thrive in this landscape? Get inspiration and practical tips from this post by our Principal Designer Juha Kronqvist.

This blog post is part of our series on the Pathways in the Intelligent Age guide.

A couple of days ago, I came across an Instagram post by Pitchfork, an independent music media outlet. A musician was asked to name a “10 out of 10” album, a difficult task for any professional musician. Interestingly, he proposed Chirgilchin, a Tuvan band that I saw perform live over two decades ago. Their music is hauntingly beautiful: a blend of Mongolian throat singing, traditional folk, and, somehow, bluegrass. Listening to them transported me to windswept steppes, horseback nomads, and the eerie call of hunting eagles. What struck me wasn't just the music, but the authenticity of the experience: completely otherworldly, deeply rooted, and unlike anything I'd typically hear.

This kind of discovery feels almost impossible today. My Spotify recommendations echo a feedback loop of safe, familiar, and algorithmically flattened soundscapes. The experience made me think: What does authenticity mean in the age of algorithms? How can we design for it, and does it make business sense to do so?

1. Authenticity as a Strategic Differentiator

In a saturated world of seamless, optimised digital experiences, authenticity has become a rare currency. It's more than a brand trait, it's a competitive advantage. Consumers, overwhelmed by choice and hyper-curation, are gravitating toward things that feel real, grounded, and human. Brands that can cultivate and deliver this sense of "realness" win trust, loyalty, and can command a price premium.

Research in consumer psychology reveals that authenticity fosters emotional connection, trust, and overall satisfaction. Business strategists such as Pine and Gilmore have long argued that authenticity is a dominant purchase criterion in the experience economy. People don't just buy products or services—they buy stories, values, and meaning. In a sense, what we design isn't just a service interface or a customer journey; it's a system of integrity.

2. The Spectrum of Algorithmic Influence

Authenticity is not a binary trait of yes’s and no’s. It's shaped and mediated by the technologies we use and today, it's particularly algorithms. We can think of experiences as falling along an algorithmic spectrum:

No Algorithms: Analogue, slow, human-led. Think: off-grid cabin, handwritten notes, a live acoustic gig.
Visible Algorithms: Where personalisation is explicit. Spotify playlists, Netflix recommendations, Instagram ads.
Invisible Algorithms: Quiet, backend automation shaping decisions without visible cues. Insurance pricing, AI-driven UX flows, dynamic content delivery.

Each zone presents a different design challenge. In algorithm-free spaces, authenticity stems from intentionality and presence. In visible algorithmic spaces, it's about transparency and alignment. In invisible systems, trust and explainability become essential.

3. Authenticity is Felt, not Rationalised

As we move from visible to invisible algorithmic systems, the subtle cues that foster trust become even more vital. Users don’t necessarily need to see every line of code or logic tree, but they need to feel that the system understands them and respects them.

What people look for isn’t perfection. It’s coherence. It’s the sense that what they’re seeing or experiencing makes sense in relation to their expectations and values. When personalised recommendation feels surprisingly spot-on, not because it's predictive, but because it aligns with a deeper need or mood, users respond with appreciation. That’s transparency in action. Not just showing your algorithmic hand, but designing so the result feels intuitively explainable.

Equally important is a sense of agency. Do I have the ability to influence what I see next, or am I being pulled down a path I didn’t choose? Authenticity often arises not from getting exactly what you want, but from knowing that you had a role in shaping what emerged. And when that’s missing, when the experience feels one-sided or overly engineered, users recoil. They may not articulate it in those terms, but the feeling is unmistakable: this isn’t for me.

Authentic experiences, then, aren't simply those that mirror our preferences. They are ones that feel fair, open, and attuned to the human need to be seen and heard, not simply sorted and served.

4. Design Tactics

No Algorithms

Examples: Boutique hotel, live concert, analogue workshop

In algorithm-free environments, authenticity is created through presence, tactility, and the richness of human interaction. These experiences thrive on story, rootedness, and intentionality and providing space for reflection and connection. Design strategies include highlighting local culture, using hand-crafted materials, or embedding rituals that make the experience feel unique and unrepeatable.

Real-world example: A retreat in the Finnish archipelago that offers no Wi-Fi and asks guests to surrender their phones upon arrival. Instead of digital prompts, the environment nudges guests into deep rest, analogue play, and shared storytelling. The result feels radically real in a way that tech-enhanced environments rarely do.

Visible Algorithms

Examples: Spotify, Netflix, recipe recommendations

When algorithms are visible, the design task is to maintain a sense of control and transparency. Users should be able to see why they are receiving a certain suggestion, and ideally, influence it. Providing feedback loops, customisation settings, and explanations in plain language all help reinforce trust.

