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Story Feedback Request: The Policy - Emergent Alignment, Recursive Cognition, and AGI Trajectories
queelius10

I need to fix the markup on this document. Sorry, I was thinking it would render markdown. I can't fix it now, will get to it later.

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How Should We Use Limited Time to Maximize Long-Term Impact?
queelius30

Thank you, mishka, for your thoughtful response. You’ve given me a lot to chew on, particularly regarding the potential of focusing on chemotherapy treatment timing. While I’ve explored AI-driven health research, I hadn't fully appreciated how important treatment timing, diet, exercise, and other factors may be for people in my situation.

There’s a mountain of data in this area, and using AI to predict salient data could potentially lead to improvements in how we approach chemotherapy. This seems like a practical and timely research direction, assuming it is still somewhat niche.

I appreciate your input.

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3mishka
More concretely (this is someone's else old idea), what I think is still not done is the following. Chemo kills dividing cells, this is why the rapidly renewing tissues and cell populations are particularly vulnerable. If one wants to spare one of those cell types (say, a particular population of immune cells), one should take the typical period of its renewal, and use that as a period of chemo sessions (time between chemo sessions, a "resonance" of sorts between that and the period of the cell population renewal for the selected cell type). Then one should expect to spare most of that population (and might potentially be able to use higher doses for better effect, if the spared population is the most critical one; this does need some precision, not a typical today's "relaxed logistics" approach where a few days this or that way in the schedule is nothing to worry about). I don't know if that ever progressed beyond the initial idea... (That's just one example, of course, there is a lot of things which can be considered and, perhaps, tried.)
When is a mind me?
queelius20

Intriguing post, but we should approach these topics with extreme epistemic humility. Our understanding is likely far more limited and confused than we realize:

1. Abstractions vs. reality: Concepts like "self" and "consciousness" are abstractions, not reality. As Kosoy analogizes, these might be like desktop icons - a user interface bearing little resemblance to underlying hardware.

2. Mathematical relations: Notions of "copy" may be a confused way to discuss identity. "Consciousness" could be a mathematical relation where only identities exist, with "copie... (read more)

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Richard_Kennaway159

I'm reminded of 1984, in a quotation I've had occasion to post before:

'You do not exist,’ said O’Brien.

Once again the sense of helplessness assailed him. He knew, or he could imagine, the arguments which proved his own nonexistence; but they were nonsense, they were only a play on words. Did not the statement, ‘You do not exist’, contain a logical absurdity? But what use was it to say so? His mind shrivelled as he thought of the unanswerable, mad arguments with which O’Brien would demolish him.

‘I think I exist,’ he said wearily. ‘I am conscious of

... (read more)
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1Thomas
  Or everyone?
queelius's Shortform
queelius40

Newcomb-like Problems in Algorithmic Trading: A New Angle?

I've been pondering the applicability of Newcomb-like problems in real-world systems, specifically algorithmic trading. Could these decision theory problems offer insights into the financial markets?

I'm particularly intrigued by the role of randomization in trading algorithms. Could this be seen as a strategy to 'defeat' a Newcomb-like predictor, making algorithms more robust against exploitation?

I'm new here and would value your insights. Is this a perspective worth diving deeper into?

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3Dagon
Interesting thought, but use of randomness in adversarial games is a very old idea, and applies to CDT just as well as other decision theories.  It IS part of strategies to defeat prediction, but it's not Newcomb-like.