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Special Report: Big Data and International Law: Not So Far Now


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By Abhivardhan


We think that International Law is limited to treaties and state relations. However, this is not the generic picture of this field. Big Data has an interesting impact over human rights, state actions and responsibility and business models, which moves towards the privatization of international law. Chatham House reports in its special section about the scope of IHRL with the fields of data science in a relative science, bringing up the formation of generic fields of international law. Human Rights, when is considered to be unusually linear, needs a dimensional approach to recognize international law in case of cyber operations, and that is the pretext, where big data becomes fundamentally important. This article explores the introductory reality of big data with the field like international law, which is a special guide of introduction for a layman.


Cyber infrastructure, is never an easy reality and it seems generally less convincing for a layman to highlight for himself, is not an easy reality. It resembles a sui generis way of fragmented lifestyle and connective infrastructures that we represent. As well as retroactively expurgating language, AI and big data will let prognostic control of latent dissidents. This will resemble Amazon or Google’s consumer targeting but will be much more effective, as authoritarian governments will be able to draw on data in ways that are not allowed in liberal democracies. Amazon and Google have access only to data from some accounts and devices; an AI designed for social control will draw data from the multiplicity of devices someone interacts with during their daily life. And authoritarian regimes will have no compunction about combining such data with information from tax returns, medical records, criminal records, sexual-health clinics, bank statements, genetic screenings, physical information (such as location, biometrics, and CCTV monitoring using facial recognition software), and information gleaned from family and friends. AI is as good as the data it has access to. Unfortunately, the quantity and quality of data available to governments on every citizen will prove excellent for training AI systems[2].

AI in its Ambit: Is it so Contingent that It is Lost to be Understood?

Under international law, a state is entitled to take countermeasures (opens in new window) for breaches of international law against it that are attributable to another state. Countermeasures are acts by an injured state against another state that would ordinarily be unlawful but are legally justified as responses to the offending state’s unlawful activity. The use of countermeasures is subject to strict conditions. The purpose is to encourage the offending state to stop its unlawful activity, rather than to punish. The countermeasures must also be proportionate. And they must not use force. There are no reasons why cyber operations may not in principle be used as a countermeasure in response to a breach of international law. There is nothing in their nature to make an exception for them. The state of existing international law is not changed by the fact that the UN group whose purpose is to agree common understandings on the international law applicable to cyber operations failed to reach agreement on this issue[3].

Source: Industrial Research Institute (2016)[4].

AI technology may have profound impacts on economic and geopolitical power balances, but it will require clarity of purpose to ensure that it does not simply serve to reinforce existing inequities. Building a framework for better managing the rise of artificially intelligent systems in the near term might also reinforce the process of mitigating longer-term risks[5]. Some claim that machine learning and deep learning[6] approximate human intelligence, but at present these tools basically detect patterns that are significantly tuned by humans and must be interpreted by humans to be useful. As a result, the advances that they represent are evolutionary and not revolutionary. One critical limitation of machine learning is that, as a data-driven approach, it fundamentally relies on the quality of the underlying data and thus can be very brittle. There are no guarantees that a computer leveraging machine learning algorithms can detect a pattern or event never previously encountered, or even scenarios that are only slightly different. As uncertainty grows, therefore, these tools become less useful[7].

It is not a League of Material Success: It is Just Imaginative Being Crystalizzed

There exists a stigma of specialized legal knowledge based on scholarly, judicial, executive and legislative data (not limited to democratic institutions, but now extended to a relativity between international law and municipal law). Moreover, the law is perfected and recognized as being duly ‘self-aware and self-critical’ and is attempted as a merger with a due ability inserted and replenished to be open to real-time assumptions and observations. For pragmatic constitutionality, it would be fit enough that the pure theories of jurisprudential schools must be an optimal and least approachable tenets of legal reasoning unless the AI finds capable enough to reconsider with a considerable acceptance of due consonance with the assumed aspect of rule of law and its due applicative constraints. This might seem to be akin to the conceptual deliberations on tort jurisprudence but revisiting human rights with the original elements of legal character and institutions in law (particularly international law via IHRL) can be a suitable step.[8] It just depends on how we deal with Big Data for making AI and its utilities better for mankind rather making it more vulnerable.


[1] Undergraduate Student at Amity University, Lucknow.

[2] Nicholas Wright, How Artificial Intelligence Will Reshape the Global Order, Foreign Affairs (July 10, 2018), available at:

[3] Joyce Hakmeh & Harriet Moynihan, Offensive Cyberattacks Would Need to Balance Lawful Deterrence and the Risks of Escalation, (March 23, 2018), available at:

[4] Industrial Research Institute, 2016 Global R&D Funding Forecast, supplement to R&D Magazine, Winter 2016 (2016).

[5] M. L. Cummings, Heather M. Roff, Kenneth Cukier, Jacob Parakilas and Hannah Bryce, Artificial Intelligence and International Affairs: Disruption Anticipated: Executive Summary, Chatham House (2018)

[6] Deep learning is a branch of machine learning that attempts to match the processes by which humans learn using

especially large and complex artificial ‘neural networks’. See Hof, R. (2013), ‘Deep learning: With massive amounts of computational power, machines can now recognize objects and translate speech in real time. Artificial intelligence is finally getting smart’, in MIT Technology Review,

[7] Supra note 5.

[8] Abhivardhan, Credibility and Legitimacy Standards for AI Realms in International Law – an IHRL Approach (July 24, 2018). 347th International Conference on Law and Political Science (ICLPS), Chennai, 24-07-2018. Available at SSRN:


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