[Corpora-List] Open Research Position (M.S. / Ph.D. / post-doc): Analyzing Routine Activities for Crime Prediction

Martin Mueller martin.mueller at me.com
Tue Apr 22 21:36:29 CEST 2014


Heidegger, not a great name to conjure with in many contexts, was nonetheless quite good on the subject of 'fore-judgement,' the literal translation of 'prejudice' and 'Vorurteil'. If you look closely enough all judgments are 'fore-judgements' and to that extent discriminatory. If I'm going on a holiday to the Pacific Northwest, I'll pack an umbrella, which I may not need if I go to Santa Fe, where sunglasses, a sun hat and sunscreen lotion will be essential. Come to think of it, Bayes and Heidegger are at one on that.

On Apr 22, 2014, at 12:39, Adam Kilgarriff <adam at lexmasterclass.com> wrote:


> If a clever system can predict who is going to predict a crime - with good, but far from 100%, accuracy, is the use it
> a) rational policing practice
> b) discriminatory
> to use that information?
>
> Seems to me, it's both.
>
> Marek says
> > But there are definitely many ways to abuse this technology as well.
>
> I don't feel abuse is the main issue. Any use of it is discriminatory. Should we trade off? Tough question.
>
> Adam
>
>
> On 22 April 2014 11:34, Marek Rei <marek.rei at gmail.com> wrote:
> Here's an interesting article about how Chicago police is already applying such technology (in somewhat troubling ways):
>
> http://www.theverge.com/2014/2/19/5419854/the-minority-report-this-computer-predicts-crime-but-is-it-racist
>
> I wouldn't say crime prediction technology by itself is evil, it's more a question of how it's used. For example, I wouldn't have a problem with a system that can prioritise a large list of likely suspects after a crime has been committed, or is able to flag a social media message calling for a hate crime. But there are definitely many ways to abuse this technology as well.
>
> Marek
>
>
>
> On Tue, Apr 22, 2014 at 10:55 AM, Christian Pietsch <chr.pietsch at googlemail.com> wrote:
> Hi Matthew,
>
> so you want to build a heuristic precrime detector based on routine
> activities observed on social networks. Does that mean that if, say, I
> tend to update my status at the same time as some terrorist in your
> training set, your software will label me as a likely terrorist and
> put me on a no-fly list? Will I get a chance to prove my innocence?
>
> When you have some spare time, try to watch Minority Report. Or did
> this movie inspire your project? Then you must have misunderstood its
> message.
>
> Your suspect
> Christian
>
>
> On Mon, Apr 21, 2014 at 11:34:11AM -0400, Matthew Gerber wrote:
> > Hello,
> >
> > A new research position has opened within our lab, and we are seeking M.S.,
> > Ph.D., and post-doc researchers.
> >
> > One-sentence summary: We are mining social media for indicators of
> > individual routine activities for the purpose of improved crime prediction.
> >
> > Longer summary: This project focuses on the spatiotemporal prediction of
> > localized attacks carried out against individuals in urban areas. We view
> > an attack as the outcome of a point process governed by the interaction of
> > attackers, targets, and the physical environment. Our ultimate goal is to
> > predict future outcomes of this process in order to increase the security
> > of human populations and U.S. assets and interests. However, achieving this
> > goal requires a deeper understanding of how attack outcomes correlate with
> > the routine activities of individuals in an area. The proposed research
> > will generate this understanding and in doing so will answer questions such
> > as the following: What are the dimensions along which individuals’
> > activities should be quantified for the purpose of attack prediction? How
> > can measurements along these dimensions be taken automatically and with
> > minimal expense (e.g., via social media)? What are the implications of such
> > measurements for attack prediction performance? Subsuming these questions
> > is the issue of geographic variation: do our answers change when moving
> > from a major U.S. city to a major U.K. city? There has been plenty of
> > previous work on spatiotemporal attack prediction (see our Asymmetric
> > Threat<http://ptl.sys.virginia.edu/ptl/projects/asymmetric-threat-prediction>project);
> > however, these basic questions remain unanswered, leaving a
> > substantial gap in our understanding of attack processes and their
> > relationships with individuals’ routine activities.
> >
> > More information can be found
> > here<http://ptl.sys.virginia.edu/ptl/projects/routine-activities-analysis-for-crime-prediction>
> > .
> >
> > Sincerely,
> >
> > Matthew S. Gerber, Ph.D.
> > Research Assistant Professor
> > Department of Systems and Information Engineering
> > University of Virginia
>
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> --
> ========================================
> Adam Kilgarriff adam at lexmasterclass.com
> Director Lexical Computing Ltd
> Visiting Research Fellow University of Leeds
> Corpora for all with the Sketch Engine
> DANTE: a lexical database for English
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