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Asklemmy @lemmy.ml Melatonin @lemmy.dbzer0.com

Since the Turing Test seems NOT to be an accurate way to check for true AI, what is? What's will be the indicator that tells us it's arrived? I can't imagine; everything seems falsifiable.

Edit: After reading the discussion, I figured I'd let GPT4 speak for itself:

The quest to identify true artificial intelligence (AI) indeed presents challenges, especially as AI models become more sophisticated. Let's explore some indicators that researchers and practitioners consider when assessing AI systems:

  1. Understanding Context and Meaning:

    • True AI should demonstrate an understanding of context and meaning. It should not merely generate plausible-sounding sentences but also comprehend the content it produces.
    • A system that can engage in nuanced conversations, infer intent, and provide relevant responses based on context would be a strong indicator of advanced AI.

  2. Generalization and Adaptability:

    • An AI system that can generalize from its training data and adapt to novel situations is valuable.
    • True AI should not be limited to memorizing specific examples but should exhibit flexibility in handling diverse scenarios.

  3. Creativity and Novelty:

    • Creativity is a hallmark of human intelligence. An AI system that generates novel ideas, art, or solutions beyond its training data suggests progress.
    • For instance, AI-generated poetry, music, or visual art that resonates with human emotions could be an indicator.

  4. Ethical Decision-Making:

    • True AI should navigate ethical dilemmas. It should consider consequences, fairness, and societal impact.
    • An AI system that can weigh trade-offs and make ethical choices aligning with human values is a positive sign.

  5. Self-Awareness and Self-Improvement:

    • While self-awareness akin to human consciousness remains elusive, an AI system that can self-assess its performance and seek improvement is promising.
    • Continuous learning, adaptation, and self-correction are essential traits.

  6. Transparency and Explainability:

    • True AI should be transparent about its decision-making process. It should provide explanations for its outputs.
    • Efforts to develop interpretable AI models and techniques for explaining their predictions contribute to trustworthiness.

  7. Robustness and Safety:

    • AI systems must handle adversarial inputs, noisy data, and edge cases gracefully.
    • Robustness against attacks and safety precautions to prevent harmful behavior are critical indicators.

  8. Human-AI Collaboration:

    • Rather than replacing humans, true AI should complement human abilities.
    • Systems that collaborate effectively with humans—such as AI assistants, co-creative tools, or medical diagnostics—demonstrate progress.

  9. Quantifiable Metrics:

    • Researchers propose various metrics to assess AI capabilities, such as perplexity, BLEU score, F1 score, and accuracy.
    • However, no single metric captures the full spectrum of intelligence.

  10. Detection Tools:

    • Researchers are developing tools to differentiate between human- and AI-generated text.
    • These tools analyze features like fluency, word frequency, punctuation patterns, and sentence length¹.
    • While imperfect, they contribute to identifying AI-generated content.

In summary, the arrival of true AI may not be a singular event but a gradual evolution marked by advancements in the above dimensions. As AI continues to progress, our understanding of its capabilities will evolve, and new indicators may emerge.

Source: Conversation with Bing, 2/29/2024 (1) How to spot AI-generated text | MIT Technology Review. https://www.technologyreview.com/2022/12/19/1065596/how-to-spot-ai-generated-text/. (2) Intelligent Supertrend (AI) - Buy or Sell Signal — Indicator by .... https://www.tradingview.com/script/q9244PAH-Intelligent-Supertrend-AI-Buy-or-Sell-Signal/. (3) Indicators - True ALGO. https://truealgo.com/indicators/. (4) Improve Key Performance Indicators With AI - MIT Sloan Management Review. https://sloanreview.mit.edu/article/improve-key-performance-indicators-with-ai/. (5) New AI classifier for indicating AI-written text - OpenAI. https://openai.com/blog/new-ai-classifier-for-indicating-ai-written-text/.

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  • Schemas are another alternative to the Turing Test. They use the ambiguity of language to test understanding.

    For example: When the ship hit the iceberg, it sank. What does "it" refer to: the ship or the iceberg?

    When the dog saw the dead rabbit, it hopped. What does "it" refer to: the dog or the rabbit?

    The problem with schemas is that ChatGPT 3.5 passes them with flying colors. And I'm still not convinced it is sentient.

    EDIT: I tried changing the order a bit like this: When the dead rabbit was seen by the dog, it hopped. What does "it" refer to: the rabbit or the dog? ChatGPT 3.5 responded with "In this sentence, "it" refers to the dead rabbit, as it is the subject of the action described (hopping)."

    • Gpt3.5 isn't particularly good.

      Gpt4:

      The sentence "When the dead rabbit was seen by the dog, it hopped" uses "it" in a way that could lead to confusion due to the use of "dead rabbit" earlier in the sentence. Logically, "it" should refer to the subject that can perform the action described by the verb "hopped." Since the rabbit is described as "dead," it cannot perform the action of hopping. Therefore, "it" logically refers to the dog, as it is the only subject capable of hopping in this context. The sentence structure, however, might cause confusion, and it would be clearer if it directly stated the subject performing the action.

      • Here's what Microsoft Copilot which uses ChatGPT 4 said when I asked:

        The phrase “it” in the sentence “when the dead rabbit was seen by the dog, it hopped” refers to the rabbit. This is because the sentence is using a subordinate clause to modify the noun “rabbit”. A subordinate clause is a group of words that provides additional information about the main clause, but cannot stand alone as a complete sentence. In this case, the subordinate clause is “when the dead rabbit was seen by the dog”, which tells us when the rabbit hopped. The word “it” refers back to the rabbit and avoids repetition. Here is an example of a sentence with a subordinate clause and a word that refers back to the main clause: I saw a dog chasing a rabbit in the park. I saw a dog chasing it, which was a rabbit. I hope this helps you understand how to use subordinate clauses and words that refer back to nouns. If you have any other questions, feel free to ask me. 😊

        Edit: I just tried it with asking it to role play as Mr. Spock. Same thing.

        Edit 2: I asked it to role play as a Vulcan. This happened:

        In this intriguing logic puzzle, the key lies in the precise wording. Let us dissect it logically:

        1. Premise: The dead rabbit was seen by the dog.
        2. Result: The it (referring to the entity that hopped) is mentioned.

        Now, let us analyze the options:

        • If "it" refers to the rabbit, then we have a paradox: a dead rabbit cannot hop.
        • If "it" refers to the dog, then the statement makes sense: the dog saw the rabbit and hopped in response.

        Therefore, "it" refers to the dog. The rabbit, alas, remains lifeless. 🐇🐾

        Remember, logic puzzles often hinge on subtle nuances and wordplay. 🤔🖖

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