Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    big data analytics in transporation
    Turning Data Into Decisions: How Analytics Improves Transportation Strategy
    3 Min Read
    sales and data analytics
    How Data Analytics Improves Lead Management and Sales Results
    9 Min Read
    data analytics and truck accident claims
    How Data Analytics Reduces Truck Accidents and Speeds Up Claims
    7 Min Read
    predictive analytics for interior designers
    Interior Designers Boost Profits with Predictive Analytics
    8 Min Read
    image fx (67)
    Improving LinkedIn Ad Strategies with Data Analytics
    9 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Data Mining and Terrorism… Counterpoint
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Big Data > Data Mining > Data Mining and Terrorism… Counterpoint
Data Mining

Data Mining and Terrorism… Counterpoint

Editor SDC
Editor SDC
4 Min Read
SHARE

In a recent posting to this Web log (Data Mining and Privacy…again, Jan-04-2010), Dean Abbott made several points regarding the use of data mining to counter terrorism, and related privacy issues. I’d like to address the question of the usefulness of data mining in this application.

Dean quoted Bruce Schneier’s argument against data mining’s use in anti-terrorism programs. The specific technical argument that Schneier has made (and he is not alone in this) is: Automatic classification systems are unlikely to be effective at identifying individual terrorists, since terrorists are so rare. Schneier concludes that the rate of “false positives” could never be made low enough for such a system to…


In a recent posting to this Web log (Data Mining and Privacy…again, Jan-04-2010), Dean Abbott made several points regarding the use of data mining to counter terrorism, and related privacy issues. I’d like to address the question of the usefulness of data mining in this application.

Dean quoted Bruce Schneier’s argument against data mining’s use in anti-terrorism programs. The specific technical argument that Schneier has made (and he is not alone in this) is: Automatic classification systems are unlikely to be effective at identifying individual terrorists, since terrorists are so rare. Schneier concludes that the rate of “false positives” could never be made low enough for such a system to work effectively.

More Read

Google and Amazon as Benchmarkers
Public Information
Another analyst firm (Ventana) gets it
Social Data on Chinese Microblogs and the Oscars
A video introduction to R for Excel users

As far as this specific technical line of thought goes, I agree absolutely, and doubt that any competent data analyst would disagree. It is the extension of this argument to the much broader conclusion that data mining is not a fruitful line of inquiry for those seeking to oppose terrorists that I take issue with.

Many (most?) computerized classification systems in practice output probabilities, as opposed to simple class predictions. Owners of such systems use them to prioritize their efforts (think of database marketers who sort name lists to find the so many who are most likely to respond to an offer). Classifiers need not be perfect to be useful, and portraying them as such is what I call the “Minority Report strawman”.

Beyond this, data mining has been used to great effect in rooting out other criminal behaviors, such as money laundering, which are associated with terrorism. While those who practice our art against terrorism are unlikely to be forthcoming about their work, it is not difficult to imagine data mining systems other than classifiers being used in this struggle, such as analysis on networks of associates of terrorists.

It would take considerable naivety to believe that present computer systems could be trained to throw up red flags on a small number of individuals, previously unknown to be terrorists, with any serious degree of reliability. Given the other chores which data mining systems may perform in this fight, I think it is equally naive to abandon that promise for an overextended technical argument.

TAGGED:terrorism
Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

ai for building crypto banks
Building Your Own Crypto Bank with AI
Blockchain Exclusive
julia taubitz vn5s g5spky unsplash
Benefits of AI in Nursing Education Amid Medicaid Cuts
Artificial Intelligence Exclusive News
AI role in medical industry
The Role Of AI In Transforming Medical Manufacturing
Artificial Intelligence Exclusive
b2b sales
Unseen Barriers: Identifying Bottlenecks In B2B Sales
Business Rules Exclusive Infographic

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

Could Data Governance Help the War on Terror?

6 Min Read

Anti-terror software glitches?

4 Min Read

The Statistics of Counter-Terrorism

2 Min Read

Are you thinking through system improvements after the Xmas Terror Attack?

7 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

ai chatbot
The Art of Conversation: Enhancing Chatbots with Advanced AI Prompts
Chatbots
ai in ecommerce
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?