Meet the “Thinking Machine”: Why We Chose Not to Personify AI at Replicant

By Nicole
January 7, 2020

Artificial Intelligence (AI) has been around for a while now. Al algorithms were brought to life more than fifty years ago, but it hasn’t been until the last decade that we’ve seen the impact of AI on our daily lives. AI is a key ingredient in intelligent applications, autonomous vehicles, and smart devices, but the evolution of AI is just like anything else, it “learns” to evolve with time.

You may be thinking, “but AI isn’t living, it is coded into development by humans so how could it have natural characteristics?” True, but what makes AI unique is it’s one of the most human-centric technologies of our generation.

Unlike other technologies, AI is capable of taking on human-like qualities like language and visual perception. This has many implications that we won’t fully unpack here, but what we will begin to discuss, are the initial building blocks of AI’s personified qualities, like giving it a name or not. We’ve seen “personified AI” with devices like Amazon’s Alexa. When you need to beckon Alexa it’s easy, you just say “Alexa” and she starts thinking for you. But, Google’s Home Assistant responds to, “Hey, Google,” a command that intentionally lacks personality. They both serve similar purposes but one is named “Alexa” (a human-like name) and the other “Google” (a computer-like name).

It’s an important question to answer, whether or not to give AI human-like names, as names set the foundation for how we treat and represent everything we interact with. Do we want AI to feel like us or do we want to create delineated boundaries as AI continues to evolve?

According to the Stanford communications professor Clifford Nass, one might argue that we should give AI female names and voices as it’s a well-established phenomenon that the human brain is developed to like female voices. This could make giving and receiving commands more amicable between humans and AI, thus leading to greater adoption of AI assistants, but it could also alienate certain users.

At Replicant, we believe that it comes down to personal preference. Both naming approaches serve a purpose and have their benefits and drawbacks, but from our experience, referring to AI in a more literal sense helps to reduce bias and create a neutral starting point for early users.

It’s also fair to say that until we have general purpose AI, we should name AI for what it is – technology. That’s why we chose to call our conversational AI platform the “Thinking Machine”. We wanted a transparent name that implicitly highlights the underlying technology without alienating users. The “Thinking Machine” gives us an opportunity to broaden the potential of our platform by using a name that makes users think of the technology first before anything else.

When it comes to the actual experience of using Replicant’s conversational AI platform however, we’ve taken great care to make it as human-like as possible. As stated by the World Economic Forum, “Designing human-centric AI interactions, optimized to develop trusted relationships between AI and humans, presents the largest opportunity for human and societal advancement in the modern era.”

When our users speak with Replicant Voice, we want it to feel as natural and emotive as possible. We want customer service agents to be able to rely on Replicant to handle tier-1 customer support issues so they can focus on customer service issues that require the most human qualities of all, compassion and empathy. We can only achieve this vision if the quality of Replicant Voice is exceptional. You can read more here on the principles we’ve developed to craft great human to machine conversations to clear the path for “human-centric AI interactions”.

Ultimately the decision of whether or not to name AI assistants and conversational AI platforms is up to companies and customers. Here are a few questions to evaluate and consider throughout the process:

Why do we need to name AI in the first place? We use names to identify one person from another and to create empathy between humans. As Dale Carnegie states in his best seller (for a few decades now!), “How to Win Friends and Influence People”, a person’s own name is the sweetest sound to their own ears. AI lacks empathy though, so unlike humans, naming AI isn’t as important by the same standards.

How can you bring attention to the innovation behind your AI technology? When you answer the phone with an assistive machine using a greeting like, “Thanks for calling Acme, this is Amy speaking” you miss an opportunity to make your technology memorable. Amy may be a generic name whereas a name like the “Thinking Machine” evokes a sense of curiosity and implicitly highlights the technology’s capabilities.

How do you want your users to perceive AI? AI doesn’t possess human empathy or compassion so when you give AI a name, you increase your user’s expectation that it will act and respond with the same emotional intelligence as a human. This may set false expectations which could disappoint your users.

How do you pick the right name when every name has an association? Sometimes a name causes us to reminisce about a friend or family member, or maybe it’s our own name so we have instant familiarity. Other names may have greater association to a particular minority group. The common denominator here is that human-like names are subjective whereas computer-like names such as the “Thinking Machine”, are objective and less bias.

In conclusion, it is up to companies and customers to decide whether or not to name their AI assistants and conversational AI platforms and there is no right or wrong answer. Your AI assistant can be called Julie, Mark or a “Thinking Machine” and it will perform exactly the same way. That said, a name sets the foundation as you consider how to guide your user’s relationship with AI-driven technology. We spend a lot of time thinking about conversational design at Replicant so we wanted to be the first to share our opinions as we continue to evolve our own best practices.