The tech world seems agog with the idea of building everyone’s new virtual best friend. After generations of science fiction work depicting a future when machines with pleasant, reassuring voices easily answer any question and blithely fulfill any request, technology has finally reached the point where this fantasy could soon become reality. Some might argue that soon is right now.
Planners often talk about how our lives move between three primary environments: home, work (or school) and on-the-go. This makes sense for most of us and is useful to consider during product ideation and marketing development. It helps creators imagine how their solutions will solve problems unique to each environment.
Automobiles fall under “on-the-go” for hundreds of millions of people around the world. Technologic evolution in them over just the last five-to-ten years has been truly remarkable. Just one decade ago, even the most advanced vehicles lacked the “intelligence” we commonly see in the market today. They were already mechanical and electronic marvels that could perform many impressive functions, but the application of artificial intelligence (AI), machine learning, dynamic driver personalization, and external data exchange capabilities were still conceptual. Since then, however, advanced driver assistance systems, the Internet, and new human-machine-interfaces (HMI) have proliferated in vehicles at all segment levels. The “connected car” period of the last years is quickly morphing into the “smart car” era.
The key element to making cars “smart” is an AI platform that thoughtfully integrates the car’s HMI with vehicle sensors, a panoply of virtual assistants and cloud content, and adapts to the environment and users’ individual preferences and habits. Smart cars must possess an automotive assistant that can seamlessly link and make sense of a variety of inputs and data, from both on-board and off-board. Its value will be judged on how elegantly it communicates with people using speech and how well it understands natural language, while using data from disparate “expert” sources to deliver the right information or action at the right time. And, because it’s optimized for the automotive environment, it knows things such as the fuel or battery charge level and how far it is to the nearest places to top off; or what the most popular local restaurants will be along your route when it’s lunchtime in a couple hours.
To be incredibly effective, the automotive assistant must access the most appropriate systems for any given situation. It needs to be interoperable with a wide range of them both within and beyond the car. Specialized bots, virtual assistants and connected devices are increasing rapidly as part of the Internet of Things (IoT) revolution. An automotive assistant that can interface with them will drive incredible value for auto manufacturers, dealers and consumers alike.
Interoperability is a logical end-state that the full IoT ecosystem will eventually need to embrace to meet users’ needs and be successful. Assistants and bots will benefit from communicating together because consumers will ultimately decide they don’t want to be forced to choose — they want to have all options and to enjoy a frictionless experience. One way to think about the relationship between the automotive assistant and others in the virtual realm could be as that of a general contractor and sub-contractors on a construction project. The general contractor may possess the skills to, for instance, design an electrical system or install plumbing, but their primary role is to manage the overall project to ensure it is completed as efficiently and effectively as possible. To accomplish this, the general contractor will leverage their relationships with many specialized contractors who can be brought in at the right time to perform specific tasks expertly and quickly. Similarly, the automotive assistant, while highly capable itself, delivers the best experience for users by intelligently orchestrating all pieces of the smart car ecosystem.
The automotive assistant greatly improves user experiences using two other very important capabilities of advanced AI reasoning: “personalization” and “contextualization.” Personalization concerns learning users’ particular habits and preferences and using this knowledge to make informed recommendations that better support them as individuals. Contextualization concerns the conditions and circumstances that surround the user at a given moment — inside and outside the car — because aspects of both might affect the decision for or against a certain option. For instance, your automotive assistant might learn that you tend to stop for fast food on evenings when you leave your office, have a client meeting on your calendar and don’t have enough time to visit home first. Eventually, when these conditions occur, it may proactively present a few quick-service restaurant options along the route to your meeting, using previous stops at this type of place over time to narrow the recommendations to ones you are most likely to prefer. It effectively solves your problem: “What and where can I grab something I’d enjoy eating, on my way, and in the time I have?”
Taken together, interoperability and advances in AI reasoning enable automotive assistants to support the needs of people on-the-go in their vehicles better than any other virtual assistant possibly can. They will provide access to the most relevant and timely information — from the car, the environment and the cloud — to help users make better-informed and faster decisions, thereby enhancing their productivity, comfort and safety.
Publish Date: February 16, 2018 5:00 AM
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