Part II — Who Are You? Synthetic Identities and the Disappearance of Certainty Online

Are We Still Talking to Humans?

Part II — Who Are You?

Synthetic identities and the disappearance of certainty online

There is a photograph.

A friendly face. A name. An age seems roughly apparent. There are holiday photographs, opinions, interests and a short biography.

The account occasionally responds to you.

What do you actually know about the person behind it?

Less than ever before.

For most of the history of social media, we have operated with an unspoken assumption:

There is a human being behind the profile.

Perhaps that person uses an old photograph. Perhaps the job title is exaggerated. Perhaps the carefully selected holiday photographs present a rather flattering version of reality.

But there is a person.

Generative AI is making even that basic assumption increasingly unreliable.

A person can now be manufactured

A realistic human face no longer requires a human model.

Neither does a voice.

A biography can be generated. Photographs can be created or altered. Posts can be written automatically. Conversations can be assisted or generated by AI.

And the identity can be changed.

The same operator could present one account as a young professional, another as a retired grandmother and another as someone of a completely different age, sex or nationality.

The relevant concept here is a synthetic persona: a digitally constructed identity that can combine generated images, invented personal information, AI-generated content and automated or human-controlled interaction.

Not every synthetic element makes an account deceptive.

Someone may use an avatar for privacy. A real person may use AI to improve a photograph or write a post. Millions of people legitimately use AI as a tool.

The crucial distinction is not:

Was AI used?

It is:

Is someone deliberately creating a false impression about who — or what — is communicating?

The problem becomes different when the user is a child

For adults, uncertainty about identity can lead to manipulation, fraud or deception.

For children, the stakes can be considerably higher.

A 13-year-old may believe another account belongs to a 14-year-old.

The profile photograph looks right. The language sounds right. They follow the same creators, know the same games and use the same expressions.

But none of those signals now proves that another 14-year-old is sitting at the other end.

An adult pretending to be a child online is not a problem created by AI. Grooming and false identities existed long before generative technology.

What AI changes is the available toolkit.

Convincing images, text and potentially voices can be generated or manipulated. Maintaining a plausible identity can become easier. And the familiar signals people once used to judge who someone might be become less reliable.

The European Commission already recognises grooming and unwanted contact from strangers as significant online risks to minors under the Digital Services Act (DSA).

But age and identity are two different questions.

Knowing that a user is over 18 does not tell us who that user is.

And knowing that an account claims to be 14 does not prove that the person operating it is 14.

Why not simply verify everybody?

At first sight the solution appears obvious:

Make everyone prove their identity.

But that creates another problem.

There are legitimate reasons to use the internet without publishing one's legal identity. Whistleblowers, abuse victims, political dissidents and ordinary citizens may have very good reasons not to make their identity public.

And requiring billions of people to hand identity documents to social-media companies creates its own privacy and security risks.

Europe is already wrestling with this tension.

The European Commission's approach to age verification is deliberately designed around privacy-preserving proof of age. A person could prove, for example, that they are over 18 without revealing their exact age, name or other unnecessary personal information.

That is an important distinction.

We do not necessarily need to know who someone is in order to establish what they are entitled to prove.

Perhaps the same kind of thinking will eventually become relevant to human authenticity.

Not necessarily:

Show me your passport.

But perhaps:

This platform has verified that a natural person controls this account.

That would be a very different proposition.

Platforms are already moving

LinkedIn is particularly interesting because professional identity is central to the platform.

In March 2026, LinkedIn reported that more than 100 million members had added at least one verification to their profile. It has also made workplace verification mandatory for members adding recruiter job titles.

Instagram and Facebook owner Meta takes a somewhat different approach, focusing partly on identifying and labelling AI-generated content.

TikTok likewise requires realistic AI-generated images, audio and video to be labelled in specified circumstances and can automatically attach an AI-generated label when it detects recognised technical credentials.

These are meaningful developments.

But notice what they primarily address:

the content.

Was this photograph generated?

Was this video manipulated?

Was this audio synthetic?

Our emerging problem goes one level deeper.

What about the identity producing all that content?

Content authenticity is not identity authenticity

A synthetic profile could contain a mixture of genuine and artificial material.

A real photograph could be stolen.

A generated photograph could represent a fictional person.

A human could write some posts while AI writes others.

An operator could personally answer important messages while automating routine conversations.

The account might therefore not be purely “human” or purely “AI”.

That binary distinction may already be becoming obsolete.

The more useful questions may be:

Who controls this identity?

Does it represent a real individual?

How much of its interaction is automated?

And is the person interacting with it entitled to know?

Those questions become especially important when trust is involved: friendship, recruitment, dating, financial advice, political discussion — and contact with children.

We used to ask whether the information was real

That question remains important.

But social media are moving into territory in which another question precedes it.

Before asking whether we can trust what somebody tells us, we may increasingly need to ask:

Who is telling us?

And sometimes:

Is there a “who” at all?

The internet has spent decades teaching us not to believe everything we read.

Generative AI presents a different challenge.

We may no longer know who we are reading at all.

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For this second part, the European Commission's DSA guidance specifically identifies grooming among the online risks platforms should address for minors. � The EU is simultaneously developing privacy-preserving age verification: its proposed approach can establish that someone meets an age threshold without disclosing their precise age or identity to the service. � TikTok already requires labels for certain realistic AI-generated content, including substantial face swaps, and supports automatic detection through Content Credentials. � Meta similarly labels detected AI-generated material on Facebook and Instagram. �

digital-strategy.ec.europa.eu

digital-strategy.ec.europa.eu +1

TikTok Ondersteuning

Facebook +1

Part III: The Right to Know — When transparency becomes a responsibility.