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

The Most Technologically Progressive Decade of the Century

Because of the Depression’s place in both the popular and academic imagination, and the repeated and justifiable emphasis on output that was not produced, income that was not earned, and expenditure that did not take place, it will seem startling to propose the following hypothesis: the years 1929–1941 were, in the aggregate, the most technologically progressive of any comparable period in U.S. economic history.1 The hypothesis entails two primary claims: that during this period businesses and government contractors implemented or adopted on a more widespread basis a wide range of new technologies and practices, resulting in the highest rate of measured peacetime peak-to-peak multifactor productivity growth in the century, and secondly, that the Depression years produced advances that replenished and expanded the larder of unexploited or only partially exploited techniques, thus providing the basis for much of the labor and multifactor productivity improvement of the 1950’s and 1960’s

Building Machines That Learn and Think Like People

Recent progress in artificial intelligence (AI) has renewed interest in building systems that learn and think like people. Many advances have come from using deep neural networks trained end-to-end in tasks such as object recognition, video games, and board games, achieving performance that equals or even beats humans in some respects. Despite their biological inspiration and performance achievements, these systems differ from human intelligence in crucial ways. We review progress in cognitive science suggesting that truly human-like learning and thinking machines will have to reach beyond current engineering trends in both what they learn, and how they learn it. Specifically, we argue that these machines should (a) build causal models of the world that support explanation and understanding, rather than merely solving pattern recognition problems; (b) ground learning in intuitive theories of physics and psychology, to support and enrich the knowledge that is learned; and (c) harness compositionality and learning-to-learn to rapidly acquire and generalize knowledge to new tasks and situations. We suggest concrete challenges and promising routes towards these goals that can combine the strengths of recent neural network advances with more structured cognitive models.Comment: In press at Behavioral and Brain Sciences. Open call for commentary proposals (until Nov. 22, 2016). https://www.cambridge.org/core/journals/behavioral-and-brain-sciences/information/calls-for-commentary/open-calls-for-commentar

Neuroscience and Education: The Importance of a Christian Understanding of Human Persons

The increased research in the neurosciences has affected the discipline of education in numerous ways, with publications translating this research into classroom practices. A caution is given to Christian educators to carefully reflect upon how this research influences our view of human persons and what difference this view makes in the teaching and learning process. The purpose of this paper is (1) to examine some of the ways that neuroscience is speaking into the discipline of education, particularly in understanding the capabilities and processes of the learner; (2) to develop an awareness of how this affects our understanding of persons; and (3) to establish the necessity for the preparation of future educators with a distinctly Christian perspective of the human constitution

Frontiers of finance: Evolution and efficient markets

In this review article we explore several recent advances in the quantitative modeling of financial markets. We begin with the Efficient Markets Hypothesis and describe how this controversial idea has stimulated a number of new directions of research, some focusing on more elaborate mathematical models that are captable of rationalizing the empirical facrts, others taking a completely different different tack in rejecting rationality altogether. One of the most promising directions is to view financial markets from a biological perspective and, specifically, with an evolutionary framework in which markets, instruments, institutions, and investors interact and evolve dynamically according to the "law" of economic selection. Under this view, financial agents compete and adapt, but they do not necessarily do so in an optimal fashion. Evolutionary and ecological models of financial markets is truly a new frontier whose exploration has just begun.Comment: 2 page