Thus, an artificial agent could have a very high level of intelligence, and nevertheless use that intelligence to pursue very odd final goals, including goals that are inimical to the survival of human beings. In other words, there is no guarantee that high levels of intelligence among AIs will lead to a better world for us. The orthogonality thesis has to do with final goals. Today we are going to look at a related thesis: the instrumental convergence thesis. This thesis has to do with sub-goals. The thesis claims that although a superintelligent AI could, in theory, pursue pretty much any final goal, there are, nevertheless, certain sub-goals that it is likely to pursue.
Convergence Theory | Definition, Discussion and Examples
In an era of globalization, it is often assumed increasingly strong selection mechanisms influence the choice and development of governance regime such that they tend to converge over time. In many conventional accounts, heightened competition between states and national economies in an ever-more-integrated global market pit governance regimes against one another in an ever-more-intense competitive struggle. The global diffusion of neoliberal governance is often predicted. This paper discusses convergence and divergence in a concise and comprehensive way. Convergence and Divergence Debate: A Discussion The convergence versus divergence debate has been an ongoing strand of the literature on management in general for decades. Arguably, Max Weber's theory of bureaucracy and rationalization represents one of the earliest contributions to this thesis of long-term convergence in management practice.
Bostrom on Superintelligence (2): The Instrumental Convergence Thesis
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Instrumental convergence is the hypothetical tendency for most sufficiently intelligent agents to pursue potentially unbounded instrumental goals provided that their ultimate goals are themselves unlimited. Instrumental convergence posits that an intelligent agent with unbounded but apparently harmless goals can act in surprisingly harmful ways. For example, a computer with the sole, unconstrained goal of solving an incredibly difficult mathematics problem like the Riemann hypothesis could attempt to turn the entire Earth into one giant computer in an effort to increase its computational power so that it can succeed in its calculations. Proposed basic AI drives include utility function or goal-content integrity, self-protection, freedom from interference, self-improvement , and non-satiable acquisition of additional resources. Final goals, or final values, are intrinsically valuable to an intelligent agent, whether an artificial intelligence or a human being, as an end in itself.