Your hands are covered in flour, a pot is simmering on the stove, and you need to know how much longer the chicken needs to roast. Without missing a beat, you call out into the empty kitchen, “Hey Siri, set a timer for 15 minutes.” A cheerful chime confirms your command has been received and executed. You didn’t say please. You didn’t phrase it as a question. You issued a direct, unadorned order.

This interaction is second nature to millions of us, but from a linguistic perspective, it’s fascinating. We have, almost unconsciously, developed an entirely new way of speaking—a specific linguistic register reserved for our digital assistants. This “Machine Speak” is a dialect of convenience, defined by its own unwritten grammar. But what are its rules, and what does the way we talk to our machines say about us?

The Anatomy of a Command: A New Linguistic Register

In linguistics, a register is a variety of language used for a particular purpose or in a particular social setting. We use different registers when talking to a child versus a boss, or when writing a legal document versus a text message. Our communication with voice assistants like Siri, Alexa, and Google Assistant is a perfect example of a new, technology-driven register with several key features.

1. The All-Powerful Imperative

The foundation of Machine Speak is the imperative mood. We don’t ask, we tell. Consider the difference:

• To a human: “Hi, sorry to bother you, but could you tell me what the weather will be like tomorrow?”
• To an AI: “Alexa, weather tomorrow.”

Our requests to humans are often softened with politeness markers (“please,” “could you”), hedges (“I was just wondering”), and framing questions. With machines, we strip all that away. The interaction is purely transactional. The AI is a tool, and we use the most direct linguistic form to operate it: the command.

2. Stripped-Down Syntax

Why waste breath on connecting words and grammatical pleasantries the machine doesn’t need? Our syntax when addressing an AI is ruthlessly efficient. We often reduce complex questions to a string of keywords.

• Instead of: “I want to listen to the new album by Taylor Swift.”
• We say: “Hey Google, play Taylor Swift’s new album.”

We’ve learned, through trial and error, what the AI can parse. We know that articles (“a,” “the”), pronouns (“I,” “me”), and complex clauses are often superfluous. The core structure is typically [Wake Word] + [Action Verb] + [Object/Parameters]. It’s the linguistic equivalent of using a cheat code—the shortest path to the desired outcome.

3. The Politeness Vacuum

Perhaps the most noticeable feature of Machine Speak is the stark absence of social lubricants like “please” and “thank you.” This isn’t because we’re trying to be rude; it’s because we intuitively understand that these markers are for beings with feelings, social standing, and egos. Politeness in human interaction serves to maintain social harmony and acknowledge the other person’s agency.

An AI has no feelings to hurt and no social favors to repay. Saying “thank you” to Alexa after she tells you the time feels strange, even performative, because the social contract that underpins such pleasantries doesn’t exist in this human-machine dynamic.

Our Internal Operating System: Why We Speak ‘Machine’

This unique register didn’t appear out of nowhere. It’s a direct reflection of our mental model of AI. We perceive these assistants not as conversational partners but as sophisticated vending machines. You put in a specific coin (a command), and you get a specific snack (a result). There’s no need for small talk with a vending machine.

Furthermore, the AI itself has trained us to speak this way. When we first started using voice assistants, we might have tried more natural, complex sentences. When those failed, the system either asked for clarification or simply didn’t work. So, we adapted. We simplified our language until we found the patterns that yielded the most reliable results. In a fascinating reversal, the machine taught the human how to communicate effectively on its terms.

This creates a comfortable, predictable interaction loop. When an AI tries to be too conversational, with unsolicited jokes or overly chummy responses, it can sometimes breach this unspoken contract and stray into the “uncanny valley,” feeling awkward or inauthentic. Our blunt Machine Speak keeps the interaction firmly in the realm of utility.

Echoes in the Real World: The Human Impact

As this register becomes more ingrained in our daily lives, a new question emerges: Is it changing how we communicate with each other?

The most-discussed concern is the so-called “Alexa Effect” on children. Parents worried that kids who got used to barking orders at a digital assistant without saying “please” would transfer that behavior to their interactions with people. The concern was so widespread that Amazon introduced an optional “Magic Word” feature for Alexa, which offers positive reinforcement when a child uses the word “please.”

For adults, the effect may be more subtle. Our reliance on keyword-based commands for voice assistants mirrors the way we’ve learned to communicate with search engines. For decades, we’ve trained ourselves to “Google” using terms like “best pizza near me” instead of full sentences. Machine Speak is arguably the next evolution of this “search engine syntax,” moving it from our fingertips to our voices.

However, this new register can also have a positive, clarifying effect. By creating such a stark contrast with human communication, it forces us to implicitly recognize *why* we use politeness, nuance, and indirectness with people. These aren’t inefficient bugs in our language; they are critical features that build rapport, show respect, and navigate complex social landscapes. Talking to a machine highlights what is fundamentally human about talking to a human.

The language we use with our voice assistants is more than just a quirky habit. It’s a living example of how language adapts to new technologies and social contexts. This stripped-down, imperative-driven register is a highly specialized tool for a specific job. As AI continues to evolve and become more integrated into our lives, so too will the grammar we use to control it. The question is, will our machines get better at understanding our messy, human way of speaking, or will we become even more fluent in the direct, efficient language of the machine?