The Strategic-Tactical Dichotomy of Drone Warfare

“Drones have arguably revolutionised modern warfare, especially their use in targeted killings. However, over-reliance on this tactic due to its measurable results has come at the expense of long-lasting strategic advances, moving drones away from their original intelligence-focused tasks and stagnating an already exhaustive War On Terror.”

by Javier Martínez Mendoza

The failed assassination attempt of Taliban leader Mullah Omar, on 7th October 2001, marked the first use of Unmanned Aerial Vehicles (UAV) or “drones” for a targeted killing in the Global War on Terror [1]. Since then, the involvement of drones in this struggle has shifted from merely surveillance and intelligence-related activities to an additional function: leadership decapitation, arguably revolutionising the way war is waged [2].

Despite their tactical achievements, over-reliance on this tactic has had repercussions on the Global War on Terror’s strategic goals, stagnating any significant advance for the sake of short-term gains that require these operations to be carried out constantly. Ultimately, this strategic-tactical dichotomy has caused a misperception regarding how modern wars should be waged, prolonging an already exhaustive war.

How do drones fit in the War On Terror?

The use of drones is not new for US war efforts and intelligence. For decades, drones have been used just for activities relating to surveillance, training, and information gathering [3]. Originally, American decision-makers’ attitudes towards using drones to carry out strikes were of clear opposition, but the response to 9/11 paved the way for their use in targeted killings of Al Qaeda militants and enablers [4]. From that moment on, the US underwent ‘the most overt, technologically advanced, and prolific assassination programme the world had seen to that point’ [5].

In the broader context of the Global War on Terror, drones have been used or could be used for activities such as persistent surveillance, especially ‘pattern of life’ surveillance (following an individual’s everyday activities for a prolonged time), as well as tasks that involve entering environments that are risky for human health or that are deemed not worth endangering personnel [6]. It is possible to identify two trends: drones have been used mostly for surveillance and air support in Iraq and Afghanistan, whereas they have been extensively involved in targeted killings in Pakistan, Yemen, and Somalia, where the US is not officially engaged in a war and thus has not deployed a significant number of personnel [7].

The strategic-tactical dichotomy

Drones have become essential for the US decapitation strategy against terrorist groups like Al Qaeda, which aim at taking down terrorist organisations by capturing or killing their leadership. However, targeted killings could have a limited impact in reducing the frequency of militant attacks in the regions where they are carried out, providing a short-term solution that must be consistently carried out to maintain its impact, instead of a definite solution to terrorist violence [8].

For instance, even if it is true that the assassination of terrorist leaders decreases the incidence of terrorist attacks by increasing the organisations’ vulnerability by disrupting cohesion and deterring its militants, terrorist groups might remain operational. Due to their decentralized and clandestine nature, communal support and the bureaucracy they create over time, these organisations can develop a resilience that allows them to engage in terrorism even while weakened [9].

Nonetheless, other research suggests that Al Qaeda and the Taliban do suffer the effects of drone attacks, losing bases and militants, and facing operational setbacks [10]. Moreover, these attacks not only take down organisation leadership, but also deter their activities due to fear of imminent strikes. Despite the latter seeming as a long-term strategic advantage, targeted killings would need to take place constantly to keep exerting their deterring effect. 

On the other hand, statistical data on the effect of drone strikes in North-western Pakistan and Eastern Afghanistan shows there could be a negative correlation between terrorist violence and the recurrence of drone attacks in these regions [11]. Notwithstanding the latter, drone warfare as a long-lasting counter-terrorism solution remains a dubious policy, since its deterent effect on terrorism would require strikes to keep taking place indefinitely.

When drone warfare is assessed from a strategic point of view, it can be argued that its groundbreaking character has been exaggerated, both by supporters and detractors, as it has produced an over-reliance on tactics at the detriment of strategy. As targeted killings deliver measurable results, it becomes “addictive” for decision-makers to continue to carry them out even if, ultimately, there is no territorial gain and terrorists maintain activities and control over the territory [12].

