Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new user(Non)-neutrality of science and algorithms: Machine Learning between fundamental physics and society
164
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
The impact of Machine Learning (ML) algorithms in the age of big data and platform capitalism has not spared scientific research in academia. In this work, we will analyse the use of ML in fundamental physics and its relationship to other cases that directly affect society. We will deal with different aspects of the issue, from a bibliometric analysis of the publications, to a detailed discussion of the literature, to an overview on the productive and working context inside and outside academia. The analysis will be conducted on the basis of three key elements: the non-neutrality of science, understood as its intrinsic relationship with history and society; the non-neutrality of the algorithms, in the sense of the presence of elements that depend on the choices of the programmer, which cannot be eliminated whatever the technological progress is; the problematic nature of a paradigm shift in favour of a data-driven science (and society). The deconstruction of the presumed universality of scientific thought from the inside becomes in this perspective a necessary first step also for any social and political discussion. This is the subject of this work in the case study of ML.
rate research
Read More
Our society is changing. Almost nothing these days works without a computer chip. Computing power doubles every 18 months, and in ten years it will probably exceed the capabilities of a human brain. Computers perform approximately 70 percent of all financial transactions today and IBMs Watson now seems to give better customer advise than some human telephone hotlines. What does this imply for our future society?
John Desmond Bernal (1901-1970) was one of the most eminent scientists in molecular biology, and also regarded as the founding father of the Science of Science. His book The Social Function of Science laid the theoretical foundations for the discipline. In this article, we summarize four chief characteristics of his ideas in the Science of Science: the socio-historical perspective, theoretical models, qualitative and quantitative approaches, and studies of science planning and policy. China has constantly reformed its scientific and technological system based on research evidence of the Science of Science. Therefore, we analyze the impact of Bernal Science-of-Science thoughts on the development of Science of Science in China, and discuss how they might be usefully taken still further in quantitative studies of science.
The world is changing at an ever-increasing pace. And it has changed in a much more fundamental way than one would think, primarily because it has become more connected and interdependent than in our entire history. Every new product, every new invention can be combined with those that existed before, thereby creating an explosion of complexity: structural complexity, dynamic complexity, functional complexity, and algorithmic complexity. How to respond to this challenge? And what are the costs?
Peaceful citizens and hard-working taxpayers are under government surveillance. Confidential communication of journalists is intercepted. Civilians are killed by drones, without a chance to prove their innocence. How could it come that far? And what are the alternatives?
Online social networks (OSNs) enable researchers to study the social universe at a previously unattainable scale. The worldwide impact and the necessity to sustain their rapid growth emphasize the importance to unravel the laws governing their evolution. We present a quantitative two-parameter model which reproduces the entire topological evolution of a quasi-isolated OSN with unprecedented precision from the birth of the network. This allows us to precisely gauge the fundamental macroscopic and microscopic mechanisms involved. Our findings suggest that the coupling between the real pre-existing underlying social structure, a viral spreading mechanism, and mass media influence govern the evolution of OSNs. The empirical validation of our model, on a macroscopic scale, reveals that virality is four to five times stronger than mass media influence and, on a microscopic scale, individuals have a higher subscription probability if invited by weaker social contacts, in agreement with the strength of weak ties paradigm.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
