The Case Against Conversational Interfaces

The same is true here. The future isn’t about replacing existing computing paradigms with chat interfaces, but about enhancing them to make human-computer interaction feel effortless – like the silent exchange of butter at a well-worn breakfast table.

The second thing we need to figure out is how we can compress voice input to make it faster to transmit. What’s the voice equivalent of a thumbs-up or a keyboard shortcut? Can I prompt Claude faster with simple sounds and whistles? Should ChatGPT have access to my camera so it can change its answers in realtime based on my facial expressions?

This brings me to my core thesis: The inconvenience and inferior data transfer speeds of conversational interfaces make them an unlikely replacement for existing computing paradigms – but what if they complement them?

We keep telling ourselves that previous voice interfaces like Alexa or Siri didn’t succeed because the underlying AI wasn’t smart enough, but that’s only half of the story. The core problem was never the quality of the output function, but the inconvenience of the input function: A natural language prompt like “Hey Google, what’s the weather in San

That’s because text is not a mobile-native input mechanism. A physical keyboard can feel like a natural extension of your mind and body, but typing on a phone is always a little awkward – and it shows in data transfer speeds: Average typing speeds on mobile are just 36 words-per-minute, notably slower than the ~60 words-per-minute on desktop.

To put the writing and speaking speeds into perspective, we form thoughts at 1,000-3,000 words per minute . Natural language might be natural, but it’s a bottleneck.

When people say “natural language” what they mean is written or verbal communication. Natural language is a way to exchange ideas and knowledge between humans. In other words, it’s a data transfer mechanism.

Data transfer mechanisms have two critical factors: speed and lossiness.