Digital libraries: the systems analysis perspective machine erudition
| DOI | https://doi.org/10.1108/DLP-02-2016-0006 |
| Published date | 09 May 2016 |
| Pages | 62-67 |
| Date | 09 May 2016 |
| Author | Robert Fox |
| Subject Matter | Library & information science,Librarianship/library management,Library technology,Records management & preservation,Information repositories |
Digital libraries: the systems
analysis perspective
machine erudition
Robert Fox
University of Notre Dame, Notre Dame, Indiana, USA
Abstract
Purpose – The purpose of this paper is to explore the concept of machine learning. Current trends in
the eld are explored, along with the potential impact on information science. Machine learning is both
an old and new eld. It has been theoretically explored since the 1940s, but advances in technology,
statistics and mathematics have recently created conditions, wherein it can be put into practice.
Design/methodology/approach – This is a conceptual column exploring the notion of machine
learning and the applications for information science.
Findings – Some of the objections to machine intelligence are common philosophical problems dealing
with the nature of thinking, self-awareness, understanding and other human traits that allow us to relate
to people, develop intuitions and have situational awareness.
Originality/value – While machine learning is being taken advantage of in the commercial sector, it
has not been effectively exploited in the academic sphere. Libraries have traditionally focused on
structured analysis and strictly controlled vocabularies to enable information discovery. Machine
learning opens up possibilities for unstructured data to be analyzed intelligently. Over 80 per cent of
regularly consumed information on the Internet is unstructured, so this eld has huge implications for
discovery from a library perspective.
Keywords Machine learning, Neural networks, Discovery, Data classication, Machine logic,
Reinforcement learning
Paper type Conceptual paper
Following the world wars in the early part of the twentieth century, and the subsequent
rise of both physics and mathematics as elds of inquiry, there was a great deal of
speculation about the future. By 1950, the world had been transformed by automation,
and machines were a part of every day life. These changes had happened so rapidly that
it seemed as though automata that would be performing all of our menial tasks in the
near future. In that era, a man named Alan Turing incorporated his intellectual
ponderings about automation and machine learning into a paper he published in Mind
called “Computer Machinery and Intelligence” (Turing, 1950). When this paper was
published, many of the controversies that we still struggle with today were raised and
debated. Some of the objections to machine intelligence are common philosophical
problems dealing with the nature of thinking, self-awareness, understanding and other
human traits that allow us to relate to people, develop intuitions and have situational
awareness.
Turing understood the importance of these problems, and in his paper, he did not
avoid them, but he did side step them to a certain degree by shifting the nature of the
question. For example, a prevalent religious objection to machine intelligence is that the
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/2059-5816.htm
DLP
32,2
62
Received 3 February 2016
Accepted 3 February 2016
DigitalLibrary Perspectives
Vol.32 No. 2, 2016
pp.62-67
©Emerald Group Publishing Limited
2059-5816
DOI 10.1108/DLP-02-2016-0006
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