Scenarios and branch points to future machine intelligence

TL;DR

This paper explores four major future scenarios for machine intelligence, analyzing how different constraints and societal factors could lead to diverse outcomes such as a singleton, multipolar, ecosystem, or upper-bound scenario.

Contribution

It introduces a comprehensive framework of four possible future scenarios for machine intelligence and identifies six key constraints that influence these outcomes.

Findings

Identifies four major future scenarios for machine intelligence.

Highlights six constraints that act as branch points between scenarios.

Provides a structured way to analyze potential futures of AI development.

Abstract

We discuss scenarios and branch points to four major possible consequences regarding future machine intelligence; 1) the singleton scenario where the first and only super-intelligence acquires a decisive strategic advantage, 2) the multipolar scenario where the singleton scenario is not technically denied but political or other factors in human society or multi-agent interactions between the intelligent agents prevent a single agent from gaining a decisive strategic advantage, 3) the ecosystem scenario where the singleton scenario is denied and many autonomous intelligent agents operate in such a way that they are interdependent and virtually unstoppable, and 4) the upper-bound scenario where cognitive capabilities that can be achieved by human-designed intelligent agents or their descendants are inherently limited to the sub-human level. We identify six major constraints that can form branch points to these scenarios; (1) constraints on autonomy, (2) constraints on the ability to improve self-structure, (3) constraints related to thermodynamic efficiency, (4) constraints on updating physical infrastructure, (5) constraints on relative advantage, and (6) constraints on locality.