Cybercrime and digital criminology: Lecture 9

‘Just as technology is changing the way young people communicate with each other every day, it’s also changing the way young people can protect themselves and their friends from becoming victims of sexual violence. This challenge is a chance to empower a new generation to take a stand against violence'

- United States Vice President Joseph Biden (in Sebelius, 2011: np)

LECTURE 9:

THE CROWDSOURCING AND

APPIFICATION OF CRIME PREVENTION

CROWDSOURCED COUNTERSURVEILLANCE

• Crowdsourced countersurveillance: ‘the use of surveillance information obtained from a networked public of crowdsourced labour to engage in the inverse surveillance of law enforcement officials and technologies’ (Wood and Thompson, 2018: 25).

• Crowdmapping: ‘the aggregation of crowd-generated inputs such as text messages and social media feeds with geographic data to provide real-time, interactive information on events’ - Qauintance (2011)

CASE STUDY: CRIME PREVENTION MANNINGHAM

• A grassroots community crime prevention group that primarily operates through the social media site Facebook.

• Located in the City of Manningham, in Victoria: a relatively affluent, low-crime area.

• Currently has just over 12,500 members.

• Through the group’s Facebook page, members are able to receive real-time updates on crimes in the area and quickly report crimes to the group’s many members.

CRIME PREVENTION AND SWARM INTELLIGENCE

WHAT IS CROWDSOURCING?

(Thompson and Wood 2018)

HUMAN SWARMS AND COLLECTIVE INTELLIGENCE

ASSESSMENT TWO

• Online police public appeals = human-intelligence crowdsourcing.

• Community crime prevention groups = knowledge-discovery and management crowdsourcing + human-intelligence crowdsourcing + swarm intelligence.

• Whilst crowdsourcing requires a central actor, swarm intelligence is characterized by leaderless decentralized co-ordination.

• Swarm intelligence: a form of collective intelligence that arises out of decentralized self-organized systems, whether natural or artificial.

2,000-word policy brief (50%)

Due Monday November 4

Complete one of the following tasks

• ‘The act of a company or institution taking a function once performed by employees and outsourcing it to an undefined (and generally large) network of people in the form of an open call. This can take the form of peer production (when the job is performed collaboratively), but it is also often undertaken by sole individuals. The crucial prerequisite is the use of the open call format and the large’ - Howe (2006: np).

• Brabham (2013: 45):

• Distributed human-intelligence crowdsourcing

• Knowledge-discovery and management crowdsourcing

• Trottier (2014): Crowdsourced surveillance

• 'The hive … extends itself as part of the environment through the social probings that individual bees enact, where the intelligence of the interaction is not located in any one bee, or even a collection of bees as a stable unit, but in the “in-between” space of becoming: bees relating to the mattering milieu' – Parikka (2010: 129).

• Whilst humans did not evolve the ability to swarm, new technologies that enable groups of humans to generate ‘real-time closed loop systems’ (Rosenberg et al., 2016).

TASK ONE

(Wood 2018)

(Thompson and Wood 2018)

You are a policy officer working at New South Wales (NSW) Police.

NSW Police is currently evaluating its social media strategy.

Your task is to write a policy brief providing recommendations to NSW Police on whether to continue or alter its social media strategies. In evaluating NSW Police’s social media strategy, you should consider both the organization’s operational and communicative uses of social media. That is, the brief should

not be limited to a discussion of NSW Police’s use of social media to undertake police ‘image

work’.

DIGITALLY-ENABLED OR DIGITALLY-DETERMINED?

TASK TWO

SWARM INTELLIGENCE AS CRIME PREVENTION

• Crime Reporting Apps
• Deterrent Apps
• Crime Prevention Audit Apps
• e-Forensic health apps

Select a currently existing crime prevention app that falls into one of the following categories:

• Personal Safety Apps
• Crowdsourced Surveillance Apps
• Crime Tracking/mapping Apps
• Educational Apps

• Rogers (2012): digitized methods vs natively digital methods.

• As natively digital methods, digitally-determined crime prevention methods are born out of the specific affordances of the digital – remove the computational technology, and the crime prevention technique cannot exist.

•  Smartphone-enabled crime prevention techniques are a particular subset of digitally-enabled crime prevention.

(Wood 2018)

You cannot use Circle of Six as your example.

