Scientific Progress: Why Getting Closer to Truth Is Not Enough

ABSTRACTThis discussion note aims to contribute to the ongoing debate over the nature of scientific progress. I argue against the semantic view of scientific progress, according to which scientific progress consists in approximation to truth or increasing verisimilitude. If the semantic view of scientific progress were correct, then scientists would make scientific progress simply by arbitrarily adding true disjuncts to their hypotheses or theories. Given that it is not the case that scientists could make scientific progress simply by arbitrarily adding true disjuncts to their hypotheses or theories, it follows that the semantic view of scientific progress is incorrect

Does Scientific Progress Consist in Increasing Knowledge or Understanding?

Bird argues that scientific progress consists in increasing knowledge. Dellsén objects that increasing knowledge is neither necessary nor sufficient for scientific progress, and argues that scientific progress rather consists in increasing understanding. Dellsén also contends that unlike Bird’s view, his view can account for the scientific practices of using idealizations and of choosing simple theories over complex ones. I argue that Dellsén’s criticisms against Bird’s view fail, and that increasing understanding cannot account for scientific progress, if acceptance, as opposed to belief, is required for scientific understanding

Scientific progress despite irreproducibility: A seeming paradox

It appears paradoxical that science is producing outstanding new results and theories at a rapid rate at the same time that researchers are identifying serious problems in the practice of science that cause many reports to be irreproducible and invalid. Certainly the practice of science needs to be improved and scientists are now pursuing this goal. However, in this perspective we argue that this seeming paradox is not new, has always been part of the way science works, and likely will remain so. We first introduce the paradox. We then review a wide range of challenges that appear to make scientific success difficult. Next, we describe the factors that make science work-in the past, present, and presumably also in the future. We then suggest that remedies for the present practice of science need to be applied selectively so as not to slow progress, and illustrate with a few examples. We conclude with arguments that communication of science needs to emphasize not just problems but the enormous successes and benefits that science has brought and is now bringing to all elements of modern society.Comment: 3 figure

Scientific Progress, Understanding, and Knowledge: Reply to Park

Dellsén has recently argued for an understanding-based account of scientific progress, the noetic account, according to which science makes cognitive progress precisely when it increases our understanding of some aspect of the world. I contrast this account with Bird’s ; epistemic account, according to which such progress is made precisely when our knowledge of the world is increased or accumulated. In a recent paper, Park criticizes various aspects of my account and his arguments in favor of the noetic account as against Bird’s epistemic account. This paper responds to Park’s objections. An important upshot of the paper is that we should distinguish between episodes that constitute and promote scientific progress, and evaluate account of scientific progress in terms of how they classify different episodes with respect to these categories

Choosing between traditional and innovative technologies: the case of scientific uncertainty

We study the choice between a traditional technology characterized by known risks and an innovative technology (a geological storages for nuclear wastes, a genetically modified organism or a new treatment in medical science) subject to scientific uncertainty. We assume that the two technologies differ in first period implementation costs, second period risk, and degree of irreversibility, and we study the effect of foreseen scientific progress on the present choice between the two. If the first-period choice is restricted to be 'all or nothing', scientific progress promotes the traditional technology; with constant absolute risk aversion, scientific progress increases the optimal level of the technology with the higher implementation cost.

Critiques of Minimal Realism

Saatsi’s minimal realism holds that science makes theoretical progress. It is designed to get around the pessimistic induction, to fall between scientific realism and instrumentalism, and to explain the success of scientific theories. I raise the following two objections to it. First, it is not clear whether minimal realism lies between realism and instrumentalism, given that minimal realism does not entail instrumentalism. Second, it is not clear whether minimal realism can explain the success of scientific theories, given that it is doubtful that theoretical progress makes success likely. In addition to raising these two objections, I develop and criticize a new position that truly falls between realism and instrumentalism

Measuring progress in robotics: Benchmarking and the ‘measure-target confusion’

While it is often said that robotics should aspire to reproducible and measurable results that allow benchmarking, I argue that a focus on benchmarking can be a hindrance for progress in robotics. The reason is what I call the ‘measure-target confusion’, the confusion between a measure of progress and the target of progress. Progress on a benchmark (the measure) is not identical to scientific or technological progress (the target). In the past, several academic disciplines have been led into pursuing only reproducible and measurable ‘scientific’ results – robotics should be careful to follow that line because results that can be benchmarked must be specific and context-dependent, but robotics targets whole complex systems for a broad variety of contexts. While it is extremely valuable to improve benchmarks to reduce the distance be- tween measure and target, the general problem to measure progress towards more intelligent machines (the target) will not be solved by benchmarks alone; we need a balanced approach with sophisticated benchmarks, plus real-life testing, plus qualitative judgment

Progress toward a cosmic dust collection facility on space station

Scientific and programmatic progress toward the development of a cosmic dust collection facility (CDCF) for the proposed space station is documented. Topics addressed include: trajectory sensor concepts; trajectory accuracy and orbital evolution; CDCF pointing direction; development of capture devices; analytical techniques; programmatic progress; flight opportunities; and facility development