How much value can our decisions create? We argue that unless our current understanding of physics is wrong in fairly fundamental ways, there exists an upper limit of value relevant to our decisions. First, due to the speed of light and the definition and conception of economic growth, the limit to economic growth is a restrictive one. Additionally, a related far larger but still finite limit exists for value in a much broader sense due to the physics of information and (...) the ability of physical beings to place value on outcomes. We discuss how this argument can handle lexicographic preferences, probabilities, and the implications for infinite ethics and ethical uncertainty. (shrink)

This is a short presentation by the Guest Editors of the series of Special Issues of the journal _Philosophies_ under the common title “Contemporary Natural Philosophy and Philosophies” in which we present Part 2. The series will continue, and the call for contributions to the next Special Issue will appear shortly.

In this article, the authors critically analyze the content of the physical interpretation of information developed by the Polish researcher R. Krzanowski. They demonstrate the connection of Krzanowski’s views with the views of R. Landauer and T. Stonier on the place of information in the context of physical reality and the mode of its existence. The research is aimed at identifying the theoretical difficulties that arise when accepting the principles of Krzanowski’s understanding of information. These difficulties relate to the connection (...) of the concept of information with the concepts of structure and meaning, as well as understanding the epistemic role of information in general. The authors also consider the list of topical issues of the philosophy of information, given by Krzanowski in his article “What is Physical Information?” published in 2020: a number of proposed questions are speculative-metaphysical, which makes it possible to criticize his position for trying to «confirm» and «substantiate» metaphysical assumptions through the use of theoretical tools and data from specific scientific disciplines. (shrink)