Assistants here, assistants there, assistants everywhere.
The tech world seems agog about building everyone’s new virtual best friend, ready to tirelessly serve our practical needs and whimsical desires anytime and anywhere. After decades of science fiction visions about a future when intelligent machines with pleasant, reassuring voices effortlessly answer their master’s most pressing questions and blithely fulfill any request, 21st Century technology has finally tipped over the point where futuristic fantasies 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 has been very useful for product ideation and marketing purposes. It helps creators imagine how their solutions will solve problems unique to each environment.
Automobiles are part of the “on-the-go” scenario for hundreds of millions of people around the globe. It is really quite remarkable how dramatically the automotive industry has been evolving over just the last five-to-ten years. Ten years ago, even the most advanced vehicles on the market lacked the intelligence we see hitting the market today. They were mechanical marvels of technology that could perform many impressive functions within and unto themselves, but artificial intelligence (AI), machine learning, true driver personalization and external data exchange capabilities were still conceptual. In the time since, driver assistance systems, the internet and new human-machine-interfaces (HMI) have proliferated in vehicles at all levels in the market. The “connected car” period of the last few years is quickly morphing into the “smart car” era.
The key element to making cars “smart” will be a deep learning AI platform that thoughtfully integrates the car’s HMI with various third-party virtual assistants, vehicle sensors, off-board content, as well as user habits and preferences. Smart cars will possess an automotive assistant that can connect a variety of inputs and data sources. Its value will be judged by how elegantly it understands and communicates with its users using speech and natural language, while accessing and delivering a world of information from a wide range of “expert” sources to instantly and/or proactively deliver the right answer, content or action. In essence, the assistant is agnostic and truly built to assist the driver — and, because it’s optimized for the automotive environment, it comes equipped with a level of expertise about fuel levels and proximity to the nearest gas station, or why that exclamation point on the dashboard is lit up…again.
To be incredibly effective, the automotive assistant must also know and work with the most appropriate sources for any given inquiry and be able to communicate with them. In other words, it needs to be interoperable with a wide range of apps, assistants and platforms that extend beyond the car. In fact, with the sheer amount of specialized bots and virtual assistants becoming available as part of the proliferation of the Internet of Things (IoT) across a number of vertical markets — banking, retail, insurance, healthcare, etc. — an automotive assistant that can communicate and work with these diverse services will drive incredible value for OEMs and consumers alike.
Interoperability is a logical end-state that the full IoT ecosystem will eventually need to embrace to be successful. Assistants and bots will benefit from working together because consumers will ultimately decide they don’t want to be forced to choose — they want to have options and choice on their own terms. A humanized way to think of the relationship between the automotive assistant and its counterparts in the extended mobile realm could be the one between the general contractor and sub-contractors on a construction project. The general contractor may well possess the skills to, for instance, design an electrical system or install plumbing, but his 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 relationships he has 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 coordinating all pieces of the connected world ecosystem.
The automotive assistant greatly improves user experiences using two other very important modern AI advancements, “personalization” and “contextualization.” Personalization concerns learning particular traits, likes and preferences of individual users, and using this knowledge to make informed recommendations that better match their needs. Contextualization concerns the conditions and circumstances that surround the user at a given moment—inside the car and outside the car—because aspects of both might affect the decision for or against a certain option. Your automotive assistant, for example, might learn that you treat yourself to a particular set of fast food on evenings after you leave work, have a client meeting scheduled on your calendar and not enough time to visit home first. The next time these conditions occur, it may proactively suggest a few selectively chosen fast food restaurant options along the route to your meeting for you to consider stopping at, essentially reducing or eliminating altogether any effort on your part to figuring out the answer to “what and where can I grab something I want to eat on my way?” The response: “How does Five Guys tonight sound?”
Taken together, rapidly improving advancements in AI interoperability, personalization and contextualization will allow automotive assistants to significantly enhance car mobility for drivers and passengers. They will provide broad access to highly relevant and timely assistance that will help drivers make better and faster decisions safely, as well as enhance the comfort and convenience of all occupants.
Bob Schassler is the executive vice president and general manager at Nuance Mobile.