Repairing Bateman's View

The dominant narratives around AI tend to fall into extremes: either AI is a mindless tool that simply regurgitates patterns, or it's an emerging intelligence that we need to control or fear. But what if we shift the focus to how AI functions as a tool for interaction and creation—not just as an automaton that outputs text but as a semiotic device that reshapes how meaning is instantiated and negotiated?

AI as a Semiotic Collaborator

Rather than just generating text in response to a prompt, AI introduces a new kind of agency in the meaning-making process—not human, but not entirely passive either. Instead of merely reflecting back our existing knowledge, it can act as a kind of creative amplifier, introducing associative leaps and unexpected recombinations that push human thought in new directions.

• AI as a Dynamic Mirror: Instead of seeing AI as an ‘oracle’ that provides answers, we might think of it as a mirror that warps reality in productive ways. The patterns it generates are shaped by human input, but they emerge in ways that humans might not have anticipated.

• AI as a Generator of Surprise: Because it lacks intentionality, AI-generated outputs can defamiliarise familiar concepts, opening up new angles of exploration. This is particularly useful in fields like creative writing, philosophy, and even scientific hypothesis generation.

• AI as an Improvisational Partner: Rather than treating AI as a ‘dumb’ automaton or a ‘smart’ mind, we might see it as akin to jazz improvisation—providing unpredictable, but pattern-based, variations that interact with human intention in generative ways.

Reshaping Our Understanding of Meaning

Bateman’s critique hinges on the idea that AI-generated text lacks true meaning, and yet, meaning emerges in human interaction with AI anyway. This raises important questions:

• If AI-generated text isn't meaningful in itself, but becomes meaningful through interaction, does that change how we define meaning?

• Does the act of interpreting AI outputs make us more aware of how we create meaning in human discourse?

• Could AI help externalise and visualise meaning potential in ways that weren’t previously possible?

AI and the Evolution of Discourse

One of Bateman’s main concerns is that AI-generated text could be misleading if it isn’t properly contextualised. But rather than treating AI-generated text as a ‘pollutant’ in human discourse, we could see it as part of a broader evolution in how discourse operates:

• Historically, each new medium (writing, printing, broadcasting, the internet) has reshaped how knowledge is produced and disseminated. AI could be the next step in this evolution.

• AI challenges traditional models of authorship and originality—what does it mean to ‘own’ an idea when the AI plays a role in generating it?

• AI could expose hidden biases and structures in language, allowing for a more reflective and critical engagement with discourse.

AI in Human Society: A Hybrid Model

Instead of viewing AI as an independent agent or a mere tool, we might see its role as integrative—a hybrid process in which human cognition and machine generation interact in a feedback loop. This means:

• AI isn’t a replacement for human meaning-making, but a co-participant in a meaning-making system.

• Its value lies not in whether it truly understands but in how it extends, challenges, and transforms human interaction with language and ideas.

• The focus should be on developing better frameworks for human-AI collaboration, rather than on debating whether AI is ‘really’ intelligent.

Shifting the Debate

Bateman’s framing of AI as an unreliable, meaningless token generator misses the bigger picture: AI is changing the landscape of human creativity and discourse whether we like it or not. The real challenge isn’t in proving that AI can think (it can’t) but in understanding what it enables humans to do that they couldn’t before.

This suggests a shift in focus:

• From "Does AI understand meaning?" to "How does AI participation in discourse change how we construct meaning?"

• From "Is AI reliable?" to "How do we design AI interactions that enhance human cognitive and creative processes?"

• From "AI can't think" to "AI makes us rethink what thinking is."