Title: Describe the capabilities and limitations of AI.
Course: Artificial Intelligence (25901-I) > Section: Exploring the Foundations of Artificial Intelligence (AI)

Description should include

- capabilities such as
  - natural language processing (e.g., text-to-speech, voice recognition, language translation, predictive text)
  - data analysis
  - data fusion
  - image recognition and machine vision
  - autonomous systems (e.g., drones, self-driving cars)
  - pattern and trend identification
  - digital twins
  - automation
- limitations such as
  - data dependency
  - resource-intensive operation (e.g., environmental impacts)
  - inaccuracy or false results
  - algorithmic bias
  - complex or uncertain task completion
  - questionable quality of data
  - lack of transparency (i.e., AI can produce a result but not explain why)
  - lack of humanity (operates solely through data-driven calculations), preventing
    - contextual (e.g., social, cultural) understanding and understanding of nuance
    - creativity and individual perspectives
    - emotional comprehension
    - ethical judgment and morality.

Description should include the concept that both the capabilities and limitations of AI technologies are always evolving.

Teacher Resource: Latest Hype Cycle for Artificial Intelligence Goes Beyond GenAI, Gartner