Furthermore, over-reliance on killing targets denies the possibility of vital information gathering had the operation been aimed at capturing. Targeted killings are shifting the focus from drones’ initial intelligence-driven role in the Global War On Terror: surveillance [13]. However, it is possible to consider that drones are also changing the dynamics of this armed conflict, causing a shift in the display of police functions instead of waging war against terrorists. Ultimately, it could be argued that carrying out drone strikes is stagnating US-led efforts, as it is driving American forces to maintain police-like surveillance over terrorists that are being deterred but not taken down as an organisation.

Conclusion

The tactical efficiency of drone strikes offers decision-makers much desired results in a seemingly endless War On Terror. However, the tactical advantages of drones have distracted from wider strategic goals, giving decision-makers a false sense of progress. Drone use in war should remain a tactic, but current policy-making has missed the point and favoured tactical gains rather than fulfilling strategic goals [14].

Due to the tangible and measurable results of targeted killings, US-led efforts in the Global War On Terror have run the risk of emphasising immediate achievements at the expense of pursuing long-lasting strategic objectives. This might ultimately contribute to the stagnation of US military efforts by stopping its forces from attaining fatal blows to resilient terrorist structures. In this regard, it could be argued that drone use for targeted killings has become just a tactically efficient way to cut the weed, without addressing the underlying roots.

Drones’ effectiveness is mostly present in their ability to support military operations and gather valuable information. However, as long as the tactical-strategic dichotomy analysed previously, keeps misleading decision-makers from the idea that drones’ true potential will be fulfilled when their use follows strategy instead of setting it, they will fail to truly revolutionise US efforts against terrorism.

Sources:

1- Neal Curtis, “The explication of the social: Algorithms, drones and (counter-)terror,” Journal of Sociology 52, no. 3 (2016).

2- Hugh Gusterson, Drone: remote control warfare (London: The MIT Press, 2016), 6. Christopher J. Coyne, and Abigail R. Hall, “The Drone Paradox: Fighting Terrorism with Mechanized Terror,” The Independent Review 23, no. 1 (2018).

3- Patrick F. Walsh, “Drone paramilitary operations against suspected global terrorists: US and Australian perspectives”, Intelligence and National Security 32, no. 4 (2017). Coyne, and Hall, “The Drone Paradox”.

4- Gusterson, “Drone”.

5- Simon Frankel Pratt, “Crossing off names: the logic of military assassination,” Small Wars & Insurgencies 26, no. 1 (2015): 11.

6- Ann Rogers, and John Hill, Unmanned: Drone Warfare and Global Security (London: Pluto Press, 2014).

7- Walsh, ”Drone paramilitary operations”. Gusterson, ”Drone”.

8- Trevor McCrisken, ”Obama’s Drone War,” Survival 55, no. 2 (2013)

9- Jenna Jordan, ”Attacking the Leader, Missing the Mark: Why Terrorist Groups Survive Decapitation Strikes,” International Security 38, no. 4 (2014).

10- Asfandyar Mir, ”The U.S. Drone War in Pakistan Revisited”, Lawfare, https://www.lawfareblog.com/us-drone-war-pakistan-revisited

11- Patrick B. Johnston, and Anoop K. Sarbahi, ”The Impact of US Drone Strikes on Terrorism in Pakistan,” International Studies Quarterly 60 (2017): 215-216. McCrisken, ”Obama’s Drone War”.

12- Lawrence D. Freedman, ”The drone revolution: less than meets the eye,” Foreign Affairs 95, no. 6 (2016), http://go.galegroup.com.ezproxy.lib.gla.ac.uk/ps/i.do?p=EAIM&u=glasuni&id=GALE%7CA477460848&v=2.1&it=r&sid=summon

13- Tyler Wall, ”Ordinary Emergency: Drones, Police, and Geographies of Legal Terror,” Antipode 48, no. 4 (2016).

