The author also provides five insights into the issues with AI in vehicles, including the shift of human error from operation to coding, the unpredictability of AI failure modes, the inability of AI to make judgments under uncertainty, the importance of maintaining AI, and the system-level implications of AI. The author calls for more government oversight and regulation, and for the recruitment of technically competent personnel in government agencies to understand and manage AI technologies effectively.
Key takeaways:
- Artificial intelligence (AI) in vehicles has been linked to at least 25 confirmed deaths and hundreds of injuries and instances of property damage in the United States.
- AI failure modes are hard to predict and can lead to accidents, such as sudden braking or misjudging the actions of other vehicles.
- Maintaining AI models is crucial as they need to be constantly updated to reflect new types of vehicles, traffic patterns, etc. This is known as 'model drift' and can lead to serious consequences if not addressed.
- Regulation of AI in vehicles is currently lacking, partly due to a lack of technical competence among regulators. The author suggests improving pay and bonus structures, embedding government personnel in university labs, and offering scholarships for undergraduates who agree to serve in the government to address this issue.