5.1.10. Explain basic concepts related to artificial intelligence (AI). (Obj. 4.10)

💡 First Principle: A modern technician should understand the basic concepts, applications, and limitations of AI as it becomes more integrated into IT systems.

Artificial Intelligence (AI) is rapidly becoming a part of the technology landscape, and as a technician, you need a foundational understanding of what it is, how it's being used, and its potential pitfalls. For the A+ exam, this is a high-level conceptual topic.

Key concepts to understand:

• What is AI? At a basic level, AI refers to computer systems that can perform tasks that normally require human intelligence, such as learning, reasoning, problem-solving, and understanding language. This is often powered by Machine Learning (ML), where a system is "trained" on a massive dataset to recognize patterns, rather than being explicitly programmed for a specific task.
• Application Integration: You already use AI every day. It's integrated into:
  • Predictive Text: On your smartphone, suggesting the next word you might type.
  • Chatbots: On websites, providing automated customer support.
  • Recommendation Engines: On Netflix or Amazon, suggesting what you might want to watch or buy next.
  • Generative AI: Tools like ChatGPT or Google Gemini that can generate new text, images, or code based on a prompt.
• Limitations and Risks: It is crucial to understand that AI is not magic and has significant limitations.
  • Bias: AI models are trained on data created by humans, and they can inherit and even amplify the biases present in that data.
  • Hallucinations: Generative AI models can sometimes confidently state incorrect information, essentially "making things up." You cannot blindly trust every output from an AI. Always verify critical information.
  • Accuracy: The accuracy of an AI depends heavily on the quality and quantity of its training data.
  • Data Privacy: This is a major concern. You should never enter sensitive, confidential, or proprietary company or customer information into a public AI model (like the free version of ChatGPT). That data could be used to train the model further and could potentially be exposed. Companies often use private, internal instances of AI models to mitigate this risk.

Technician's Perspective: As an IT support professional, you might use AI in several ways. You could use a generative AI to help you write a PowerShell script, to summarize a long technical document, or to brainstorm potential causes for a strange troubleshooting issue. However, you must always apply your own expertise. Use the AI as a very knowledgeable but sometimes unreliable assistant. You must review the script it writes for errors, fact-check its troubleshooting suggestions, and ensure any communication it helps you draft is accurate and professional. Understanding its limitations is key to using it effectively and safely.

Reflection Question: Why is it a critical security concern to avoid entering sensitive company or customer data into public AI models like ChatGPT?