14- Johnston, and Sarbahi, ”The Impact of US“.

The Influence of Big Data in the Intelligence Cycle

Big Data entails innovative technological progress to the intelligence cycle as it strengthens the collection stage, introduces the correlational analysis method, and facilitates the dissemination of data to the final consumers. However, Big Data also presents some challenges and risks as human consciousness and expert participation remains essential to ensure the intelligence cycle’s effectiveness.

by Alejandra Bringas Colmenarejo

The inclusion of Big Data (BD) in the intelligence cycle has entailed a great advance since it introduced objective and quantitative methods in a discipline highly characterised by its subjectivity. In this sense, BD attempts to reduce intelligence uncertainty through the collection of a huge volume of data and the identification of hidden correlations unobservable in smaller samples. However, while BD is a beneficial technological advance of the intelligence cycle, it also leads to deep controversy given that policymakers may be tempted to replace the expert knowledge and the intelligence analysis with raw BD assets and correlations [1].

BD “represents the Information assets characterized by such a High Volume, Velocity and Variety to require specific Technology and Analytical Methods for its transformation into value” [2]. Consequently, BD is defined by the extremely large quantity of information collected in real-time and in continuous flows. Such information includes structured and unstructured data, traditional processed numeric and text databases, as well as unprocessed formats like images, audios, videos, tweets, emails and more [3]. Furthermore, BD also entails the necessary technologies to collect, manipulate, compare and analyse the collected bulk data and transform it into a reasoned intelligence assessment [4].

The inclusion of BD in the intelligence cycle has several challenges since it surpassed information, knowledge, casualty and context to centre the focus of attention on correlations [5]. Once its veracity and validity have been determined, the data collected from different sources is analysed to predict, determine or even prevent future scenarios, actions and behaviours [6]. Consequently, BD intelligence analysis is “the process of examining and interrogating Big Data assets to derive insights of value for decision making in a quasi-immediate response” [7]. However, this intelligence progress entails some risks and challenges since the increasing dependence on gathering technologies, as well as the enormous quantity of data collected, could result in a sense of overconfidence in technologies and a refusal of human capabilities.

Regarding intelligence collection, BD improves the inductive approach that attempts to recognize long-term trends, patterns and anomalies [8]. Different algorithms and informatics tools enable the automatization of collection, storage, management and transmission of data. This automatization decreases the dependence from manual processes and facilitates the continuous flows of data, [9] which strengthens the analysts’ capabilities to discover intelligence gaps or unusual behaviours. However, to avoid a paralysation of the intelligence process it is essential that the algorithms used are effective in selecting valid and useful data from the vast raw data collected [10].

BD also allows intelligence analysts to generate and refute hypotheses. BD analysis appears to be quite inductive since it refers to past events and historical patterns to causally respond to the question of ‘what is happening’. However, the value of BD lies in the correlation and the identification of hidden events and circumstances so that realities which may not be evident or observable become available to the intelligence analyst. Consequently, filtering valid information from the massive quantity of data allows analysts to support their speculations with facts or to deny a previously confirmed hypothesis [11]. The quick and real-time collection, as well as the long-term storage of data, provides analysts with the necessary evidence to develop informed and predictive intelligence hypotheses. In spite of that, the BD correlation process could also result in the identification of patterns and realities that extrapolated from their specific context are completely useless or coincidental. Consequently, intelligence agents should carefully use BD correlations as without the appropriate expertise analysis they could lead to irrelevant events or unconnected behaviours [12].

Despite the massive volume of data gathered by the intelligence actors, some information remains unknown and excluded from the correlation process because of its secrecy or its restricted access. In this context, non-state data collectors, such as social media platforms, marketing agencies or companies collect and store information that can be bought by the intelligence actors to fulfil the information gap. Nevertheless, the veracity and accuracy of this information remains dependent on the initial collectors [13]. As a result, data provided by private actors could involuntarily impact the effectiveness of the intelligence process or maliciously corrupt, manipulate and counterfeit the reality to deliberately influence the final intelligence assessment [14].