You are a policy officer working at the Victorian Department of Justice and Regulation, in the Community Crime Prevention Division.

Your department has launched a grant to support the further development of an existing crime prevention app that would be officially recommended by the department and Victoria Police.

Your department has received a grant application from the developers of your chosen crime prevention app.

On the basis of information about the app, and supporting your claims with research, you must decide firstly, whether to fund the app grant, and secondly, whether you recommend any changes to the features or functionality of the app that might improve its effectiveness or remove any problematic features.

Your policy brief should refer to literature on the crime prevention theories and principles the app builds upon, as well as any critical literature that might be relevant to the app.

Because there is not a great deal of published research that directly addresses

crime prevention apps yet, you are allowed, for this question only, to reference

this lecture when I discuss unpublished ideas.

• Coupling traditional Neighbourhood Watch crime prevention techniques with technologies that facilitate human swarming lets groups more effectively harness the four key functions of swarm organisation:
• Coordination
• Cooperation
• Collaboration and
• Deliberation (Garnier et al., 2007).

• Human swarms who are collectively aware of changes in information regarding a crime, and are able coordinate in responding to it.

TASK THREE

PART 2:

(Thompson and Wood 2018)

You are a policy officer seconded to the E-Safety Commissioner.

Your task is to write a policy brief offering policy recommendations how to best respond to online abuse and harassment.

However, your department head has specified that the department is not interested in policy responses that draw upon situational crime prevention and crime prevention through environmental design principles.

Whilst you can briefly mention these environmental crime

prevention approaches to online abuse and harassment, the core of your review and recommendations cannot be based upon their principles.

CROWDSOURCING,

COLLECTIVE INTELLIGENCE AND

CRIME PREVENTION

TASK FOUR

You are a policy officer working at Victoria Police.

In the wake of NSW Police’s Facebook page surging in popularity after enacting its ‘meme strategy’, Victoria Police is considering changing its social media strategy and has requested a policy brief that offers best practice recommendations on a police-social media strategy.

Your task is to write a policy brief that provides recommendations to Victoria Police on how it might improve its existing social media practices. In making these recommendations, you should reference Victoria Police’s 2018/2019 Community Safety Statement.

The brief should consider, but not be limited to, a

discussion of the potential for undertaking police

‘image work’ on social media.

ASSESSMENT TWO STRUCTURE

Executive summary: two to three sentences summing up the entire brief (50-75-words).

Introduction: explain the policy issue and why it is particularly important or current (200-300-words).

Research and evidence: provide details from literature/articles, government reports, on the problem (750-850-words).

Policy recommendations: discuss and justify your reasons for how the problem(s) should be addressed (600-700-words).

Conclusions: reinforce the key message to take

away from the policy brief (250-250-words).

ASSESSMENT TWO CRITERIA

CROWDSOURCING, HUMAN SWARMS

AND FEAR OF CRIME

Clarity of policy brief purpose: does the policy brief establish who its audience is, and establish the specific problem it is responding to?

Critical understanding and review of relevant literature: does the policy brief provide an adequate review of relevant literature on the issue?

Substantiation of recommendations: does the policy report offer well-substantiated recommendations?

Structure of policy brief: does the section contain all the components of a policy brief?

Number of errors: is the policy brief free of expression- and content-related errors?

Expression and writing style: does the policy brief keep jargon to a minimum? Is it written in an accessible style?

Quality and amount of referencing

• Crime Prevention Manningham was constantly buzzing with fear, anger and suspicion, even in weeks where few members reported actual crimes (see also Dixon, 2017)

• In becoming more conscious of local crime, many members became hypervigilant and even more fearful:

‘with everything I've been reading I'm really getting scared' - Group member, August 2016

'news/comments here makes me scared sometimes but it is what it is !' - Group member, August 2016

(Thompson and Wood 2018)

PART 3:

EVALUATING CRIME

REGULATING CRIME PREVENTION APPS: CONCERNS

PREVENTION APPS

• Quality concerns (Terry, 2015)

• Difficult to evaluate the efficacy of apps (Terry and Gunter, 2018)

• Safety concerns

• Do certain apps (for example Citizen) promote risky behaviour?

• Data protection concerns

• Gaps in regulatory models

• Regulatory indeterminacy (Terry, 2016)

CRIME PREVENTION APP DEVELOPMENT

KEY EVALUATIVE QUESTIONS:

• Descriptive questions: how many individuals have adopted the app?

