Because Alexa shouldn't be ashamed of not being ChatGPT

Because Alexa shouldn't be ashamed of not being ChatGPT


When Microsoft unveiled the new Bing and Google unveiled Bard, many compared these new generative AI services to digital assistants like Alexa, Google Assistant, and Siri, to underscore the gap in capabilities. Even Microsoft CEO Satya Nadella made this point in an interview with the Financial Times earlier this month: "They were all dumb as rocks," he told the paper last month. "Whether it's Cortana, Alexa, Google Assistant or Siri, all of these products don't work. So we had a product that was supposed to be the new interface for a lot of information that didn't work."

I understand that it is natural to make this comparison because we are talking about AI and also because these new experiences, from ChatGPT to Microsoft Copilot, have been referred to as chatbots which, coincidentally, was also how we referred to digital assistants.

There are two main reasons why the comparison is incorrect.

Because Microsoft will change online search and not Google

by Caroline Milanesi


The work to be done

The first is that digital assistants have a different job to do. Even the new Bing agreed when I asked, "Are you like Alexa?" He replied, "Alexa is Amazon's voice AI that can help you with various tasks and requests. I am Microsoft's Bing chat mode, which can help you find information and generate content. We're both powered by AI, but we have different characteristics and capabilities.

Bing is right. By and large, digital assistants were created to do tasks for us, whether it's providing simple information like the weather, adding something to our shopping list, or helping us navigate our smart homes.

What started out as simple voice-based interactions have morphed into preemptive and contextual suggestions. Navigating our private life, especially our home, is not an easy task, because privacy and different comfort levels come into play more often than we think. There is also a key difference when dealing with Bing and ChatGPT versus Alexa, Siri or Google Assistant. In the first case, the knowledge necessary for the required task to be carried out profitably is found with them, while in the second case, it depends on us.

This brings me to the second reason for their success.

Emotions, lies, mistakes: the double life of Bing





The investment

These experiences are also so different because of the investment made in chatbots versus assistants. Not only the financial investment of companies of the caliber of Open AI and Microsoft, or the computing power that these interactions require, but the investment that we, the users, have made and, consequently, of the data available to the platforms.

ChatGPT or other generative AI services are powered by huge amounts of data and their performance depends on the information they have. We then interact with them by leveraging their knowledge database, asking a question and obtaining information in a format that makes it easily accessible, or by commissioning them to create content for us based on all the information available.

With digital assistants, the investment must come from the individual users. There is no way for a brand, be it Amazon, Apple or Google, to know all of our personal information to help the digital assistant be more efficient or conduct more human-like interactions.

Over the years the focus has been on conversational AI so that the tips we have to give digital assistants are not rigid, essentially shifting learning how to talk to a digital assistant to just understanding. But as a user, I had to invest. I had to decide that I wanted to train the assistant with my own data and interactions. This is an aspect of the relationship we have with digital assistants that is not always clear.

The more I do, the more I share, the more the system improves. Just like it would with a real human assistant. Whether digital or real, an assistant learns from your behavior, learns your preferences, and over time starts doing things for you. As a result, our trust in them grows and empowers them to do even more as they get things right.

Digital assistants and new chatbots share the same opportunity: as their behavior translates into more correct results to meet our needs, we trust them more. The more we trust them, the more we demand from them. This is where some friction arose in the early life of digital assistants, when simple tasks were performed flawlessly and users started wanting more, but expectations weren't always met. That "more" was slow in coming. With the new chatbots we are not there yet and for now it is just a moment of great effect. But let's be honest with ourselves. It's a bit like the first time you used Alexa to get an answer to a question spoken into a smart speaker or watched the lights go off with a voice command. It even seems boring now, as most users continue to do the same tasks they did in 2014.

My life with Astro, Amazon's home robot

by Caroline Milanesi



Give and take

We want more, but we are not willing to commit too much. And this is another aspect of its interactions that will also be true for generative AI. How much effort will it take, as a user, to verify the information I receive from my queries? Is that comparable to the effort it takes to create a Siri shortcut so that when I say "goodnight," the lights go out, the doors close, and the thermostat switches to a lower temperature? Or is the result so brilliant that my effort will seem less due to the greater benefit I get from it? Will my trust in these new chatbots fade when I find out that the information is incorrect?

Generative AI is magical in some ways, but the real value emerges when you invest in it consistently, whether it's Microsoft and Google updating their models and continuing to inject fresh data, or whether it's us that we teach our digital assistant what our morning routine is.

There's always something fascinating about an object - a smart speaker, a computer, a search engine - that behaves similar to a human being. Chatbots and digital assistants are here to make us better, to take the friction out of mundane tasks, and ultimately to try and make our daily lives a little easier. However, this does not happen without us changing too. Whether it's finding an unexpected question about ordering toilet paper normal, or seeing an automated thank you email sent to every guest who attended the party over the weekend. What we can get from our experiences will always be proportional to our level of acceptance. This is easier to do in a consumer context, with simple, non-sensitive tasks, than in a corporate environment, where we may have to rethink how we work and our value.



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