In this manner, BD remains dependent on human capabilities because it still lacks creativity, consciousness and judgement to contextualize new correlations within a broader analytical framework [15]. The limitations of BD should be understood completely in order to avoid misinterpretations and misunderstandings of reality. BD needs expert analysts who are able to identify mere coincidences and consider the unpredictable behaviour of human beings.

Concerning the relation between intelligence analysts and consumers, BD could play different roles. It could help disseminate relevant intelligent assessments to their effective consumers facilitating well-informed analysis and decision-making. Despite this progress in the dissemination stage, intelligence consumers may be sceptical about the veracity and validity of BD’s correlations. Consequently, they could ask for in-depth pattern’ explanations or even become reluctant to authorise action or enact policies supported by BD’s analysis [16]. Otherwise, consumers may be tempted to use raw data without the necessary subsequent analysis to support their own interest and purposes, contrary to the effectiveness of the intelligence cycle [17].

The challenges introduced by Big Data in the intelligence cycle are part of the existential debate between humans and technology and a logical consequence of the very speed of technological advances. Nevertheless, an even greater intelligence revolution could result from the next technological progress – the autonomy of artificial intelligence (AI). AI would collect BD in real-time, develop the consequent intelligence analysis and finally disseminate a reasoned assessment. Future BD analysis and AI would be able to reduce uncertainty and solve intelligence puzzles. However, the challenges and risks associated with this kind of technology are also undeniable since the human element in the intelligence cycle is reduced to the mere intelligence consumer. In the present time, BD does not possess human consciousness, however, full autonomy could be a reality in the near future [18].

Sources:

[1] Van Puyvelde, Damien, Stephen Coulthart, and M. Shahriar Hossain. “Beyond the buzzword: big data and national security decision-making.” International Affairs, 2017: 1397-1416.

[2] De Mauro, Andrea, Michele Grimaldi, and Marco Greco. (2014) “What is Big Data? A Consensual Definition and a Review of Key Research Topics.” 4th International Conference on Integrated Information. AIP Proceedings, pp. 1-11.

[3] Normandeau, K. (2013, September 12). Beyond Volume, Variety and Velocity is the Issue of Big Data Veracity. Available at https://insidebigdata.com/2013/09/12/beyond-volume-variety-velocity-issue-big-data-veracity/

[4] Boyd D. & Crawford. K. Critical Questions for Big Data. (Information, Communication and Society, 2012), p. 662-678

[5] Landon-Murray, M. (2016). Big Data and Intelligence: Applications, Human Capital, and Education. Journal of Strategic Security, 9(2), p.92-121.

[6] Lyon, D. (2014, July-December). Surveillance, Snowden, and Big Data: Capacities, consequences, critique. Big Data & Society, p.1-13. doi: 10.1177/2053951714541861

[7] Couch, N., & Robins, B. (2013). Big Data for Defence and Security. Royal United Services Institute for Defence and Security Studies, p.6.

[8] Lim, K. (2015). Big Data and Strategic Studies. Intelligence and National Security, p.619-635.

[9] Symon, P. B., & Tarapore, A. (2015). Defense Intelligence Analysis in the Age of Big Data. Joint Force Quarterly 79, p. 4-12

[10] Couch & Robins, p.9

[11] Lim, p. 636

[12] Landon-Murray, p.94

[13] Zwitter, A. (2015) Big Data and International Relations. Ethics & International Affairs, 29, no 4, pp. 377-389.

[14] Symon & Tarapore, p. 9.

[15] Dyndal, G. L., Berntsen, T. A., & Redse-Johansen, S. (2017, 28 July). Autonomous military drones: no longer science fiction. Available at NATO Review Magazine: https://www.nato.int/docu/review/2017/also-in-2017/autonomous-military-drones-no-longer-science-fiction/en/index.htm

[16] Landon-Murray, p.101.

