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🇬🇧😟(No) Ethics and (No) Privacy in Intelligence at the Time of Artificial Intelligence

ethics and intelligence at the age of artificial intelligence

The Battle Between Digital Rights and Intelligence Activities in the Era of Artificial Intelligence


Consistent estimates show that the production of digital data accounts for 2,5 quintillion bytes and it is forecast that this number is expected to increase over 160 zettabyte per year in 2025. Similar quantities of measurement are popular to the surveys related to the magnitudes of the family of physics, while as far as data, quantification refers to the only one, among tangible and intangible productions, which currently needs SI prefixes in order to be defined in the real quantity.Present and foreseen volumes result from digitization and digitalization made possible through progress in digital technology since the beginning of the 50’s of the previous century. The transformation of the analog data into digital and changing business models, aiming at achieving new added value opportunities from technology, are activities which have interacted and continue to interact in the volumetric production of data. Jointly with the transmission speed, they are basically linear components which by themselves are not able to explain progress in quantities. On the one hand, systematic digital interaction among business models and on the other hand that one between models, stakeholders and external social-economic networks (referents and deferents) lead to the complex system(1) of digital transformation [DT]. It’s such an interaction that causes and continues to be the main responsible for quantitative exponentiality.

Intelligence is the discipline that provides scenarios to decision-makers turning raw data in wisdom through the activity of research, influence and defense of the information itself and for this reason, together with finance, it has been the one that has been affected mostly by DT and from which it has been and will continue being revolutionized.

This statement doesn’t have a quantitative approach only. War has followed its own model of development without excluding neither digitization nor digitalization. Weapon systems underwent both the coactions of the two technological tendencies and strategic logic(2) has been respected in the performance of all levels including both the technical and the operative ones perpetrating the development of new systems and operability as far as the dynamic of action/counter-reaction. However, digital interaction which originated DT has questioned the whole existing meaning at the level of theatre and great strategy, therefore the rules of the war. The pervasively strategic concept of “Unrestricted War”(3) without DT should have been neither developed nor planned(4) and least of all performed. Consequently, if information rises at the level of theatre when not of great strategy as in the case of the 13th 2016–2020 five-year Chinese plan, the discipline dealing with it has necessarily to make a quantum jump.

Therefore, DT is contextual reason and need for rising intelligence quality. If unrestricted war allows that whatever socio-economic digital archetype can be offensive and defensive weapon at institutional level, one has to be equipped to use, contrast and prevent from itself. Likewise whoever actor, who belongs to the patterns originating from or changed through DT, has to be aware of being both a target and a war tool at the same time. It doesn’t matter if, in a parallel symmetric conflict, the role of the third parties weapon is covered or contending because competitive needs imposed by digital globalization markets join the two aspects until the individual level.

Therefore, the weapon of computation in the face of quantitative increase doesn’t become any longer the only necessity, of tactical nature, inserted by DT towards intelligence; at every stage of strategy, decision-makers and analysts have to be provided with useful knowledge in real time by intelligent systems at every stage of strategy.

State of Art

The high positioning of intelligence along the pyramid of strategic needs hasn’t caused consequences and rethinks exclusively in the sectors historically dedicated to its use, i.e. military and institutional. First of all, with the progress of DT, it itself has become business model, creating value through interactions generated from the market targets of the reference models. Totally different, the new cycle of globalization(5) which has developed since 1990 up to now presenting features mainly based on ICT so that Intelligence function has become indispensable and not only necessary for temporary needs but also for whoever economic player without excluding the individual. Finally, Intelligence itself, being a discipline, has had to rethink its own role(6): the intelligence training knowledge cycle, still valid in its components, has been organized and evolved according to horizontal guidelines, among different steps and vertical within the steps of the strategic dimension. The change has taken place in both schemes, public and private, which foresee Intelligence as an advocate of objective scenarios in the presence of the decision-maker and of those, the Anglo-Saxon ones in particular (but not only), whose result of the analysis has to include action predictability as far as political position taken by the decision-maker towards reference systems to which it relates(7).

