Towards Strong AI

Abstract

Strong AI—artificial intelligence that is in all respects at least as intelligent as humans—is still out of reach. Current AI lacks common sense, that is, it is not able to infer, understand, or explain the hidden processes, forces, and causes behind data. Main stream machine learning research on deep artificial neural networks (ANNs) may even be characterized as being behavioristic. In contrast, various sources of evidence from cognitive science suggest that human brains engage in the active development of compositional generative predictive models (CGPMs) from their self-generated sensorimotor experiences. Guided by evolutionarily-shaped inductive learning and information processing biases, they exhibit the tendency to organize the gathered experiences into event-predictive encodings. Meanwhile, they infer and optimize behavior and attention by means of both epistemic- and homeostasis-oriented drives. I argue that AI research should set a stronger focus on learning CGPMs of the hidden causes that lead to the registered observations. Endowed with suitable information-processing biases, AI may develop that will be able to explain the reality it is confronted with, reason about it, and find adaptive solutions, making it Strong AI. Seeing that such Strong AI can be equipped with a mental capacity and computational resources that exceed those of humans, the resulting system may have the potential to guide our knowledge, technology, and policies into sustainable directions. Clearly, though, Strong AI may also be used to manipulate us even more. Thus, it will be on us to put good, far-reaching and long-term, homeostasis-oriented purpose into these machines.

Artificial Intelligence and a Weapon of Mass Destruction

“…The development of strong artificial intelligence 13 systems should only happen when we are convinced that their results will be positive. ", and their risks are manageable" -it is written in the appeal [17]. In addition to Elon Musk, thousands of people have signed the public appeal.…”

Philosophy of future: analytical overview of interaction between education, science, and artificial intelligence in the context of contemporary challenges

“…From the role of AI and its capabilities, two different types can be distinguished -Strong AI and Weak AI (Müller, 2024). Strong AI, or human-level AI, refers to a hypothetical form of AI that possesses the ability to understand, learn, and reason across a wide range of areas at a level comparable to human intelligence (Butz, 2021). Strong AI demonstrates general cognitive capabilities similar to those of humans, including perception, language understanding, problem-solving, creativity, and self-awareness (Fjelland, 2020).…”

Adaptivity: a path towards general swarm intelligence?

“…This parallel leads us to believe that breakthroughs in AGI development will concomitantly lead to more adaptive outcomes for swarms. For instance, Butz (2021) argues that current (narrow) machine learning “optimizes the best possible strategy within the status quo” and that current algorithms are “reflective rather than prospective.” On the other hand, strong AI needs to be predictive to infer the hidden causes behind its observations and explain the reasoning behind its decision-making process. This offers us prospective routes to improve the current SI status quo.…”