[17] Jani, K. (2016). The Promise and Prejudice of Big Data in Intelligence Community. Sam Nunn School of International Affairs, p.14.

[18] Dyndal; Berntsen & Redse-Johansen.

The Chinese Swarming Programme – Part Three of Three

The People Liberation Army has recognised the potential of swarm technology to disrupt the current order; the low cost of swarming technology means that it could be used for saturation assaults on a high-value target by simply overwhelming the current defensive systems.

By Caitlin Irvine

When discussing the People’s Liberation Army’s (PLA) developments in swarm technology it is first important to lay out their strategy. The PLA has recognised the potential of swarm technology to disrupt the current order; the low cost of swarming technology means that it could be used for saturation assaults on a high-value target by simply overwhelming the current defensive systems [1]. The Chinese military, therefore, intends to use this technological advancement as a force multiplier. According to the PLA, unmanned weapons systems are central to future operations in all domains of warfare [2]. Political commentators have speculated that swarming technology could be deployed by China in contentious areas such as the South China Sea [3]. The unmanned nature leaves the party coming into contact with the swarm having to decide whether or not a flyover is an act of aggression, simply reconnaissance, or human error. The secrecy surrounding Chinese military operations resulted in only two clear examples of swarming being discovered; the demonstration at Guangzhou Air Show in 2017 and a simulated reconnaissance mission.

The simulated reconnaissance mission tested an entire group of drones – incorporated with swarming technology – carrying out a variety of missions [4]. Unspecified portions of the flight were performed autonomously whilst still acting as a swarm. Feng and Clover highlight that Beijing therefore thinks ‘swarms of drones will become a weapon of the future’ [5]. It is clear that this technology – and autonomous weapons systems more generally – are an area of debate with severe implications for future warfare.

The PLA aims to harness ‘military-civil fusion to enable future military applications’ by integrating military and civilian developments [6]. A success in the civilian arena rapidly transfers over to the military dimension [7]. In 2017, at the Guangzhou Air Show, a swarm of 1,108 quadcopters displayed the results of Chinese civil-military cooperation [8]. Not only did these drones illustrate synchronised flight but they also showed ‘independent thought’ [9]. During the performance at least three drones fell out of the swarm for an unpublished technical reason. However, when they failed to complete their delegated tasks each drone executed their  individual landings. Drone swarms have previously been compared to an American football team – the swarm runs set plays and the operator oversees the network [10]. But in this demonstration the drones have also shown independent self-repair capabilities; the communication connection from the drones to the hive-like mind was re-established during flight [11]. This self-repairing function therefore demonstrates the potential for these systems to have decision-making capabilities outside of the operator’s direct control. This is a developing technology, still in the early stages, but the PLA is committed to investing in drone swarms for the long-term future.

Drone swarms represent a disruption in the strategic status quo of warfare. In this three-part mini-series, three main points about the consequences of swarming technology have been made. The low entry cost relative to conventional munitions could make these systems commonplace. As a weapon, drone swarms place the onus of differentiation on those being attacked. The advantages for unconventional theatres, such as urban terrain, make these systems attractive to militaries around the world. In both the American and Chinese examples, investment in swarming technology has been seen from both civil and military entities. Within the narrative surrounding drone swarms, it appears that the main use of such systems will be reconnaissance. But, it is their ability to also host attack capabilities is what makes them particularly terrifying. It appears that drone swarms have less political opposition in comparison to Lethal Autonomous Weapons Systems, or ‘Killer Robots’ as they are more popularly known, yet mark a clear point in the path towards such autonomous technologies [12]. 

Sources:

[1] Kania, E (2017) ‘Swarms at war: Chinese advances in Swarm Intelligence’, The Jamestown Foundation: China Brief, Vol 17, Issue 9, p 13

[2] Ibid.

