SISA Cyber Security for AI CSPAI Question # 7 Topic 1 Discussion
CSPAI Exam Topic 1 Question 7 Discussion:
Question #: 7
Topic #: 1
During the development of AI technologies, how did the shift from rule-based systems to machine learning models impact the efficiency of automated tasks?
A.
Enabled more dynamic decision-making and adaptability with minimal manual intervention
B.
Enhanced the precision and relevance of automated outputs with reduced manual tuning.
C.
Improved scalability and performance in handling diverse and evolving data.
D.
Increased system complexity and the requirement for specialized knowledge,
The transition from rigid rule-based systems, which rely on predefined logic and struggle with variability, to machine learning models introduced data-driven learning, allowing systems to adapt dynamically to new patterns with less human oversight. This shift boosted efficiency in automated tasks by enabling real-time adjustments, such as in spam detection where ML models evolve with threats, unlike static rules. It minimized manual rule updates, fostering scalability and handling complex, unstructured data effectively. However, it introduced challenges like interpretability needs. In GenAI evolution, this paved the way for advanced models like Transformers, impacting sectors by automating nuanced decisions. Exact extract: "The shift enabled more dynamic decision-making and adaptability with minimal manual intervention, significantly improving the efficiency of automated tasks." (Reference: Cyber Security for AI by SISA Study Guide, Section on AI Evolution and Impacts, Page 20-23).
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