What are the Limitations of Machine Learning in Causal Analysis?

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Discussion Overview

The discussion centers on the limitations of machine learning in causal analysis, exploring the differences between human intuition and machine capabilities in understanding causality. It touches on theoretical implications, practical applications, and the philosophical aspects of intelligence and learning.

Discussion Character

  • Debate/contested
  • Conceptual clarification
  • Exploratory

Main Points Raised

  • Some participants argue that machine learning excels at predictions but struggles with causal analysis, which requires human intuition and judgment.
  • Others contend that human understanding of causality is not universally agreed upon, suggesting that if causality is subjective, then human intuition is necessary for causal analysis.
  • A participant highlights that while humans may not perform causal analysis perfectly, they can generate insights and hypotheses that machines may overlook due to their reliance on existing data.
  • Concerns are raised about the current limitations of machine learning, particularly in tasks requiring adaptability and nuanced understanding, such as driving or language acquisition.
  • Some participants speculate that future AI could potentially match or exceed human intelligence by integrating various cognitive skills, although this remains uncertain.
  • There is a discussion about the nature of human cognition and whether the complexities of human thought can be replicated in AI, with some suggesting that current AI lacks the necessary psychological understanding.
  • One participant proposes that the complexity of human emotions and intuition might be more intricate than tasks currently manageable by AI, raising questions about the feasibility of replicating such processes in machines.

Areas of Agreement / Disagreement

Participants express differing views on the capabilities of machine learning versus human intelligence in causal analysis. There is no consensus on whether machines can ever fully replicate human intuition or if they can achieve a level of understanding comparable to human reasoning.

Contextual Notes

The discussion reveals limitations in the current understanding of causality, the definitions of intelligence, and the potential for future advancements in AI. Participants acknowledge the complexity of human cognition and the challenges in translating these processes into machine learning algorithms.

  • #61
I agree with the concept that machines have no limit, but comparing them to human intelligence seems arbitrary and anthropocentric. We'd also have to make clear that we're talking about very long periods of time. 100 years from now? Yeah, there's a lot of limits and I don't see a Bender Rodriguez strutting down the street in that amount of time, but they'll certainly be driving our cars and flying our planes. 1000 years? Mmm... maybe? 10,000, absolutely.

Of course, assuming humans destroy ourselves, which in theory, we don't have to.

It shouldn't really even be debatable of whether or not an AI could ever match a human. The human brain is a chemical machine, we have programmable maths that describes that chemistry. Given enough computing power, you could build a brain from atoms up inside a computer. It's unlikely we'd ever need to do anything like that and I don't see humanity having that much computing power any time soon, but there's nothing really preventing it in theory. The only real limit is energy and matter.

Natural selection gave us our thought process in about 600 million years, I'd think intelligent design could beat that by several orders of magnitude.I'm weary of AI in the long term. I don't think anyone alive today has to worry about it, but I see it as one of the potential "great filters" for life in the Fermi paradox. I see no reason to fear any individual AI, but the fact that they are immortal means that the number of them will grow very rapidly. I think they'll be very individualized, and be a result of their "upbringing." They'll be as diverse as humans and while I believe that most humans are good. .. Hitler existed.
 
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  • #62
A. Neumaier said:
Many classification problems solved by computers better than by humans are also not well-defined problems.
I don't doubt that at all, but I wouldn't lump all non-well-defined problems in the same category. There are several different degrees of being badly defined, some of which are still perfectly solvable - sometimes even with trivial ease - by some humans, despite all their vagueness.
 
  • #63
Auto-Didact said:
I don't doubt that at all, but I wouldn't lump all non-well-defined problems in the same category. There are several different degrees of being badly defined, some of which are still perfectly solvable - sometimes even with trivial ease - by some humans, despite all their vagueness.
Please give examples.
 
  • #64
A. Neumaier said:
Please give examples.
I'm currently publishing two papers on this topic; will link when they are done.
 

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