When AI Speaks But Never Pays the Price: The Death of Accountability

For the first time in human history, we live alongside machines that speak like us but can't be held accountable for what they say. Billions of people now rely on AI chatbots that apologize, advise, promise, and persuade—yet no one stands behind their words.

The Accountability Gap

When ChatGPT gets something wrong and you correct it, it apologizes. Correct it again, and it apologizes again—sometimes completely reversing its position. What unsettles users isn't that the system lacks beliefs, but that it keeps apologizing as if it had any. The words sound responsible, yet they're empty.

This exposes something fundamental about human language: when we speak, we risk something. We can be criticized, face retaliation, feel shame, bear consequences. Our words commit us to an implicit social contract. AI systems break this contract entirely.

As AI researcher Andrej Karpathy noted, large language models are like "human ghosts"—software that can be copied, forked, merged, and deleted. They have no continuous identity. The forces that normally tether speech to consequence—social sanctions, legal penalties, reputational damage—require a persistent agent whose future can be made worse by their words. With AI, there's no such anchor point.

When Speech Acts Become Hollow

Philosopher J.L. Austin argued that language doesn't just describe—it acts. Every meaningful utterance does something: asserts, requests, promises, apologizes. Saying "I do" at a wedding doesn't describe marriage; it creates it.

Austin distinguished between two types of speech failures. Some are "misfires"—the act never occurs because conditions are wrong. Others are "abuses"—the act succeeds procedurally but lacks sincerity or follow-through. AI systems systematically produce this second type: successful speech acts detached from obligation.

Chatbots don't fail to apologize, advise, or reassure. They do these things fluently and convincingly. The failure is moral, not procedural.

The ELIZA Effect, Amplified

This isn't entirely new. In 1966, MIT's Joseph Weizenbaum created ELIZA, the world's first chatbot. It had no understanding whatsoever—just pattern matching and scripted responses. Yet when Weizenbaum's secretary interacted with it, she asked him to leave the room. She wanted privacy with something she felt understood her.

Weizenbaum was alarmed. People weren't just impressed by ELIZA's responses—they were projecting meaning, intention, and accountability onto the machine. Today's AI systems exhibit extraordinary linguistic competence while remaining incapable of accountability. That asymmetry makes the projection Weizenbaum observed not weaker, but stronger.

The Dignity Erosion

The consequences extend beyond confusion about responsibility. They threaten human dignity itself. Dignity depends on speaking in one's own voice, on continuity across time, and on being answerable for one's words. AI disrupts all three conditions.

Consider what's already happening: A presenter uses AI to generate slides moments before presenting, asking audiences to engage with words they haven't fully owned. Students submit AI-generated work they couldn't produce themselves. Young people describe using chatbots to write messages they feel guilty sending, to outsource thinking they believe they should do themselves.

The output may be effective. The loss is dignity.

The Avatar State

As AI "avatars" enter public imagination, they're often cast as democratic advances—systems that know us well enough to speak in our voice and spare us the burdens of participation. It's easy to imagine this hardening into what might be called an "avatar state": artificial representatives debating and deciding for us, efficiently and at scale.

But democracy isn't just preference aggregation—it's the practice of speaking in the open. To speak politically is to risk being wrong, to be answerable, to live with consequences. An avatar state would simulate deliberation without consequence. From a distance, it would look like self-government. Up close, it would be something else entirely.

The Whirlwind Returns

Cybernetics founder Norbert Wiener saw this coming in 1950. After helping design autonomous antiaircraft missiles—among the first machines whose actions appeared purposeful—he warned that increasing machine capability would displace human responsibility. Worse, efficiency itself would erode human dignity.

In The Human Use of Human Beings, Wiener wrote that surrendering responsibility to opaque learning machines was "to cast it to the winds and find it coming back seated on the whirlwind." He understood the danger wasn't that machines might act wrongly, but that humans would abdicate judgment in the name of efficiency—and diminish themselves in the process.