As a result, there are macro-changes always in the process of being defined due to the growing systematic complexity of this discipline which has been affected by DT differently according to geo-political and geo-economic areas. The divisions between Intelligence towards the outside and that one towards the inside of the reference system tend to disappear. What is the meaning of this spatial division line which characterized institutional and corporate framework when the battlefield shifts in “non-natural space”(8) of digital data? Likewise the horizon of demarcation between intelligence and counter-intelligence, a division which is itself historical, with reference to the mission of the work. The asymmetry of theatres and actors involved in confrontation and the mutability of the roles played by themselves, make it dangerously inefficient actions aimed at achieving sector goals. Ever if it should be one of the results of an efficient intelligent system based on sharing digital data and information. The dominant positions in intelligence action are emphasized in those countries whose systemic DNA presents interpenetration and collaboration between public and private, between internal and external resources to the socio-economic actor to the detriment of the closed apparatuses aiming at the only use of specificity with internal genesis. It is not only a matter of technological and technical resources but mainly of out-of-the-box availability of thoughts which are indispensable in the “unrestricted”.

The ongoing transformation is not exempt from tensions. It appears superficially in the definition step, mainly in closed systems featured by lack of pragmatism where DT implies the loss of the meaning of terms such as “economic war”, “economic Intelligence”, “information war” and of abbreviations which have characterized the sectorialisation of intelligence (HUMINT, SIGINIT, …) according to a contamination in the diversified use of datum that lives little room for labeling once significant. Going into deep, as behind labels there are people the more in closed apparatuses, the structural clash shifts into the ground, common to DT implications, of the human function in the working process, in this case in the intelligence cycle.

Challenge and Opportunities

The forced passage from technology to the concept of “unrestricted Intelligence” has been a test-bed for all facilities dedicated to the activity. The approach to intelligence in terms of “great strategy” has rewarded and continues to benefit large, medium and small countries, which regardless of the technological level of departure had the systematic assumption of pooling competitive resources in their political, bureaucratic, entrepreneurial and social DNA. Even those who were struggling, because of their different structural problems, had the winning factor in their systematic sharing of DT process being allowed to climb positions. Universities, research centres and think-tanks already codified in their actions to be functional to the system have proved to be an irreplaceable source of resources from which to draw not only at a specialist, tactical level, but with a new vision of the whole.

The ongoing growing opportunities are enormous and they are due to two factors. The first is the need to use specialized resources, with targeted competence, for the particular solution of general problems. Outsourcing, even in the design of solutions, is a necessary condition for an effective and efficient approach and the known budgets confirm this trend. As an example, think of the different components involved in a strategic action of influence within SOCMINT (SOCial Media INTelligence): it is unthinkable at the level of resources and skills to implement the entire cycle internally, as recent events have shown. From another point of view, the activity of systemic scouting has become an opportunity. New ideas and solutions are developed for market reasons, regardless of the needs expressed by Intelligence. Therefore, it becomes fundamental, therefore, both at public and private levels (sharing similar intentions and resources), to explore, suggest contests and support the development of those solutions which can make a strategic difference, equipping themselves with managerial skills capable of grasping the ‘out-of-the-box’ with a predictive vision.

Also in this case historically systems closed in themselves are having the worst in evolution, regardless of the level of DT reached, as they are not systematically geared, therefore mentally, for sharing competitive trust.

Presumable Development

Paradoxically, in Intelligence information cycle, the step which has been least affected by the stress of DT has been that of the analysis. Even if the proposition of the scenario were to be reiterated necessity in function of the change of a few planned variables, it is, however, the action which continues to suffer most heavily from human intervention. The discipline that is changing the status-quo is Artificial Intelligence [AI] for three reasons. The first, through different methodologies, historically is the first time that algorithms produce wisdom autonomously. In other words, they are able to produce knowledge independently and stratify it to make it available for further analysis and feedback. The second, AI, is multidisciplinary and multi-sectoral: therefore, the different developments of the market, in which it is protagonist adapt to the strategic evolution of ‘unrestricted intelligence’. The third, it is proving in the development to be a driving force for some sectors, even those of not immediate connection, an engulfing others. One thinks, by way of example, of the legal professions and of the advantage in terms of repeated analysis that the applications of AI are entailing.

It is, therefore, from the development of the cognitive predictive capacities of AI that the greatest progress in support of the activity of analysis is expected. The trend is confirmed by the current contests and by research projects in symbiosis with the private sector carried out by IARPA, the office for advanced research in Intelligence of the American DNI (Director of National Intelligence), as far as anticipatory Intelligence is concerned. They do not invest exclusively in obvious and specialized sectors, such as, for example, cybersecurity and semantic predictive analysis, but also in areas of wide qualitative and quantitative scope for reference data sets and expected results, such as the general forecast of individual judgment and prejudices.