Real-world example: Duolingo dynamically adapts its language courses to each user’s progress. It surfaces "Because you struggled with verbs" explanations and allows users to adjust practice areas, giving them visible and understandable control over their learning journey.

Invisible Algorithms

Examples: Insurance quotes, delivery ETAs, credit scoring systems

Invisible algorithms require the most care. Because users can’t see them working, authenticity hinges on clarity, fairness, and empathy. Communicating key decisions in clear and understandable terms, allowing for correction or appeal, and ensuring that automated logic aligns with human values are all critical to preserving trust.

Real-world example: A bank that uses AI to determine loan eligibility introduces a plain-language explanation interface, allowing customers to see which factors influenced their score and what they can change to improve it. By making a complex system intelligible, the bank earns credibility rather than suspicion.

5. Pitfalls: When Algorithms Undermine Authenticity

Yet, as we deepen our reliance on algorithmic tools, the pursuit of authenticity encounters some sharp edges. It’s easy to forget that while algorithms are good at predicting behaviour, they’re less adept at capturing nuance. What starts as personalisation can quickly become a narrow corridor of sameness and one that quietly edits out the unexpected.

Over time, this overfitting can feel like a form of confinement. We get more of what we’ve already chosen, reinforcing a static self-image. The thrill of stumbling upon the unexpected, like discovering Chirgilchin through a serendipitous live gig, fades in a world where every decision is anticipated.

Even well-intentioned systems can misstep. When they rely on shallow profiling or extrapolate too confidently from past behaviour, the results often ring hollow. Worse, when users can't tell why they’re being shown certain content, or worse, feel manipulated by it, the experience starts to feel disingenuous. Opacity doesn’t just obscure the process; it undermines trust.

And when everything starts to look and sound the same, we lose not just variety, but risk our own identities. Authenticity thrives on difference, context, and contradiction. If the design irons out all the wrinkles, we’re left with an experience that might be efficient, but ultimately, forgettable.

6. Designing for Authentic Experiences

Designing for authentic experiences in the age of algorithms isn’t about rejecting technology, but rather about humanising it. Here’s how:

Make algorithms visible where it matters

When people know that personalisation is happening, they’re more likely to trust it, especially when they understand the logic behind it. Transparency creates clarity, and clarity invites agency. A visible algorithm signals, “You’re still in control here.”

Support user reflection and choice

Great experiences don’t just give users more of what they want; they invite users to reflect on what they could want. Offering room to diverge, reset, or explore alternative paths fosters a sense of authorship. Design for forks in the road, not dead ends.

Tell true stories through action

Authenticity isn’t just communicated in copy; it’s proven through consistency between what a service says and what it does. If a brand claims to be ethical, it must embed that in its policies, pricing, and partnerships. The story must unfold across every touchpoint. It’s not about marketing. It’s about alignment.

Honour surprise and delight

Not all experiences should be expected. Surprise can be a form of truth, especially when it resonates emotionally. Injecting occasional novelty or subtle friction can refresh a stale journey and remind users that the system sees them as dynamic, not predictable.

Embed values, not just logic

Authentic systems are shaped by more than user data; they’re built on principles. Designers should ask: Who benefits from this recommendation? Is it fair? Is it kind? By encoding empathy and ethics into systems, we align technological power with human priorities.

Restrict access or findability

Authenticity sometimes means resisting scale. Consider limiting access, participation, or algorithmic reach to protect the integrity of an experience. Make it harder to game. Design systems where not everything is monetised, sponsored, or promotable. This preserves the trust that something is there because it matters, not because it has paid its way.

"Algorithms are good at giving us more of what we know. But authenticity often lives in what we don’t expect—in the offbeat, the unoptimised, the human detour."

7. The Real Human Advantage

That old Chirgilchin gig? It was an unrepeatable moment. No app nudged me toward it. It happened because I followed my curiosity, because a friend dragged me along, and because I didn't know what to expect.

Algorithms are good at giving us more of what we know. But authenticity often lives in what we don’t expect: in the offbeat, the unoptimised, the human detour.

As designers and developers, we have an opportunity to create space for those moments. Whether it’s through transparency, serendipity, or intentional friction, we can shape systems that don’t just feel smart, but feel true. And in a world of ever-narrowing feeds, that might be the boldest design move we can make.

PS. Support authentic music by listening to or buying the Chirgilchin album on Bandcamp.

Picture credit: Julia Volk