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Universal Ethics: Organized Complexity as an Intrinsic Value

Jean-Paul Delahaye; Clément Vidal

ABSTRACT: How can we think about a universal ethics that could be adopted by any intelligent being, including the rising population of cyborgs, intelligent machines, intelligent algorithms, or even, potentially, extraterrestrial life? We generally give value to complex structures, to objects resulting from long periods of work, and to systems with many elements and with many links finely adjusted. These include living beings, books, works of art, and scientific theories. Intuitively, we want to keep, multiply, and share such structures, as well as prevent their destruction. Such objects have value not because more information (in bits) would simply mean more value. Instead, they have value because they require a long computational history – assuming that the numerous interactions governing their construction constitute a computation – and they display what we call organized complexity. To propose the foundations of a universal ethics based on the intrinsic value of organized complexity, we first discuss conceptions of complexity, and argue that Charles Bennett’s logical depth is a satisfactory notion of what we are looking for. We then put forward three fundamental imperatives: to preserve, augment, and recursively promote organized complexity. We show a broad range of applications with human, non-human, and non-living examples. Finally, we discuss some specific issues of our framework such as the distribution of complexity, the managing of copies and erasures, and how our universal ethics tackles classical ethical issues. In sum, we propose a clear, homogenous, and consistent ethical foundation that can integrate many universal ethics desiderata.


KEYWORDS: Philosophy of information, organized complexity, Kolmogorov complexity, logical depth, ethics, universal ethics, infoethics, thermoethics, environmental ethics, transhumanism

Final version, forthcoming in Evolution, Development and Complexity: Multiscale Evolutionary Models of Complex Adaptive Systems, edited by G. Georgiev, C. L. F. Martinez, M. E. Price, & J. M. Smart. Springer Publishing.
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