• Normative questions: is the app being used as it was originally intended?

• Cause-and-effect questions: has the app been effective in preventing crime? (Chelimsky, 1985).

• The International Organization for Standardization (ISO) (1998) identifies three characteristics or metrics of usability:
• Efficiency
• Effectiveness
• Basic subjective satisfaction

• Morville (2004) identifies seven factors that influence user experience:

• Useful
• Usable
• Desirable
• Findable

• The appropriateness of an app:

•  Does the app make an effective use of the specific affordances of the smartphone, including their portability, mobility, and facilitation of perpetual contact?

• The evidence base of an app:

•  Does the app build upon recognized crime prevention principles?

•  If the app is a form of smartphone-enabled crime prevention, we might ask, is there empirical support for the effectiveness of the crime prevention techniques that the app applies?

• Potential unintended consequences:

•  Does the app’s functionality and messaging have the potential to:
• Increase fear of crime?
• Support victim-blaming sentiment?

• The user experience of the app:

• How well does the app fare in regard to metrics of efficiency, effectiveness and basic subjective satisfaction?

• Accessible
• Credible
• Valuable

RESPONSIBILISATION - THERE'S AN APP FOR THAT

(Wood 2018)

• Crime prevention apps, to use Garland (2001) and Beck’s (Beck, 1992) terms, have been criticized as just another self-responsibilisation strategy that places responsibility on the individual to manage and/or avoid risks (see Comack and Peter, 2005; Gray, 2009).

• To use Manovich’s (2001) term, responsibilisation has been transcoded into the language and logic of the smartphone, transforming it in the process.

• More technological solutionism? (Morozov, 2013).

NEXT LECTURE:

POLICING AND SOCIAL MEDIA

REFERENCES

National Network to End Domestic Violence (2017) Resources. Technology Safety Blog. Available at: https://www.techsafety.org/resources/ [Last accessed 6/10/2017]

Nhan J, Huey L and Broll R (2017) Digilantism: An analysis of crowdsourcing and the Boston Marathon Bombings. British Journal of Criminology 57(2): 341-361.

Parikka J (2010) Insect media: An archaeology of animals and technology. Minneapolis, US: University of Minnesota Press.

Pasulka N (2012) Want to Stop Rape? There’s an App for That. Mother Jones, Apr.6 Available at: http://www.motherjones.com/politics/2012/04/way-to-prevent-rape-app-iphone-apps-against-abuse/ [Last accessed 9/10/2017]

Rosenberg LB and Baltaxe D (2016) Swarm Intelligence and Morality of the Hive Mind. Paper presented at Collective Intelligence. New York University, June 1-3. pp.1-9.

Rosenberg, L., Baltaxe, D., & Pescetelli, N. (2016). Crowds vs swarms, a comparison of intelligence. In Swarm/Human Blended Intelligence Workshop (SHBI), September 28-29. pp.1-4.

Salter M (2016) Crime, Justice and Social Media. London, UK: Routledge

Sampson RJ (2008) Collective efficacy theory: Lessons learned and directions for future inquiry. In Cullen FT, Wright JP and Blevins KR (eds) Taking stock: The status of criminological theory. New York, US: Routledge. pp.149-166.

Sebelius K (2011) “Apps Against Abuse” Challenge to Help Assault and Dating Violence. The White House, Jul.13. Available at: https://obamawhitehouse.archives.gov/blog/2011/07/13/apps-against-abuse-challenge-help-address-sexual-assault-and-dating-violence [Last accessed 3/10/2017]

Shannon CE and Weaver W (1998) The mathematical theory of communication. Chicago, US: University of Illinois press.

Tech 4 Good (2012) A Free App that Prevents Violence Before it Happens. Circle of 6. Available at: http://www.nolasart.org/uploads/2/9/1/3/29136053/circle-of-6-one-sheet.pdf [Last accessed 4/10/2017]

Tech 4 Good (2015a) Schools. Circle of 6 App. Available at: https://www.circleof6app.com/schools/ [Last accessed 4/10/2017]

Terry, N. P., & Gunter, T. D. (2018). Regulating mobile mental health apps. Behavioral sciences & the law, 36(2): 136-144.

Thacker E (2004) Networks, Swarms, Multitudes: Part Two. CTHEORY: 5-1.

