AI learns to adapt to your style when you converse with ai using sophisticated machine learning algorithms which monitor and analyze trends in your language and communication preferences. For example, we can see how personal assistants such as Apple Siri or Google Assistant learn with time. Forrester Research showed in a report of 2022 that 68 percent of users feel that their AI assistants learn and get personalized answers based on their individual usage patterns even after just a few interactions. These assistants then learn things like your preferred tone, the phrases you typically use, and perhaps even contextual cues that lead these machines to adjust their responses in a way that seems appropriate to your unique way of expressing yourself.
Natural Language Processing (NLP) is an important part of this process. For example, NLP models like GPT-4 and BERT are generally used in chatbots or virtual assistants to understand user intent and respond. These models are trained on huge datasets that allow them to comprehend everyting from formal business vernacular all the way down to casual, street language. Specifically, a study in the Journal of Artificial Intelligence Research conducted this year found that given some exposure to writing styles, AI systems such as GPT-4 could then shift their responses with up to 95% accuracy based on the conversation thus far, creating a much more natural experience tailored to each individual user’s articulation and tone of voice.
Additionally, some AI will even recognize certain emotional signals in your language and change their tone. So if a user is talk to ai in a formal manner, AI can reply with an official structured response. But when a user uses an informal tone or language, like slang or abbreviations, AI can follow that and give a casual and friendly response. A prime example is with customer service chatbots, who change their tone depending on the seriousness of the situation or how urgent one needs their answer. In a 2021 Salesforce report, it was stated that around 78% of customers expect a tailored service experience, and AI is leading the charge when it comes to delivery at scale by adapting to their style.
AI adapting to your style is also evident in personalized recommendations like those from Netflix or Spotify. They analyze your recent behavior, like what kind of shows you watch or what kind of music you listen to and learn about your taste over time. These AI systems also start getting more and more ingrained in knowing what type of content you like, and so they begin to recommend content that is tailored to your exact liking. For example, Spotify has AI that works with a recommendation algorithm changing according to the listening habits of users and brings you playlists and songs based on your very own unique style. Spotify, in 2023 claimed an 85% improvement of its recommendation algorithm accuracy after only half a year.
With a single word, the ai learns and adapts to constantly become better at mimicking your preferred style of communication in alignment with your own personality and behavior using such technologies. With more interactions, the system better performs conversions in a natural and customized way for you. Machine learning and natural language processing (NLP) are enabling a lot of adjustments to user style, making these behaviors part of the AI experience and consequently embedding AI more closely to human interactions.