Potential Disruption

DT has already produced disruption in Intelligence: collection, collation, analysis, dissemination and feedback have been upset in techniques and processes. The strategic strengthening will take place through the predictive models allowed by AI in two perspectives: the confirmatory one and OSINT (Open Source INTelligence). According to the first aspect, the interpretation of terabytes, stored and in the course of storage, will allow to change, knowledgeably, convictions and behavioural models acquired historically as true. Structured and sedimentary behaviours, as per analysts’ point of view, never questioned and at present at the basis of the choices of decision-makers, public and private, of any actor, will progressively become bias thanks to the interpretation capacity provided by AI: the macro sectors most affected by the phenomenon will be geo-politics, geo-economics and broad-spectrum socio-economic sciences. Similarly, from an OSINT point of view, the real-time prediction, not so much of behaviours as of the critical capacity to deal with them, will be a disruption factor. This will allow the decision-maker not to make one of the correct provided choices for but ‘the correct choice’ in real time.

In the general framework, as it has already happened, the actors who, due to their culture, reference legislation, type of constitution and sector of belonging, have less to respond to ethical, moral, social and regulatory sub-structures that regulate the use of the analysis data, will certainly have an advantage.

The complexity of the system

The digital transformation and globalization have changed the traditional intelligence framework from the early 1990s of the last century. The change, progressive and in progress, has been vertical, horizontal and oblique. Beyond the aims imposed by great strategy the different levels of the same one interpenetrate and merge : theatres, operations, tactics must be available in a mutually flexible manner at any time. In this perspective and as necessary, any technical tool and any actor can play a functional role in the strategy.

Labelling has ceased to make sense because they have ceased the edges, technical and operational, which they defined them. The investments needed to maintain the competitive have become such that public-private collaboration, for men and means, is an indispensable factor in a context of massive spread of information.

The system then climbed into the quantitatively and qualitatively complex. It had to evolve as a result of technological innovation and, at the same time, it had to do it in the most advanced forms in order to compete. Intelligent systems, AI, from support of elaboration have become paradigm needed to discernment of intelligence. Automated knowledge production, which is involving all sectors, puts intelligence to face problems that others do not have.

Ethics, norm and innovation

The debate between ethics and innovation (also understood as research) is not only old as the hills but also the amount of material available to build, or update, its own opinion is proportional to seniority. Finalized and recent analysis are helpful because they define articulated and shared principles by researchers of different latitudes. With the pragmatic intent of dealing with the ‘time’ component one aspect is underlined, obvious, and that is that innovation in the socio-cultural context, therefore ethical, in which it operates makes non-existent actions. They are always antecedent to the re-actions of the context itself (reactions of ethics) aimed at detecting and framing the effects. This causes for a (variable) period information asymmetry between suppliers and users of innovation: the former have the knowledge, the latter are passively subject to the effects not only without mediation but, given the novelty factor, even without references to contact for to be helped in mediation.

To the objection that this has always been, because inherent on the process of innovation propagation, we oppose four factors that digital transformation and globalization have changed compared to the past : the propagation time, now equal to zero, the possibility of mass dissemination, background noise and the oblivion of the data. These elements interact with exponentially information asymmetry : innovation is shared between specialists in real time; equally in real time it can give rise to podery developments over niches entirely unknown or deliberately concealed ; it remains unstinguishable in the real potential of the effects due to the amount of information, even (intentionally or otherwise) contradictory, present in social networks for those who are not specialists ; the effects are not eliminable, as the digital data is never destructible with certainty.

In other ways, the relationship between ethics and the law notoriously is not mutually speculating. The first reflects the values of a collectivity the second is based, and conditioned, by local cultural rules that lead to permitting or prohibiting behaviors. If you assimilate the behaviour of innovation to its effects is intuitive as the asymmetrical component at the expense of users increases : the law takes time to highlight, evaluate a behavior and consider its effects variably licit.

An observation that often occurs, especially in the Anglo-Saxon world, is that the law is much more rapid than ethics in grasping the distortions of novelty and put a Band-Aid at best. This line of thought worked when Moore’s Law was the radical factor, and that is, reasoning in terms of computational speed enhancements : now the parameters have changed, the speed is just one of the incremental factors (however important) that leads the algorithm to produce cognitive output. Others are, for example, accuracy in the definition of the domain, the direct and indirect libraries available, the bias detection and correction systems, all things which, with the same capacity for computation with it, have little to do, except for system or paradigms changes. The law is now harnessed in a multi-dimensionality of input that prevents a reaction at least more readiness than ethics, as it had previously occurred.

