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Emerging trends: I did it, I did it, I did it, but. . .

  • KENNETH WARD CHURCH (a1)

Abstract

There has been a trend for publications to report better and better numbers, but less and less insight. The literature is turning into a giant leaderboard, where publication depends on numbers and little else (such as insight and explanation). It is considered a feature that machine learning has become so powerful (and so opaque) that it is no longer necessary (or even relevant) to talk about how it works. Insight is not only not required any more, but perhaps, insight is no longer even considered desirable.

Transparency is good and opacity is bad. A recent best seller, Weapons of Math Destruction, is concerned that big data (and WMDs) increase inequality and threaten democracy largely because of opacity. Algorithms are being used to make lots of important decisions like who gets a loan and who goes to jail. If we tell the machine to maximize an objective function like making money, it will do exactly that, for better and for worse. Who is responsible for the consequences? Does it make it ok for machines to do bad things if no one knows what’s happening and why, including those of us who created the machines?

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Copyright

This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.

References

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Church, K., 2005. Reviewing the reviewers. Computational Linguistics 31 (4): 575578.
Church, K. 2014. TALIP perspectives, guest editorial commentary: what counts (and what ought to count)? ACM Transactions on Asian Language Information Processing (TALIP) 13 (1): 5:1–5:5.
Freyne, J., Coyle, L., Smyth, B., and Cunningham, P., 2010. Relative status of journal and conference publications in computer science. CACM 53 (11): 124132.
LeCun, Y., Denker, J. S., Solla, S. A., Howard, R. E., and Jackel, L. D., 1989. Optimal brain damage. NIPS 2: 598605.
O’Neil, C., 2016. Weapons of Math Destruction. Crown, New York: Crown Publishing Group.
Page, L., Brin, S., Motwani, R., and Winograd, T. 1999. The PageRank citation ranking: bringing order to the web. Technical Report, Stanford InfoLab.
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Natural Language Engineering
  • ISSN: 1351-3249
  • EISSN: 1469-8110
  • URL: /core/journals/natural-language-engineering
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