What are the limits of machine learning in traffic safety?

What are the limits of machine learning in traffic safety?

Machine learning can analyze data and predict patterns, but it has limitations like data bias and lack of real-world adaptability.

Can machine learning handle unpredictable traffic situations?

Not always. Machine learning relies on historical data, so it may struggle with novel or rare traffic scenarios.

How does data quality affect machine learning in this context?

Data quality is crucial; poor data can lead to inaccurate models, which may compromise safety recommendations.

Are there ethical concerns with using AI in traffic safety?

Yes, ethical concerns include accountability for accidents and the potential for biased decision-making based on flawed data.

What advancements are being made to improve these limitations?

Researchers are working on better algorithms, more diverse datasets, and integrating human insights to enhance AI's effectiveness.