All of Tomáš Gavenčiak's Comments + Replies

The transitions in more complex, real-world domains may not be as sharp as e.g. in chess, and it would be useful to model and map the resource allocation ratio between AIs and humans in different domains over time. This is likely relatively tractable and would be informative for prediction of future development of the transitions. 

While the dynamic would differ between domains (not just the current stage but also the overall trajectory shape), I would expect some common dynamics that would be interesting to explore and model.

A few examples of concrete... (read more)

Seeing some confusion on whether AI could be strictly stronger than AI+humans: A simple argument there may be that - at least in principle - adding more cognition (e.g. a human) to a system should not make it strictly worse overall. But that seems true only in a very idealized case.

One issue is incorporating human input without losing overall performance even in situation when the human's advice is much wore than the AI's in e.g. 99.9% of the cases (and it may be hard to tell apart the 0.1% reliably).

But more importantly, a good framing here may be the opt... (read more)

1Tomáš Gavenčiak
The transitions in more complex, real-world domains may not be as sharp as e.g. in chess, and it would be useful to model and map the resource allocation ratio between AIs and humans in different domains over time. This is likely relatively tractable and would be informative for prediction of future development of the transitions.  While the dynamic would differ between domains (not just the current stage but also the overall trajectory shape), I would expect some common dynamics that would be interesting to explore and model. A few examples of concrete questions that could be tractable today: * What fraction of costs in quantitative trading is expert analysts and AI-based tools? (incl. their development, but perhaps not including e.g. basic ML-based analytics) * What fraction of costs is already used for AI assistants in coding? (not incl. e.g. integration and testing costs - these automated tools would point to an earlier transition to automation that is not of main interest here) * How large fraction of costs of PR and advertisement agencies is spent on AI, both facing customers and influencing voters? (may incl. e.g. LLM analysis of human sentiment, generating targeted materials, and advanced AI-based behavior models, though a finer line would need to be drawn; I would possibly include experts who operate those AIs if the company would not employ them without using an AI, as they may incur significant part of the cost) While in many areas the fraction of resources spent on (advanced) AIs is still relatively small, it is ramping up quite quickly and even those may provide informative to study (and develop methodology and metrics for, and create forecasts to calibrate our models).

The concept of "interfaces of misalignment" does not mainly point to GovAI-style research here (although it also may serve as a framing for GovAI). The concrete domains separated by the interfaces in the figure above are possibly a bit misleading in that sense:

For me, the "interfaces of misalignment" are generating intuitions about what it means to align a complex system that may not even be self-aligned - rather just one aligning part of it. It is expanding not just the space of solutions, but also the space of meanings of "success". (For example, one ext... (read more)

Complexity indeed matters: the universe seems to be bounded in both time and space, so running anything like Solomonoff prior algorithm (in one of its variants) or AIXI may be outright impossible for any non-trivial model. This for me significantly weakens or changes some of the implications.

A Fermi upper bound of the direct Solomonoff/AIXI algorithm trying TMs in the order of increasing complexity: even if checking one TM took one Planck time on one atom, you could only check cca 10^250=2^800 machines within a lifetime of the universe (~10^110 years until... (read more)