Here then you return to the problem of the time gap : who manages innovation has all the keys to manipulate it in their own favour and who undergoes the new one doesn’t have the defense keys, not being consciously aware of the problem for long. Before ethics and legislation are able to process and produce mediation the gap is able to give rise to actions with uncertain potential, in terms of licit-illicit/ethical-unethical, managed by a few on the head of many. Their value goes way beyond the concepts related to the time expressed in the theories of business and systemic innovation (see Schumpeter and connected) and has a own path because it impacts the interests of weak stakeholders with less specific knowledge, and that is the end users. In other words it is difficult to imagine initializing a movement of opinion in favor of observation or regulation of a cause if you are not aware that it exists.

In the intelligence, it doesn’t matter whether it’s public or private, the scenario is this. AI applications, at the different stages of the information cycle, make the ‘technically possible’ for reasons of investment and engineering mastering a Graal in the possession of a few who repours its effects on many unaware. With the proper differentiations between national security and private operations, the problem is not to evaluate behaviors, or sancting (or predict what to enshrine) but the lack of awareness in the target.

Engineering mastering also allows, all out on the table and for a while, what is called ‘strategic ignorance’, and that the hypocritically deflection of the responsibility toward imaginary auto-bias learning and black boxes of different nature, namely the machines. Notoriously, the algorithms in the initialization phase are neither designed (and codified) by themselves nor are they left to themselves, in the phase of self-learning and online production of output, in the behavior if it is not in line with the goal that we have set ourselves.

Frankly, the writer has little interest if periodically to someone of the FAMANG, or the protagonists of minor cabotage, a million-dollar penalty is imposed on the basis of the GDPR or other legislation for unlawful conduct. First, because the reprimand in cash are the cost, already in budget, of the risk of the action ; second, because fines are of such amount that they do not damage corporate profitability, so they do not have any deterrence to future behaviour ; third, because the damage is done and there is no way to go back.

This is not about digital justicialism: it would be stupid for the very nature of innovation. It is, however, to devise processes of informational protection of the user who at least, and pending cultural and regulatory evaluations, put it to the current of phenomenology.

Unless you rely on the cyclicality of events, like Snowden or Cambridge Analityca who accidentally discover Pandora’s box always and however when the damage is done, there is now no informative protection. There are excellent think-tanks and active organizations in the field of digital right, including the investigative side, at the local as supranational levels, but they are set up on pre-revolution models of the production of knowledge. In their niche they inform a few elected representatives and make reference to ethical, political and legislative decision-makers according to the times of the latter : no one has yet adopted a model that adapts to the speed of AI implementation in intelligence and uses it to inform in useful times the mass of users.

Intelligence and ethics

The relationship between intelligence and ethics has been defined pragmatically, and significantly, by Michael Hayden (at the top of US intelligence on the latter decade, in command of NSA, CIA and other) about ten years ago when he transmitted the image of a target, with the center representing the ‘politically sustainable’ and, progressively, three concentric outwards representing ‘legal’, ‘operationally sustainable’ and the ‘technologically feasible’. With an effort to accustom the ‘politically sustainable’ locution with ‘ethically sustainable’ the argument might play : today the informational asymmetry raises doubts.

If we talk about national security, state intelligence activities, it is shared that the agencies must comply at the inputs of policy makers and regulations (special and not) for them, whatever the nature of the regime. If the information asymmetry allows ‘technologically feasible’, in the absence of regulatory and political assessments that deal with the effects, operators (of any level) will be quiet, as to accountability to the tort, the single subjected to a ‘doable’ a little less.

Second point, what meaning ‘national security’ (which are its perimeters) in a context of lack of norm or political awareness of applied technology if it is ‘operationally sustainable’ in related areas of public interest, as common crime and / or tax? Also in this case the public actor who operationally applies the technology does not commit an unlawful act (it does not yet exist) nor is politically incorrect (with respect to a political input wich is also non-existent), indeed performs his work to the best : in what way is the individual protected?

