Artificial intelligence (AI) has come a long way in the last few years, bridging the gap between theoretical conversations and what is now practical possibilities, and nowhere are the possibilities more exciting than in the automotive industry. Between the design of the cars we currently drive (and the ones we’ll own in the future) and the process of manufacturing them, there is a lot of room for AI to expand, create efficiencies and make the process of auto-making and driving safer overall. The question is becoming when, not if, artificial intelligence will take over the automotive industry — and will manufacturers, suppliers and automakers be ready?
Breaking Down AI
Artificial intelligence can be broken down into the four categories most relevant to the automotive industry. The first is machine learning, or algorithms that learn from examples and experience, rather than predetermined processes. Machine learning forms one of the essential frameworks of AI and can be found in many of the technologies we already use in daily life. Deep learning, on the other hand, is a subset of machine learning formally patterned after human neural networks and serves as the second category. Deep learning allows computers to make accurate predictions about behavior; given the increasing amount of data made available via social networks and smartphones, deep learning is the fastest growing part of AI.
The third category is natural language processing, or the ability for computers to recognize, interpret and respond to varied types of human speech. This includes accented speech, dialects, and slang — hence the title “natural” — and has come a long way in the last decade alone. Fourth and finally is machine vision, which is the ability of computers to perceive and process visual cues like images, spatial distance, defects and speed — even when humans cannot.
When thinking about the power of artificial intelligence, top of mind for many are autonomous vehicles, which operate with minimal interference from human drivers. Artificial intelligence processes are now synthesizing data in order to learn how best to respond — and how humans respond — to driving conditions. For automobiles, this includes predicting how other cars will behave, how to gauge weather conditions, understanding road issues and more. Eventually, this could change many automotive-driven industries, from taxis and rideshare vehicles to delivery companies and public transportation.
Vehicle manufacturers are also looking to AI to help people avoid human errors that lead to accidents. For example, safety features linked to automatic braking, collision avoidance systems, pedestrian and cyclist alerts, cross-traffic alerts and intelligent cruise controls are some of the other features being powered by AI. By working as an assistant to a human driver, these artificial intelligence advancements benefit everyone on the road.
Another significant contribution artificial intelligence is making is the use of biometrics to analyze driver security. This kind of technology would require a car to drive only when it recognizes a certain voice, which could be used to increase safety in ridesharing. Artificial intelligence could also track and synthesize biometric data about alertness and attention, preventing possible accidents when the vehicle senses the driver is unsafe to operate it.
The common thread through all of these applications is the increased safety of everyone on the road; this is a trend in AI development, and will likely be the focus for the foreseeable future. Concepts like vehicle-to-vehicle (V2V) technology, where connected cars will have the ability to communicate with one another, are being developed; this technology could reduce accidents by connecting vehicles, alerting the network when something goes wrong, and allowing drivers (or even the vehicles) to take preventive measures.
AI Requirements and Benefits
The software, machines and parts powered by AI technology may require fewer components to operate, but they will require more specialized employees in order to program and troubleshoot them. Today, a significant bottleneck with the adoption of autonomous vehicles is the shortage of software engineers who are required to develop the algorithms and apply the AI for these complex systems. Many companies are attempting to clear this hurdle right now through “aqui-hiring,” or buying out smaller tech companies with an established team to help build the organizations’ future capabilities in preparation for a much different automotive landscape.
For most, the benefits of artificial intelligence outweigh the drawbacks. Increased safety and efficiency are a siren song not easily resisted — especially since they extend beyond vehicles all the way to manufacturing. One study estimates that artificial intelligence in manufacturing could reduce labor hours by 0.5-1.5% while significantly increasing productivity; AI can also improve safety, generate ideas, make predictions about calibrations and repairs and more. Machine vision in manufacturing, for example, is being developed to correctly identify microscopic errors (notably in circuit boards) that the human eye cannot detect.
Another example is preventive maintenance. Most industrial equipment is typically serviced on a fixed schedule, regardless of actual operating condition, resulting in wasted labor and risk of unexpected and undiagnosed equipment failures. Now this equipment can be fitted with sensors and networked together, allowing these devices to be monitored, analyzed and modeled for improved performance and service. The large amounts of data this creates can now be analyzed using AI in order to generate predictive analytics in order to maximize equipment efficiency and avoid unwanted equipment downtime.
Of course, given enough time, the manufacturing process could be reinvented with AI so much so that human laborers are no longer needed, at least not to perform the same jobs. Robotics and AI processes could eventually replace the need for low-skill workers, which of course has the potential to negatively impact the labor force in the short term. In the long term, the idea is to re-train those workers for higher level tasks.
Artificial intelligence will fundamentally change the automotive landscape; from manufacturing to the operation of vehicles, the increased efficiency, safety and productivity spell out a future that may completely defy our present understanding of how the industry works. The smartest choice for vehicle manufacturers and automotive suppliers is to consider the benefits of leveraging artificial intelligence technologies to improve their day-to-day operations, future outlooks and overall success.