Are We Still Talking To Humans?
Part I — The Manufactured Crowd
Bots, artificial engagement and the illusion of public opinion
You open Instagram, LinkedIn, TikTok or X.
A post has thousands of likes. Hundreds of people have commented. The same opinion appears again and again. Some comments are angry, others supportive. People argue with each other.
Without consciously deciding to do so, we register something:
Apparently, a lot of people think this.
That assumption matters.
Likes, comments, followers and shares are not just numbers. They are social signals. They help us estimate what other people find important, credible, outrageous or normal.
But there is a problem.
We increasingly cannot be certain how many independent human beings those numbers actually represent.
When 100 voices are not 100 people
Bots have existed for years. At their simplest, they are software programs that perform actions automatically: posting, following, liking, sharing or commenting.
One bot is not particularly interesting.
Thousands of automated or centrally coordinated accounts are.
If one organisation controls 100 accounts and all of them participate in the same discussion, we may perceive 100 different voices.
The interface shows 100 participants.
The reality behind the screen may contain only one organising actor.
That is where bots become more than spam.
They can create the appearance of popularity, outrage, disagreement or consensus. They can amplify a subject until real people start noticing it — and then those real people begin reacting as well.
Artificial activity can therefore generate genuine human activity.
At that point, separating the two becomes considerably harder.
The information does not even have to be false
Much of the public debate about online manipulation concentrates on disinformation: deliberately false or misleading information.
But manipulation can be more subtle.
Imagine a perfectly factual article that is artificially shared thousands of times by coordinated accounts.
The article has not become false.
Its apparent social importance has been manipulated.
That distinction matters because people do not judge information in isolation. We look at what others are reading, sharing and saying.
A minority opinion can be made to look widespread.
A controversy can be made to look enormous.
Anger can be made to look universal.
And repetition can create the impression that an issue is suddenly everywhere.
Nobody needs to put an opinion directly into our heads.
Changing the environment in which we form that opinion may already be influential.
This is not hypothetical
The European External Action Service (EEAS), the diplomatic service of the European Union, investigates what it calls Foreign Information Manipulation and Interference (FIMI).
Its 2026 threat report examined organised attempts to manipulate information environments. The report describes networks of channels, websites and social-media accounts used to produce and amplify influence operations.
Political influence is one documented application, but artificial engagement is not exclusively political.
Commercial actors can want popularity. Fraudsters need credibility. Marketers want reach. Campaign organisations want attention. And real users can organise themselves into so-called engagement pods, agreeing to like and comment on one another's posts to increase visibility.
Even LinkedIn explicitly prohibits fake accounts, bots and fake engagement intended to manipulate its content algorithms.
In March 2026, LinkedIn went further. It announced additional measures against automated comments and engagement pods, stating that LinkedIn should be a platform for real people, real jobs and real conversations.
That is an interesting choice of words.
Because apparently, even on a professional network, whether the person and interaction are real can no longer simply be assumed.
What does a like actually mean?
This changes the way we should look at familiar social-media statistics.
1,000 likes do not necessarily equal 1,000 independent human judgements.
500 similar comments do not constitute an opinion poll.
A trending subject does not automatically represent spontaneous public interest.
But the opposite is equally important.
Ten likes do not mean that only ten people found something valuable. Algorithms, network position, timing and recommendation systems also determine what becomes visible.
Social-media metrics look precise.
What they measure is considerably less precise than the number suggests.
That should make us cautious — not paranoid.
Not every strange account is a bot. Not every popular opinion is manufactured. And an opinion we disagree with should never be dismissed as artificial without evidence.
Awareness means understanding that manipulation is possible without imagining it everywhere.
But there is another problem
So far, we have assumed that bots are relatively easy to understand.
A machine performs actions that normally belong to a person.
But generative Artificial Intelligence changes something more fundamental.
AI can now create the photograph.
It can write the biography.
It can produce the posts.
It can write the comments.
It can change tone, language and personality.
And suddenly the question is no longer only whether the crowd is real.
It becomes much more personal:
Is the person I am talking to a person at all?
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The factual foundation for Part I comes from the European External Action Service (EEAS) and its 2026 report on Foreign Information Manipulation and Interference (FIMI). � A particularly well-documented historical example is the US case concerning the Internet Research Agency: the indictment describes hundreds of fictitious US personas and accounts designed to appear American. � LinkedIn currently prohibits fake accounts, bots and fake engagement and says it limits engagement pods and automated comments. �
Part II: Who Are You? — Synthetic identities and the disappearance of certainty online.