If ten years ago the paradigm was ‘to collect as much as possible cause before or after it might be usefull’ now AI makes the technology available to make the most of it in real time : if one time massive collection was aimed at storing, in view of the necessary future uses (aimed at countering illegal behavior) now it is used to perform behaviours or massive behavioral predictivity. Another time, in what way the individual is protected if these effects bypass the two central areas of the Hayden target the effects are not known? Here’s the target needs to be reviewed with new perspective.

More recently Sir David Omand, (former head of British GCHQ) in the course of the review of the Investigation Power Act issued in 2016, said that the relationship between ethics and national intelligence must be that of a ‘just war’. To underscore the concept David Anderson (Queen’s Counsel in the context of terrorism), in the same process of amending legislation, saidabout the pervasiveness of intelligence that it must have the highest powers and that the problem is when to exercise them. The final version of the ACT made its own these and other suggestions with the consequence that Hayden’s target has been erased in its two areas closer to the center, updating it to the factual reality. It does not matter if the ACT was a civil rights aberration and is the most disputed measure in recent years in the United Kingdom : the purpose of eliminating the ethical problem has been reached by allowing, practically, everything.

Thus with national intelligence the point is that citizens (users), in a ‘translucent’ area as Michael Leither (chief of National Counterterrorism Center under George W. Bush) called it with good foresight, are aware of being massively tracked, surveyed, archived in every digital, biometric and (progressively, shortly) bio-genetic performance. No one, however, is able to know how these data are used, nor by who and even what behavioral and predictive deductive techniques are applied and for what purposes. It is the unresticted ‘just war’ referred to in the previous post.

For private intelligence, few lines are enough. There are only the perimeters of ‘operationally sustainable’ and ‘technologically feasible’ all the rest is left to individual ethics which, as from daily evidence, is (to use an euphemism) extremely elastic. On the other, if the context is the era of ‘capitalism of surveillance’ differently it could not be, otherwise it could not be for the survival of the profit model itself. Users remain with the ‘legal’ that, roughly and according to the different legislations, allows you to be informed (when it’s good) with a three-year gap.

So what to do?

On the one hand there are the state agencies that need to apply the ‘unrestricted intelligence’ because they consider it politically necessary to their own ends. In doing this they use the resources of private intelligence, for which the term ‘ethical’ (when taken into account) is an oxymoron compared to the meaning of ‘limit’. If this was not the competitive advantage of one and the other would be impossible. In the midst the mode of development of innovation that allows neither a shared massive information nor the apttation in useful times of rules in order to safeguard the potentially unlawful conduct. On the other side the users who progressively, under any regime, learn with a delay that makes it almost useless the same awareness, that they have entered surveillance bubbles of the habits for which Orwell’s 1984 or Black Mirror are children’s fairy tales.

Fresh Surveys indicate that the issue is not at the top of the concerns of citizens, even in countries for which high technology penetration combines a high rights sensitivity. The scenario does not surprise for two reasons : first the issue is young and, second, the disclosure is deficient for what has been said.

In the face of unrestricted intelligence and the consolidation of the model of surveillance capitalism, the response should be a typology of social counter-intelligence, widespread, collective and ‘unrestricted’, which allows for the creation of effective movements of opinion by temporal reaction, on the model of what is advent for the environment.

At the moment there is no such thing.


(1)Christian Matt, Thomas Hess, Alexander Benlian — Digital Transformation Strategies — Business & Information System Engineering — Vol.57 — October 2015

(2)Edward N.Luttwak — Strategy, The Logic of War and Peace — 2003 — The Belknap Press of Harvard University Press

(3)Qiao Liang, Wang Xiangsui — Unrestricted Warfare — 1999 — PLA Literature and Arts Publishing House

(4)Valery Gerasimov — Voenno-promyshlennyi kur’er — #8/2013

(5)Richard Baldwin — The Great Convergence: Information Technology and the New Globalization — 2016 — The Belknap Press of Harvard University Press

(6)Mark Phythian — Understanding the Intelligence Cycle — 2014 — Routledge

(7)-Sherman Kent — Strategic Intelligence for American World Policy — 1951 — Princeton University Press

(8)-see (3) note

This is adaptation of a neuronal Italian/English AI translation by IBM Watson.



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alessandro rossi🧟‍♂️💭

alessandro rossi🧟‍♂️💭

Innovation Intelligence Analyst| Meditator Zombie| Hikikomori White-Haired| Digital Borderline| Has A Black Hole Under The Pillow| A Bad Product Of💜Venezia🦁