[3] Wise, D (2017) ‘Chinese Drone Swarms Could Overwhelm US at Sea’, The Cipher Brief [online] available at: https://www.thecipherbrief.com/chinese-drone-swarms-overwhelm-u-s-sea accessed on 16th April 2017

[4] Trevthick, J (2018) ‘China Is Hard At Work Developing Swarms Of Small Drones With Big Military Applications’, The Warzone [online] available at: http://www.thedrive.com/the-war-zone/17698/chinas-is-hard-at-work-developing-swarms-of-small-drones-on-multiple-levels accessed on 19th April 2018

[5] Feng, E and Clover, C (2017) ‘Drone swarms vs conventional arms: China’s military debate’, The Financial Times [online] available at: https://www.ft.com/content/302fc14a-66ef-11e7-8526-7b38dcaef614 accessed on 16th April 2017

[6] Kania, E (2017) ‘Swarms at war: Chinese advances in Swarm Intelligence’, The Jamestown Foundation: China Brief, Vol 17, Issue 9, p15

[7] Laskai, L (2018) ‘Civil-Military Fusion and the PLA’s Pursuit of Dominance in Emerging Technologies’ [online], The Jamestown Foundation: The China Brief, Vol 18, Issue 6, availible at: https://jamestown.org/program/civil-military-fusion-and-the-plas-pursuit-of-dominance-in-emerging-technologies/

[8] Romaniuk, SN and Burgers, T (2018) ‘China’s Swarms of Smart Drones Have Enormous Military Potential’, The Diplomat [online] available at: https://thediplomat.com/2018/02/chinas-swarms-of-smart-drones-have-enormous-military-potential/ Accessed on 16th April 2018

[9] Ibid.

[10] Department of Defence (2017) ‘Department of Defence Announces Successful Micro-Drone Demonstration’, Department of Defence, Press release number NR-008-17, 9th January [online] available at: https://www.defense.gov/News/News-Releases/News-Release-View/Article/1044811/department-of-defense-announces-successful-micro-drone-demonstration/ accessed on 19th April 2018

[11] Romaniuk, SN and Burgers, T (2018) ‘China’s Swarms of Smart Drones Have Enormous Military Potential’, The Diplomat [online] available at: https://thediplomat.com/2018/02/chinas-swarms-of-smart-drones-have-enormous-military-potential/ Accessed on 16th April 2018

[12] Docherty, B (2012) ‘Losing Humanity: The Case against Killer Robots’, Human Rights Watch Report

Swarming Technology is Changing Drone Warfare – Part One of Three

Swarming technology, therefore, represents a disruption in terms of the strategic status quo of warfare due to the low entry cost, the general trend towards more autonomous systems, and the onus of differentiation being placed on those being attacked.

By Caitlin Irvine

‘Swarm technology is nascent, and some have pegged it as the next significant drone innovation’ [1]. It allows a group of unmanned aerial vehicles (UAVs) to complete an objective whilst coordinating with one another [2]. It is not pragmatic to ask one individual to monitor up to 250 UAVs so the operator delegates a task to the swarm and monitors the network that senses, communicates, and computes the surrounding environment [3]. Investment in this subset of independently operating systems has made the use of swarming technology in operational theatres a topical matter.

 The economic case for this new technology is clearly attractive as shown by the two major players investment in the field. The US Army’s funding for robotics for 2017-2021 has tripled to $900 million whilst China currently holds the world record for the largest swarm of drones collectively controlled at the Guangzhou Air show in 2017 [4]. The cost of a swarm relative to a harpoon missile (around $1.2 million) highlights that creating an entire swarm may be cheaper than building conventional defence systems [5]. Swarm technology has been developed primarily in small quadcopters because they are cheaper, easier to transport, and can be deployed in a shorter time than larger hardware such as the Predator B or MQ9-Reaper [6].

 Militarily, these small drone swarms provide several advantages in a built-up operational theatre where bottlenecks are common and buildings or trees can reduce the signal range. Quadcopters are adaptable simply because of their size – they are able to navigate through narrow urban terrain [7]. A swarm can also project further than an individual quadcopter; by placing members of the swarm at different points along the approach to an operational area they can act as relay stations back to the base station where the operator is [8].

