Though the idea of artificial intelligence (AI) has been around for decades, AI technology is now being applied in numerous industries—including automotive. These uses range from simple tasks to complex applications such as image recognition. As more companies explore the potential value of AI at their organizations, the size of this industry is anticipated to grow significantly. Greater collaboration, awareness, and talent investments can help speed the growth of artificial intelligence technologies.
While there are multiple definitions of AI, the Center for Automotive Research defined AI as: “The use of mathematical algorithms to ingest data, process and characterize it, discover important features or patterns within it, and perform classification and decision-making based on what was discovered” (Bahrani Fard, Dennis, Hong, Fiorelli, & Wallace, 2018).
Based on this definition, AI could be used to discuss a group of technologies for data processing and analysis. Our recommendations fall into three major categories 1) support a collaborative environment, 2) encourage knowledge advancement and awareness, and 3) invest in talent.
In each of these categories, industry, academia, and government needs to work together for the continued growth of AI.
For many years, the Silicon Valley tech hub has attracted tech companies and talent to its region due to the ecosystem that developed surrounding the tech industry.
Similarly, community leaders can support the development of an AI ecosystem in their area by leading efforts to obtain funding for AI-related businesses. Also, these leaders can invest in the leading AI industries, including computer science, engineering, automotive, manufacturing, and health care, to support growth in AI fields.
One critical aspect of supporting the growth of AI is building awareness of the technology and its applications. There are several ways that stakeholders can spread information. One way is to sponsor learning and networking opportunities such as roundtable events, webinars, or social networking hours. Another way academia can be involved is through the sharing of information amongst institutions by setting up conferences, sessions, and workshops to discuss ongoing research and current challenges faced by the industry.
Lastly, stakeholders can support and encourage the use of data for educational purposes. Secure data sharing initiatives could be achieved through multiple partnerships between state governments and industry.
Not surprisingly, to support the continued development of AI, the industry will need to support the education of the future workforce. Industry and academia need to collaborate to continue producing students with the necessary skill sets promptly as AI is a fast-evolving technology.
One recommendation to support collaboration between stakeholders within the industry, academia, and the public sector is to keep on the cutting edge of technology and continue the development of AI curriculum as advancements in this field occur.
Terni Fiorelli is an industry analyst for the Business group atthe Center for Automotive Research (CAR) in Ann Arbor, Mich.
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