This chapter aims to contribute to critically investigate whether human-made scientific
knowledge and the scientist's role in developing it, will remain crucial—or can data-models …

In this chapter I discuss connections between machine learning and the philosophy of
science. First I consider the relationship between the two disciplines. There is a clear …

Scientificity is essentially methodology. The use of information technology as
methodological instruments in science has been increasing for decades, this raises the …

The applications of machine learning (ML) and deep learning to biology has fostered the
idea that the automated nature of algorithmic analysis will gradually dispense human beings …

Finding solutions to many of the world's major challenges requires increasing scientific
knowledge. Artificial intelligence (AI) has the potential to increase the productivity of science …

Introduction: Machine Learning as Philosophy of Science Page 1 Introduction: Machine
Learning as Philosophy of Science KEVIN B. KORB School of Computer Science and …

It is widely believed that empiricism, though once dominant, is now extinct. This turns out to
be mistaken because of incorrect assumption about the initial dominance of logical …

Abstract [claim that] the prevailing conception of scientific thinking... has been an overly
narrow one that compartmentalizes scientific thinking as a technical, rarefied form of thought …

The focus of this article is a question that has been neglected in debates about digitalization:
Could machines replace human scientists? To provide an intelligible answer to it, we need …

Abstract Traditionally, the Philosophy of Science has examined the nature of scientific
discovery. In recent years, Cognitive Science has gathered together work in Artificial …