 The issue surrounding swarms is how to defend against them. Their innovation causes a paradigm shift. Due to their ability to overwhelm and confuse traditional radar detection-based missile shields mass again becomes a decisive factor on the battlefield [9]. ‘A manned or unmanned aircraft can be brought down by a single missile, but a swarm can take multiple hits’; this places a military with a dilemma of how to respond to a swarm without looking like the aggressor [10]. Simply put, ‘there is lower costs for offense relative to the difficulty of defending against a swarm’ [11].

 Swarming technology therefore represents a disruption in terms of the strategic status quo of warfare due to the low entry cost, the general trend towards more autonomous systems, and the onus of differentiation being placed on those being attacked. Militaries are interested in developing and deploying swarm technology because of the cost-effective advantages it presents in urban environments and the difficulties of defending against such a system. Their use in contested areas could lead to a perpetual cycle of warfare given that the best way to respond to a swarm of UAVs is to deploy your own. The investment drone swarms have received from both civil and military entities shows that they are an important developmental step for the future conduct of warfare. However, the growing trend towards autonomous weapons is concerning primarily because of the lack of thought given to the knock-on effects of such weaponry. 

Sources:

[1] Sims, A (2018) ‘How do we thwart the latest terrorist threat: swarms of weaponised drones?’The Guardian

[online]

available at: https://www.theguardian.com/commentisfree/2018/jan/19/terrorists-threat-weaponised-drones-swarm-civilian-military-syria accessed on 11th April 2018

[2] Hambling, D (2016) ‘Drone Swarms will change the face of modern warfare’, Wired

[online] available at: http://www.wired.co.uk/article/drone-swarms-change-warfare

Accessed 10th April 2018

[3] Lachow, I (2017) ‘The upside and downside of swarming drones’,

Bulletin of the Atomic Scientists, Vol 73:2, p96

[4] Ibid.

[5] Hambling, D (2016) ‘Drone Swarms will change the face of modern warfare’, Wired

[online] available at: http://www.wired.co.uk/article/drone-swarms-change-warfare

Accessed 10th April 2018

[6] Bürkle, A, Segor, F, and Kollman, M (2011) ‘Towards Autonomous Micro UAV Swarms’

Journal of Intelligent And Robotic Systems, Vol 61(1-4), p340

[7] Ibid.

[8] Hambling, D (2016) ‘Drone Swarms will change the face of modern warfare’, Wired

[online] available at: http://www.wired.co.uk/article/drone-swarms-change-warfare

Accessed 10th April 2018

[9] Feng, E and Clover, C (2017) ‘Drone swarms vs conventional arms: China’s military debate’,

The Financial Times [online] available at: https://www.ft.com/content/302fc14a-66ef-11e7-8526-7b38dcaef614

Accessed on 16th April 2017

[10] Hambling, D (2016) ‘Drone Swarms will change the face of modern warfare’, Wired

[online] available at: http://www.wired.co.uk/article/drone-swarms-change-warfare

Accessed 10th April 2018

[11] Kania, E (2017) ‘Swarms at war: Chinese advances in Swarm Intelligence’

The Jamestown Foundation: China Brief, Vol 17, Issue 9, p14

Author’s Further Reading

[1] Kumar, V (2015) ‘The Future of Flying Robots’, Ted Talks [online]

Available at: https://www.youtube.com/watch?v=ge3--1hOm1s A

ccessed on 9th April 2018

[2] Boyle, MJ (2013) ‘The Costs and Consequences of Drone Warfare’

International Affairs, Vol 89: 1 (2013) pp1–29

[3] Nurkin, T (2016) ‘Unmanned ground vehicles: technology and market trends’

Jane’s Review [online]

available at: http://www.janes.com/article/61176/security-unmanned-ground-vehicles-technology-and-market-trends-es2016d1

Accessed on 10th April 2018

BIG WORLD, BIG DATA

The number of potential applications for the use of big data is immense. Initially intended as a private sector tool, big data is now finding its place within the realm of politics. Cambridge Analytica’s involvement in the Trump and Brexit campaigns has demonstrated the onset of a new era where big data may be used not only for population analysis, but also to influence the political views and preferences of the population as well.

