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/.

  • Thorny_Insight
    3 months ago

    The goal of AI research has almost always been to reach AGI. The bar for this has basically been human level intelligence because humans are generally intelligent. Once an AI system reaches “human level intelligence” you no longer need humans to develop it further as it can do that by itself. That’s where the threat of singularity, i.e. intelligence explosion comes from meaning that any further advancements happens so quickly that it gets away from us and almost instantly becomes a superintelligence. That’s why many people think that “human level” artificial intelligence is a red herring as it doesn’t stay that way but for a tiny moment.

    What’s ironic about the Turing Test and LLM models like GPT4 is that it fails the test by being so competent on wide range of fields that you can know for sure that it’s not a human because a human could never posses that amount of knowledge.

    • 8ace40@programming.dev
      3 months ago

      I was thinking… What if we do manage to make the AI as intelligent as a human, but we can’t make it better than that? Then, the human intelligence AI will not be able to make itself better, since it has human intelligence and humans can’t make it better either.

      Another thought would be, what if making AI better is exponentially harder each time. So it would be impossible to get better at some point, since there wouldn’t be enough resources in a finite planet.

      Or if it takes super-human intelligence to make human-intelligence AI. So the singularity would be impossible there, too.

      I don’t think we will see the singularity, at least in our lifetime.

      • Thorny_Insight
        3 months ago

        Even if the AI was no more intelligent than humans it would still be a million times faster at processing information due to the nature of how information processing in silicon works compared to brain tissue. It could do in seconds what would take months if not years for a group of human experts. I don’t also see any reason why it would be hard to make it even more intelligent than that. We already have AI systems with superhuman capabilities. They’re just really really good at one thing instead of many which makes it narrow AI and not AGI.

        “Human level intelligence” is a bit vague term anyway. There’s human intelligence like mine and then there’s people like John Von Neuman.