Trottier, D., (2014), ‘Crowdsourcing CCTV surveillance on the Internet,’ Information, Communication & Society, 17(5): 609-626.

Williams N (2016) The Ethical Pitfalls of Crime Prevention Apps. Digital Ethics & Policy, Jan.19. Available at: http://digitalethics.org/essays/ethical-pitfalls-crime-prevention-apps/ [Last accessed 4/10/2017]

Wall, D. (2007). Cybercrime: The transformation of crime in the information age. Cambridge, UK: Polity.

Wood, M. A., & Thompson, C. (2018). Crowdsourced Countersurveillance: A Countersurveillant Assemblage?. Surveillance & Society, 16(1), 20-38.

(Wood and Ross 2020)

Bonabeau E, Dorigo M and Theraulaz G (1999) Swarm intelligence: From natural to artificial systems. Oxford, UK: Oxford University Press.

Brabham DC (2013) Crowdsourcing, Cambridge, US: MIT Press.

Brantingham, P. J., & Faust, F. L. (1976). A conceptual model of crime prevention. Crime & Delinquency, 22(3): 284-296.

Charmaz K (2006) Constructing Grounded Theory: A Practical Guide Through Qualitative Analysis. Thousand Oaks, US: SAGE Publications.

Cooper, G. (2001). The mutable mobile: Social theory in the wireless world. In B. Brown, N. Green & R. Harper (Eds.), Wireless world: Social, cultural and interactional issues in mobile communications and computing (pp. 19–31). London, UK: Springer-Verlag.

Daubs MS and Manzerolle VR (2016) App-centric mobile media and commoditization: Implications for the future of the open Web

Dixon N (2017) Stranger-ness and Belonging in a Neighbourhood WhatsApp Group. Open Cultural Studies 1: 493-503.

Freiberg A (2001) Affective versus effective justice Instrumentalism and emotionalism in criminal justice. Punishment and Society 3(2): 265-278.

Galeon D and Caughill P (2016) Harnessing the Power of the Hive Mind Has Allowed One Company to Predict the Future. Futurism, Nov.10. Available at: https://futurism.com/harnessing-the-power-of-the-hive-mind-has-allowed-one-company-to-predict-the-future/ [Last accessed 29/10/2017]

Garnier S, Gautrais J and Theraulaz G (2007) The biological principles of swarm intelligence. Swarm Intelligence 1(1): 3-31.

Grace R (2015) Burglary rate surges in Melbourne’s Manningham area. The Age, May.26. Available at: http://www.theage.com.au/victoria/burglary-rate-surges-in-melbournes-manningham-area-20150526-gh9ned.html [Last accessed 2/12/2017]

Greenfield A (2017) Radical Technologies: The Design of Everyday Life. London, UK: Verso

Hinchey MG, Sterritt R and Rouff C (2007) Swarms and swarm intelligence. Computer 40(4): 111-113.

Hutchby, I. (2001). Technologies, texts and affordances. Sociology, 35(2), 441–456.

Janis IL (1972) Victims of groupthink: A psychological study of foreign-policy decisions and fiascos. Boston, US: Houghton Mifflin.

Katz, J., & Aakhus, M. (2002). Conclusion: Making meaning of mobiles – A theory of Apparatgeist. In J. Katz & M. Aakhus (Eds.), Perpetual contact: Mobile communication, private talk, public performance (pp. 301–318). Cambridge, UK: Cambridge University Press.

Kelly A and Finlayson A (2015) Can Facebook save Neighbourhood Watch? The Police Journal: Theory, Practice and Principle 88(1): 65-77.

Lanier J (2010) You are not a gadget: A manifesto. London, UK: Vintage.

Lapowsky I (2014) This app is a 21st century rape whistle. Wired, May.9. Available at: https://www.wired.com/2014/09/circle-of-6/ [Last accessed 4/10/2017]

Lub V (2017) Neighbourhood Watch in a Digital Age: Between Crime Control and Culture of Control. London, UK: Palgrave Macmillan.

Manovich L (2001) The Language of New Media. Cambridge, US: MIT Press

Mantoro, T., Agani, N., Ayu, M. A., & Jatikusumo, D. (2014, December). Location-aware mobile crime information framework for fast tracking response to accidents and crimes in big cities. In 2014 3rd International Conference on Advanced Computer Science Applications and Technologies (pp. 192-197). IEEE.

