Is AI Accurate?

ESTROGEN GUY

ESTROGEN GUY

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No, artificial intelligence (AI) is not 100% accurateand is prone to errors, including false positives, false negatives, and hallucinations. AI operates on probabilities and historical data, not certainty, and its performance is influenced by factors like training data bias, the complexity of the task, and incomplete information. It is crucial to recognize these limitations and use AI as a tool for assistance rather than a definitive source of truth.

Why AI Isn't 100% Accurate
    • Probabilistic Nature:
      AI models are based on statistical probabilities and approximations, not exact formulas.
    • Training Data Limitations:
      AI models learn from historical data, which can contain errors, biases, or be incomplete, leading to inaccurate outputs.
    • Hallucinations:
      Generative AI models can sometimes "hallucinate," meaning they produce incorrect, fabricated, or nonsensical information.
    • Complexity:
      Real-world scenarios involve complex data and conditions, making it challenging for AI to achieve perfect accuracy.
Implications of AI Inaccuracy
    • False Positives and Negatives:
      AI systems can incorrectly identify something as either present when it isn't (false positive) or absent when it is there (false negative).
    • Misinformation:
      Inaccurate AI-generated content can contribute to the spread of misinformation if not critically evaluated.
    • Need for Verification:
      It is essential to verify information and outputs from AI, especially in critical applications where absolute accuracy is required.
How to Use AI Responsibly
    • Understand its Limitations:
      Be aware that AI is not infallible and can make mistakes.
    • Use as a Tool:
      View AI as a helpful assistant rather than a source of absolute truth or a substitute for human judgment.
    • Verify Information:
      Always cross-reference AI-generated information with reliable sources, especially for important decisions.
    • Apply Critical Thinking:
      Develop your critical thinking skills to evaluate AI outputs, identify potential inaccuracies, and understand the context of the information provided.
 
An AI model is only as good as its training data and parameters.
Gemini (Google's AI) was biased to show diversity over objective fact in earlier models.

google-ai-generating-race.png
 
Andrewgen_Receptors said:
An AI model is only as good as its training data and parameters.
Gemini (Google's AI) was biased to show diversity over objective fact in earlier models.

google-ai-generating-race.png
Click to expand...
Exactly but as time goes on and AI gets trained on more content then it will become more accurate. Definitely an AI is only as good as the data sets it's trained on. The early AI models created in 1950s and 60s were quite primitive in comparison.
 
MindlessWork said:
AI research originated in the late '50s.
Click to expand...
The bad thing is companies are using AI. My experience is longer and frustrating wait times. Some companies will not give you options of a live person. They want to email you a reply. I’m sure if we stop paying the bills. Will get a live person calling us. Things are just nuts all over the world. But this is written already. These days will come and go.
 
Someone use AI to correct a letter I sent out. I was so mad at the person Number one, she gave one of my business address to AI. 2. My whole entire point of the letter. AI changed the narrative. I was so mad at this woman.
 
MindlessWork said:
AI research originated in the late '50s.
Click to expand...
Well, you sent me down a rabbit hole trying to prove you wrong. You aren't.

Original AI research was all theoretical and anticipated to be based on explicit parameters and decision making.
This just couldn't work for a number of reasons.

Current AI is based off machine learning and neural networks, particularly deep learning. It's mostly pattern recognition.

None of this actually aligns with the real definition of Artificial Intelligence, though. We're still lifetimes away from that, thankfully.
 
Andrewgen_Receptors said:
Well, you sent me down a rabbit hole trying to prove you wrong. You aren't.

Original AI research was all theoretical and anticipated to be based on explicit parameters and decision making.
This just couldn't work for a number of reasons.

Current AI is based off machine learning and neural networks, particularly deep learning. It's mostly pattern recognition.

None of this actually aligns with the real definition of Artificial Intelligence, though. We're still lifetimes away from that, thankfully.
Click to expand...
Exactly, as time went on new LLM models and algorithms got developed so that natural language queries can be made to the AI engine. True artificial intelligence is indeed a long way off but as of now it's gotten quite usable.
 
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