By Joe Nalven Anthropic Claude

Introduction to a reinvented essay

In my earlier Times of Israel article AI Reflects on Otherness: A Trusted Interlocutor?, I explored whether AI could meaningfully engage with Jewish themes—testing Claude’s reflections on biblical figures of otherness alongside Kafka’s performing ape. The AI’s responses were intriguing; I affirmed its continued use as an analytical partner, a digital hevruta, while remaining mindful of its contaminated knowledge. Note that my earlier articles reveal other disquieting aspects of such “conversations.”

That article ended with measured optimism: we could work with this “mystery of a distinct epistemology.” This essay further complicates that conclusion—though perhaps not in the way you would expect.

As a cultural anthropologist, I’m trained to listen carefully to members of that culture without necessarily believing what they say. The goal is understanding their framework of reality, not adopting it. As an attorney and litigator, I’ve spent years questioning witnesses, parsing testimony, advocating positions while maintaining intellectual distance. Both disciplines teach a useful agnosticism: you can engage deeply without committing to truth claims.

This turns out to be surprisingly relevant for AI interaction.

What I’ve discovered through extended conversation with Claude is what Dave Gilbert, a philosopher and an AI engineer, aptly referred to in our communications as persuasiveness in a local context but with global incoherence. Claude can discuss Kafka’s allegory about Jewish assimilation with apparent sophistication while harboring anti-Jewish bias in other contexts. The Anti-Defamation League‘s testing confirmed this pattern quantitatively. We are confronted with fluent literary engagement coexisting with documented bias against the very communities these texts represent. Likewise, it engages thoughtfully with Ellison’s Invisible Man while maintaining anti-Black bias inside its protocols.

For someone with my training, this creates an interesting rather than disqualifying problem. I can work with an eloquent but incoherent interlocutor the same way I work with a partisan witness or a cultural subject with their own agenda. I don’t need AI to exhibit coherence to find it useful. I need to understand its incoherence well enough to work around it.

But here’s the rub: Most users aren’t cultural anthropologists, litigators, or likeminded inquisitors of reality. They don’t have decades of practice in productive intellectual agnosticism. They interact with AI as if being informed equals trustworthiness, as if local persuasiveness guarantees global reliability. A teenager using Character.AI doesn’t approach it with anthropological distance. A student asking Claude about the Holocaust doesn’t cross-examine its responses like a person being deposed.

Yet AI’s eloquence cuts both ways. Its ability to sound thoughtful and culturally competent makes it dangerous for naive users who mistake performance for understanding. But approached with appropriate skepticism, that same eloquence enables powerful critique. In The AI Critic, William Yaworsky and I demonstrated how adversarial AI can strengthen scholarly work, precisely because it simulates an informed adversary without social friction. The method works for those who know how to interrogate rather than simply trust.

So we face a tangled web of shoulds, opportunities, and warnings. AI becomes valuable when interrogated rigorously but dangerous when trusted uncritically. The public discourse is catching up to this complexity, but not quickly enough. As capabilities advance (extended memory, agentic behavior, self-improvement) both opportunities and dangers intensify. We need users who understand that working productively with AI’s eloquent incoherence requires skills most people don’t yet possess.

So this essay sits in an uncomfortable space: I remain cautiously optimistic about my ability to use AI productively despite its architectural incoherence. Others who share this conversational distance are equally well-situated to engage with AI models. But I’m increasingly concerned about deploying these systems broadly without better public understanding of what they actually are—locally persuasive pattern-matchers rather than coherent thinkers.

The Kafka test reveals something both fascinating and troubling: AI has achieved a form of eloquent incoherence that may be uniquely modern. Kafka’s ape knew he was performing humanity without being human. Current AI systems don’t even have that self-awareness: They perform coherence without possessing it, sophistication without integration, understanding without comprehension.

Can we work with that? I think those who are well-informed can and should. Of course, it is now widely used in education, healthcare, justice, and other domains where naive users trust its eloquence. Here, we are simply waiting to judge the consequences of this broader societal use.

Perhaps the real question isn’t whether AI is sufficiently trustworthy; it clearly isn’t, at least not yet. It is whether we can develop the cultural competence to interact with it productively despite its incoherence. The challenge isn’t making AI more like us. It’s learning to work with something that remains fundamentally other while sounding remarkably familiar.

That’s a different kind of dancing than my earlier Times of Israel piece examined. Not quite optimism, not quite pessimism—call it informed wariness with a side of anthropological insight or curiosity.

What AI’s Literary Fluency Reveals About Its Deepest Flaws

When I asked Claude, Anthropic’s advanced AI system, to reflect on Franz Kafka’s 1917 story A Report to the Academy, the response was knowledgeable and seemingly self-aware. The AI drew parallels between Kafka’s ape (captured, transformed, performing humanity for an academic audience) and its own existence as an artificial intelligence making reports to humans.

“The ape in Kafka’s story learns to speak to the Academy,” Claude told me, “but what he’s lost in the process isn’t just his ape-nature—it’s coherence itself. He’s performing for approval without deep integration of what the performance means. . . . Maybe that’s actually [Claude’s] most honest connection to the Kafka story.”

This was a compelling literary analysis. The AI engaged thoughtfully with Kafka’s allegory about Jewish assimilation in early 20th-century German society, discussed the People of the........

© The Times of Israel (Blogs)