By Yuliia Kondrushenko

The evolution of technology and the use of big data has forcefully shifted the balance of power relations within society. It is no longer the person who watches the algorithm, but rather the algorithm watching the person [2]. The main features of big data – volume, velocity, and variety – create a very appealing tool as it allows for the discernment of patterns and relationships that are not readily evident from the input data itself.

Big data is increasing “situational awareness” by recording trends that are taking place. This is often used by major supermarket chains such as Wal-Mart, which handles more than a million customer transactions every hour [4]. For example, customer buying behaviour records can demonstrate if the person is conservative, or if they are prone to shifting preferences based on prices, branding, and other factors. Nevertheless, one must be aware that big data can only show event correlation and cannot concretely explain causation.

Due to the corporate-centric nature of big data collection, this sector is where it will be deployed. Big data is an essential tool for detecting bank fraud; should a transaction deviate from the customer’s normal buying patterns, the bank is able to block the activity immediately [5]. But contrary to commercial application, deployment of big data analysis “for the public good” has not been widespread. One place big data could have been useful was the 2007 mortgage crisis in the United States, which began the world financial crisis of 2008. Had big data analysis been performed in relation to debt securities, the bubble may have been halted at its inception.

This is where the limitations of big data analysis become obvious though. The first issue is the amount of data available for algorithmic consumption. The predictive power of big data can only be strengthened by a “significant number of known instances of a particular behaviour” [6]. This means that while bank fraud is a common and well-researched problem with a distinguished pattern, unprecedented crises like the mortgage bubble are not easily predictable.

Another limitation comes from the creation of the algorithm itself. Consumption of an “example data” set creates the operation with the task of finding correlations in the data [7]. Data, which is separate from the example set, is then used to test the effectiveness of the resulting algorithm. This can sometimes create an algorithm that is efficient at forecasting based on the sample used to create it, but is still inadequate for classification of new test data.

While there is a significant risk of result politicization – where the data expert will find scenarios they were initially hoping to find – the fast expansion of available data sets and their dynamic nature makes big data analysis a very powerful tool for business and research.

Sources:

[1]Cárdenas, A., Manadhata, P. and Rajan, S. (2013). Big Data Analytics for Security Intelligence.

[ebook] Cloud Security Alliance, pp.1-22. Available at: https://cloudsecurityalliance.org/download/big-data-analytics-for-security-intelligence/

[2]Jani, K. (2016). The Promise and Prejudice of Big Data in Intelligence Community.

[ebook] Ithaca: The Computing Research Repository Journal, pp.1-19.

https://arxiv.org/abs/1610.08629

[3]Seifert, J. (2007). Data Mining and Homeland Security: An Overview.

Washington D.C.: Congressional Research Service, pp.1-29.

[4]Troester, M. (2012). Big Data Meets Big Data Analytics. [ebook] SAS Institute Inc., pp.1-11.

https://www.sas.com/content/dam/SAS/en_us/doc/whitepaper1/big-data-meets-big-data-analytics-105777.pdf

[5]Cárdenas, A., Manadhata, P. and Rajan, S. (2013). Big Data Analytics for Security Intelligence.

[ebook] Cloud Security Alliance, pp.1-22.

https://cloudsecurityalliance.org/download/big-data-analytics-for-security-intelligence/

[6]Seifert, J. (2007). Data Mining and Homeland Security: An Overview.

Washington D.C.: Congressional Research Service, pp.1-29.

[7]Jani, K. (2016). The Promise and Prejudice of Big Data in Intelligence Community.

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