Moving towards an era of AI-powered smartphones
Artificial intelligence (AI) features will become a critical product differentiator for smartphone vendors that will help them acquire customers while retaining current users, according to Gartner, Inc. As the smartphone market shifts from selling technology products to delivering compelling and personalised experiences, AI solutions running on the smartphone will become an essential part of vendor road maps over the next two years. Gartner predicts that by 2022, 80 per cent of smartphones shipped will have on-device AI capabilities, up from 10 per cent in 2017.
On-device AI is currently limited to premium devices and provides better data protection and power management than full cloud-based AI, since data is processed and stored locally. The research firm has identified 10 high-impact uses for AI-powered smartphones to enable vendors to provide more value to their customers. A few of these include “digital me” sitting on the device — that is, smartphones will be an extension of the user, capable of recognising them and predicting their next move. They will understand who you are, what you want, when you want it, how you want it done and execute tasks upon your authority.
Another is regarding user authentication — password-based, simple authentication is becoming too complex and less effective, resulting in weak security, poor user experience, and a high cost of ownership. Security technology combined with machine learning, biometrics and user behaviour will improve usability and self-service capabilities. For example, smartphones can capture and learn a user’s behaviour such as patterns when they walk, swipe, apply pressure to the phone, scroll and type, without the need for passwords or active authentications. Third is motion recognition — emotion sensing systems and affective computing allow smartphones to detect, analyse, process and respond to people’s emotional states. The proliferation of virtual personal assistants and other AI-based technology for conversational systems is driving the need to add emotional intelligence for better context and an enhanced service experience. Car manufacturers, for example, can use a smartphone’s front camera to understand a driver’s physical condition or gauge fatigue levels to increase safety. Another high-impact use is natural-language understanding — continuous training and deep learning on smartphones will improve the accuracy of speech recognition, while better understanding the user’s specific intentions. For example, natural-language understanding could be used as a near real-time voice translator on phones.