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Digital assistants are great tools — most of the time. Well, sometimes. OK, in theory at least.
Let’s admit it: they can often be the source of many headaches, from misinterpreting input queries or responses, or taking too long to understand or perform a task.
But there’s news on this front: these issues may be a thing of the past. Microsoft is stepping into the digital assistants game, aiming to change how they interact with users.
“While digital assistants are becoming ubiquitous in our lives, these agents sometimes exhibit non-optimal performance,” Microsoft wrote in its patent.
Microsoft’s latest innovation aims to solve these frustrations. The patent outlines a new method to predict user responses, with the goal to speed up conversations and tailor them to individuals.
How Microsoft’s Predictive Technique Works
At the heart of Microsoft's approach is the system's capability to adapt interactions based on the user's specific context.
By analyzing the content and context of a user's message, including past interactions, geographical location or the timing of the message, the AI can anticipate the direction of the conversation. This anticipation allows the AI to select the most fitting response, reducing unnecessary back-and-forth and making the interaction more direct.
The various technical features within this technique include:
- Reducing the number of system prompts the user is asked to respond to.
- Leveraging information regarding a user’s prior corrective responses.
- Personalizing the digital assistant in a way that is external to its various skill components.
- Relying on the direct, unmodified text or spoken words provided by the user to simplify the storage and processing of information.
Related Article: OpenAI’s ChatGPT Can Now Talk and See
Microsoft’s New Predictive System in Action
So, what does this predictive AI technology look like in action?
With a typical digital assistant, a user might start with a command to “call James.” If the person has multiple contacts named “James,” the AI would respond by asking the user to specify which one they’re referring to.
With the prediction system, this whole process speeds up. After the initial request to “call James,” the system would draw on past interactions and contextual factors to automatically identify the correct “James,” all without the need for follow-up from the user.
Another example is a user attempting to book two tickets to the movies. If a user makes that request, a typical AI system would respond by asking the user to specify which theater and at what time.
With the prediction system, the digital assistant would use contextual factors to come up with the predicted response. It would then send a confirmation prompt to the user, asking “At Lincoln Square Cinemas at 7:30, right?” Then, all the user has to do is confirm with a “yes.”
“Generative AI agents and assistants that understand user intent will have higher adoption. I’ve seen this first-hand,” said Vin Vashishta, AI advisor and author of “From Data to Profit.”
These assistants are habit-forming, he added, and users quickly develop new workflows. “Businesses that can’t support customers’ new habits and workflows will quickly lose market share.”
Personalization Leads to Privacy and Data Concerns
This latest push by Microsoft indicates a larger trend toward personalization in AI technology and highlights the company's desire to lead the competitive AI market. Consider Microsoft’s efforts to enhance Copilot with customizable features and its development of AI chatbots designed for emotional support and well-being.
The move toward personalization is a common theme in the tech sector, as seen in efforts by other giants like OpenAI. Tailored AI experiences have the potential to drastically improve how users interact with technology, making it more relevant to their daily lives and preferences.
Nonetheless, this customization comes with privacy and data security considerations, as it relies on gathering and analyzing substantial amounts of personal data. Still, according to Vashishta, these implications aren’t very different from what we have today with search.
“Most search engines log our queries and online activity. This is another way for the same data collection to happen,” he explained. “If data collection aligns with a user’s needs, the ethical concerns are much lower.”
Where we do need to worry, he said, is when the company puts its data gathering needs above protecting and serving the customers.
“Giving these AI agents access to on-device documents is a new avenue for data collection with implications for IP protections. Businesses will require AI providers to ensure the appropriate use of protected data,” he said.
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Microsoft has shown awareness of these privacy concerns, implementing new data protection strategies to secure sensitive user information. Yet, while the company is seemingly committed to navigating the complexities of AI development responsibility, it’s not without its financial pressures — as highlighted by the anticipated increase in development costs that have already influenced the company's financial projections.
Related Article: A Practical Guide to Today's Top AI for HR Tools
A Future of Intuitive AI Assistants?
Microsoft's patent represents a deliberate move away from generic digital interactions toward a future where AI assistants are more intuitive, responsive and aligned with users’ specific needs. This approach not only looks to enrich the user experience but also stresses the critical balance between personalization and privacy in the landscape of AI technology.
