CEPE/IACAP Joint Conference 2021 - Abstract Submission and Registration

Session

Philosophy of Computing and Machine Learning

3

Not scheduled

32. A Falsificationist Account of Artificial Neural Networks

Individual Paper

Machine learning operates at the intersection of statistics and computer science. This raises the question as to its underlying methodology. While much emphasis has been put on the close link between the process of learning from data and induction, the falsificationist component of machine learning has received minor attention. In this talk, I argue that the idea of falsification is central to...

122. Machine Learning as Model & as Metaphor

Individual Paper

Over human intellectual history, philosophers have made progress on under- standing natural systems by analogising them with technological advances. New technologies also serve as formal, physical, and conceptual models of target sys- tems, and their development is informed by empirical discoveries in the sciences. Emerging technologies in machine learning promise a radical disruption of...

103. What to Make of Functions in Computer Science? A Case Study on the Basis of Computer Programs

Individual Paper

This study aims to fill a gap in the literature about the role of “functions” in computing, particularly focusing on the case of computer programs. For exemplifying the problem, I focus on recent work, Piccinini’s 2015 Physical Computation: A mechanistic account and Turner’s 2018 Computational Artifacts, and compare them. Based on that (i) I argue that the notions of functions employed in the...