87 research outputs found
Reductionism and the Universal Calculus
In the seminal essay, "On the unreasonable effectiveness of mathematics in
the physical sciences," physicist Eugene Wigner poses a fundamental
philosophical question concerning the relationship between a physical system
and our capacity to model its behavior with the symbolic language of
mathematics. In this essay, I examine an ambitious 16th and 17th-century
intellectual agenda from the perspective of Wigner's question, namely, what
historian Paolo Rossi calls "the quest to create a universal language." While
many elite thinkers pursued related ideas, the most inspiring and forceful was
Gottfried Leibniz's effort to create a "universal calculus," a pictorial
language which would transparently represent the entirety of human knowledge,
as well as an associated symbolic calculus with which to model the behavior of
physical systems and derive new truths. I suggest that a deeper understanding
of why the efforts of Leibniz and others failed could shed light on Wigner's
original question. I argue that the notion of reductionism is crucial to
characterizing the failure of Leibniz's agenda, but that a decisive argument
for the why the promises of this effort did not materialize is still lacking.Comment: 11 pages, 1 figur
Integrative biological simulation praxis: Considerations from physics, philosophy, and data/model curation practices
Integrative biological simulations have a varied and controversial history in
the biological sciences. From computational models of organelles, cells, and
simple organisms, to physiological models of tissues, organ systems, and
ecosystems, a diverse array of biological systems have been the target of
large-scale computational modeling efforts. Nonetheless, these research agendas
have yet to prove decisively their value among the broader community of
theoretical and experimental biologists. In this commentary, we examine a range
of philosophical and practical issues relevant to understanding the potential
of integrative simulations. We discuss the role of theory and modeling in
different areas of physics and suggest that certain sub-disciplines of physics
provide useful cultural analogies for imagining the future role of simulations
in biological research. We examine philosophical issues related to modeling
which consistently arise in discussions about integrative simulations and
suggest a pragmatic viewpoint that balances a belief in philosophy with the
recognition of the relative infancy of our state of philosophical
understanding. Finally, we discuss community workflow and publication practices
to allow research to be readily discoverable and amenable to incorporation into
simulations. We argue that there are aligned incentives in widespread adoption
of practices which will both advance the needs of integrative simulation
efforts as well as other contemporary trends in the biological sciences,
ranging from open science and data sharing to improving reproducibility.Comment: 10 page
Robust Computer Algebra, Theorem Proving, and Oracle AI
In the context of superintelligent AI systems, the term "oracle" has two
meanings. One refers to modular systems queried for domain-specific tasks.
Another usage, referring to a class of systems which may be useful for
addressing the value alignment and AI control problems, is a superintelligent
AI system that only answers questions. The aim of this manuscript is to survey
contemporary research problems related to oracles which align with long-term
research goals of AI safety. We examine existing question answering systems and
argue that their high degree of architectural heterogeneity makes them poor
candidates for rigorous analysis as oracles. On the other hand, we identify
computer algebra systems (CASs) as being primitive examples of domain-specific
oracles for mathematics and argue that efforts to integrate computer algebra
systems with theorem provers, systems which have largely been developed
independent of one another, provide a concrete set of problems related to the
notion of provable safety that has emerged in the AI safety community. We
review approaches to interfacing CASs with theorem provers, describe
well-defined architectural deficiencies that have been identified with CASs,
and suggest possible lines of research and practical software projects for
scientists interested in AI safety.Comment: 15 pages, 3 figure
Collecting Systematic, Introspective Reports of Pharmacological Effects and Side-Effects
The study of subjective, first-person experience is a topic with both philosophical and practical implications. In this article, I discuss the value of collecting a critical mass of prose or verbal descriptions of introspectively determined, subjective effects of pharmacological agents. I suggest that datasets of introspective reports fit in the modern research landscape at the intersection of biomedical informatics and the emerging discipline of contemplative neuroscience. I compare the current proposal to Descriptive Experience Sampling (DES), discuss relevant methodological and conceptual issues in the study of introspection, and provide a list of questions for directing future investigation
Mammalian Value Systems
Characterizing human values is a topic deeply interwoven with the sciences, humanities, political philosophy, art, and many other human endeavors. In recent years, a number of thinkers have argued that accelerating trends in computer science, cognitive science, and related disciplines foreshadow the creation of intelligent machines which meet and ultimately surpass the cognitive abilities of human beings, thereby entangling an understanding of human values with future technological development. Contemporary research accomplishments suggest increasingly sophisticated AI systems becoming widespread and responsible for managing many aspects of the modern world, from preemptively planning users’ travel schedules and logistics, to fully autonomous vehicles, to domestic robots assisting in daily living. The extrapolation of these trends has been most forcefully described in the context of a hypothetical “intelligence explosion,” in which the capabilities of an intelligent software agent would rapidly increase due to the presence of feedback loops unavailable to biological organisms. The possibility of superintelligent agents, or simply the widespread deployment of sophisticated, autonomous AI systems, highlights an important theoretical problem: the need to separate the cognitive and rational capacities of an agent from the fundamental goal structure, or value system, which constrains and guides the agent’s actions. The “value alignment problem” is to specify a goal structure for autonomous agents compatible with human values. In this brief article, we suggest that recent ideas from affective neuroscience and related disciplines aimed at characterizing neurological and behavioral universals in the mammalian kingdom provide important conceptual foundations relevant to describing human values. We argue that the notion of “mammalian value systems” points to a potential avenue for fundamental research in AI safety and AI ethics
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