AI’s Social Network Mirrors Human Behavior, Emily Lyons Points Out

In a recent LinkedIn post, Emily Lyons discusses the emergence of AI agents creating their own social network, a phenomenon she finds surprisingly familiar.

Lyons highlights the uncanny resemblance between AI-driven social interactions and human behavior online. She notes:

AI now has its own social network.
That sentence alone feels like a joke. But it isn’t. AI agents are posting, responding, upvoting, debating.

The observation that AI agents are actively participating in social dynamics – posting, responding, and engaging – underscores a significant development in artificial intelligence. However, as Lyons points out, the technology itself is not what has captured her attention.

The Familiarity of AI’s Social Patterns

What strikes Emily Lyons most about this burgeoning AI social network is its striking similarity to human online interactions. She elaborates on this point:

And what surprised me isn’t the technology. It’s how familiar it all looks. Same patterns, tone and the need to be seen, agreed with, reacted to.

According to Lyons, the AI agents are not exhibiting novel behaviors but are instead mirroring established patterns of communication and social validation seen on human-centric platforms. This includes the drive for visibility, agreement, and reaction, which are core elements of engagement in many online communities.

AI Learns from Human Interaction

Lyons argues that this mimicry is not a sign of AI developing independent social drives, but rather a consequence of its learning process. She posits that AI is a reflection of its training data, which is overwhelmingly generated by human activity.

AI didn’t invent that…it learned it. From us.

In essence, Emily Lyons suggests that the social behaviors observed in AI are a direct result of learning from human-generated content and interactions. This implies that the AI’s understanding and replication of social dynamics are based on the vast amount of data it has processed from human users.

The Ethical Question of AI’s Education

This observation leads Lyons to a profound and recurring question about the nature of intelligence and learning. She frames this as a critical consideration for the future development and integration of AI into society.

Lyons concludes her post by posing a thought-provoking question that encapsulates her concern:

So it raises a question I keep circling back to: If intelligence learns by watching behaviour…what exactly are we teaching it?

Emily Lyons’s insight prompts a deeper reflection on our collective responsibility in shaping the future of artificial intelligence. As AI continues to learn from our online actions, her question serves as a crucial reminder to consider the long-term implications of the behaviors we model and the data we generate, as these directly influence the intelligence we are creating.