🇬🇧🤔Ethics and Intelligence at the Times of Artificial Intelligence — Part 1/2, Digital Transformation

intelligence ai and ethic
AI, DT, Intelligence and ethic

Two-part analysis on how the relationship between ethics and intelligence, at the time of artificial intelligence, has become almost impossible and needs to be redefined based on new parameters: first part, the effects of the digital transformation.


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.


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.


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.


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.


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.

Second Part of Analysis


(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



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alessandro rossi🧟‍♂️💭

alessandro rossi🧟‍♂️💭


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