Mascheroni G and Vincent J (2016) Perpetual contact as a communicative affordance: Opportunities, constraints, and emotions. Mobile Media & Communication 4(3): 310-326.

McCarthy, O. T., Caulfield, B., & O’Mahony, M. (2016). How transport users perceive personal safety apps. Transportation research part F: traffic psychology and behaviour, 43, 166-182.

Miller P (2007) Swarm Theory. National Geographic, Jul.1. Available at: http://ngm.nationalgeographic.com/2007/07/swarms/miller-text [Last accessed 2/12/2017]

Morozov E (2013) To Save Everything, Click Here: The Folly of Technological Solutionism. New York, US: PublicAffairs.

SMARTPHONE-ENABLED AND SMARTPHONE-DEPENDENT

CRIME PREVENTION

• Smartphone-enabled crime prevention: crime prevention techniques that use smartphones, but do not require smartphones

• Smartphones may still act as a force multiplier that improves the effectiveness of the crime prevention technique.

• Smartphone-dependent crime prevention: can only be performed using smartphones or mobile technologies with a similar functionality.

• That is, we need to consider the affordances - possibilities for action - that smartphones offer, and which other communicative media do not (Hutchby, 2001).

(Wood and Ross 2020)

APPIFICATION

• Personal Safety Apps

• Crowdsourced Surveillance Apps

• Crime Tracking/mapping Apps

• Educational Apps

• Developmental crime prevention apps

• Crime Reporting Apps

• Crime Prevention Audit Apps

• e-Forensic health apps

• Apps are now central to the fabric of smartphones, so much so that smartphones may readily be dubbed (2016: 52) term ‘app-centric media’ (Daubs and Manzerolle 2016: 52).

• Appification: the replacing or substitution of websites with apps (Kosner, 2012).

• ‘Instead of thinking about the web as a hierarchical tree of documents, we need to start thinking about all of that content as an underlying service layer for application based interfaces’ - Kosner (2012: np).

• Crime reporting, crime mapping, personal safety, and prisoner rehabilitation and reintegration, have all – to varying levels – been appified

A TYPOLOGY OF CRIME PREVENTION APPS

Citizen crime avoidance

app interface

FIVE-MINUTE BREAK

(Wood and Ross 2020)

CRIME PREVENTION APPS

CIRCLE OF 6

• Crime prevention apps can be mapped onto Brantingham et al's (1976) crime prevention typology, which distinguishes between on primary, secondary, and tertiary prevention.

• Primary prevention apps are those that are marketed to potential victims of crime.

• Secondary prevention apps are apps that attempt to prevent offending among individuals deemed at risk of committing a crime.

• Tertiary prevention apps are apps that attempt prevent individuals who have already committed an offence from re-offending.

PRIMARY, SECONDARY AND TERTIARY

• Mobility and portability

• Cooper (2001): We can understand the mobility of smartphones as a three way process:
• The mobility of the user
• The mobility of the device
• The mobility of the content

• 'Perpetual contact’: the ability to communicate with others anytime, and anywhere (Mascheroni and Vincent, 2016).

• Geo-tracking

• ACHESS - a e-forensic mental health app that is smartphone dependent.

THE AFFORDANCES OF SMARTPHONES

PART 1:

THE APPIFICATION OF

CRIME PREVENTION

OVERVIEW

PART 1: UNDERSTANDING THE APPIFICATION OF CRIME PREVENTION

• Typologising crime prevention apps

• Conceptualizing crime prevention apps

• Smartphone-enabled and smartphone-dependent crime prevention apps

PART 2: THE CROWDSOURCING OF CRIME PREVENTION

• Forms of crowdsourcing

• Crowdsourced surveillance

• Crowdsourced countersurveillance

• Crime prevention and collective intelligence

PART 3: EVALUATING CRIME PREVENTION APPS

‘How can people and computers be connected so that – collectively – they act more intelligently than any person, group, or computer has ever done before?’ - Malone (2018: 16)

How might people and computers be connected so that – collectively – they can prevent crime more effectively than any person, group, or computer has ever done before?

mark.wood@unimelb.edu.au

CRIM2007: CYBERCRIME AND DIGITAL CRIMINOLOGY

DR MARK WOOD