Man versus Machine at Combat Tactical Level Decision Making

The human ability to collect information, make sense of a situation, optimise action, and learn while executing has been challenged recently in games, simulators, diagnoses, and real-time analysis. How may this development reflect to future tactical combat level decision-making? Is the machine going to win the man in combat?

"This requires not only substantial investment in resources but also an open-minded and exploratory approach, in contrast to the common but sometimes exaggerated perception of military organisations as conservative entities." Meir Finkel (Finkel 2023)

"Fifth-generation warfare shifts the focus from kinetic force in physical dimension to the impact information dimension, where narratives and perceptions take centre stage, enabled by emerging technologies such as artificial intelligence, automation, and robotics." Daniel Abbott (Abbott 2010)

The article reviews some recent achievements in artificial intelligence, sets the situation for the combat technical level functions, digs deeper into decision-making under stressful conditions and illustrates a possible vision for the future state. The aim is to shake the historically conservative concepts of land battle to consider future possibilities.

Artificial Intelligence Improvements in Decision Making

A view to the evolution of machine learning improvements in various strategic-tactical games and competitions in Table 1 shows that machines are catching up and dominating men in table, card and video games and creativity competitions. Furthermore, fast-learning general-purpose algorithms are beating dedicated algorithms in those same games. 

Table 1: A sample of improvements in Machine learning applications in gaming and creativity

Year	Confrontation	Improvement
1997	Chess: DeepMind against Garry Kasparov	It took IBM 11 years to build and use customised chips to execute parallel searches. DeepMind was able to evaluate 200 million positions per second.
2016	Go: AlphaGo against Lee Sedol	A neural network-based algorithm first learned from game data, then played against itself, and finally, improved based on made mistakes. AlphaGo was able to create an unseen move during the game.
2017	Chess: AlphaZero against Stockfish (2016 top chess engine)	General purpose reinforcement learning algorithm that learned Chess after playing 4 hrs against itself. AlphaZero was able to assess 80 000 positions per second.
	Shogi: AlphaZero against Elmo (2017 world champion Shogi engine)	The algorithm learned the game after playing 2 hrs by itself. AlphaZero was able to assess 40 000 positions per second on a board that has more options than Chess.
	Go: AlphaZero against AlphaGo Lee (advanced Go engine)	Deep neural network with tabula rasa reinforcement learning algorithm. The algorithm learned the game within three days while playing itself.
	Poker: Liberatus against four champion poker players	The algorithm used a game theoretic approach for reasoning in an imperfect information environment while playing simultaneously against four human players with the following abilities: ·        Managing the whole poker competition in advance ·        Solving each game during the contest ·        Self-improvement after each day of the three-week competition
2019	Dota 2: Open AI Five against a Team of 5 esport players	The algorithm used proximal policy optimisation. The algorithm used 800 petaflops/s to gain about 45 000 years of experience within ten months. The short-term average decision time was 80ms.
2020	AlphaFold2 doubled the score of human competitors in Critical Assessment of Structure Prediction.[1]	The algorithm predicted 3D structures based on complicated rules faster and more holistic than a human.
2022	AI model that uses tens of terabytes of Earth system data and can predict the next two weeks of weather tens of thousands of times faster and more accurately than contemporary forecasting methods.[2]	With enormous amounts of data, ML algorithms can create forecasts of very complex phenomena.

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[1] https://www.technologyreview.com/2022/02/23/1045016/ai-deepmind-demis-hassabis-alphafold/

[2] https://www.technologyreview.com/2023/07/05/1075865/eric-schmidt-ai-will-transform-science

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In conclusion and, in theory, a machine combined with the above features could:

1. Starts from zero knowledge and trains within months to master given battle scenario's technical, tactical, and possibly operational level features for victory.
2. Anticipates adversary moves ahead, creates picture of potential scenarios, and predicts adversary manoeuvring in 3-D space better than humans.
3. Makes short-term decisions within 80 milliseconds and optimises decisions simultaneously at technical and tactical levels.
4. Identifies lessons from the events and gains 150 years of theoretical combat experience teaching itself overnight.

 

Technical Level of Ground Combat is a Complex Military Decision-Making Environment

Probability and chance are well-recognised (Clausewitz 1984) (Fuller 2012) (Oliviero 2021) factors of battle environment. Tactics-technical level combat capability is a sum of surprise, manoeuvre, mass, firepower, and tempo (to name some essential tenets) orchestrated in variety of combinations with Command and Control to disrupt the adversary's socio-technical military system and exhaust its fighting ability. (Friedman 2017) The tactical tenets are in transformation to address the foreseeable changes on the battlefield. First, let's review the most likely changes in land warfare and, second, see what they will require from tactical tenets.

RUSI Land Warfare Conference (RUSI 2023) promoted the following tendencies of change in land warfare, which will challenge the contemporary tactics:

1. Transparent battlefield

• Civilian and military LEO satellite-based sensors provide a continuous feed of information from above the battlefield. The data can be acquired from commercial sources and fused with algorithms trained to identify especially military action on the ground.
• Unattended ground sensors improve details and add reliability to real-time event pictures.
• Cover and concealment become harder since sensors can fuse detection data from different parts of spectrum.
• Adversary will know the location and movement of blue forces as quickly as the information flows in the blue battle management system.

2. The concentration of effects vs protection

• Standoff weapons, lethal autonomous weapon systems, and precision warheads make it challenging to survive with contemporary armour. Adding armour thickness slows tactical mobility.
• Concentrated armoured units create a lucrative target for conventional artillery, attack helicopters, or massing of anti-tank UASs.
• Platforms and actors need to become more expendable and distributed but able for coordinated manoeuvres and fires.

3. Sustainment

• Logistics enables the tempo of fighting and is essential for offensive operations. Supplying distributed units require new delivery methods.
• Movement and mass of material expose logistics for continuous, wide-spectrum surveillance, so protection and endurance of logistics become a challenge.

4. Situational awareness

• An increasing amount of data and information challenges sense-making as human cognition overburdens from large amounts of information, loses focus in the stimulus-rich environment, and makes a biased conclusion.
• The organisational culture may prevent the distribution of information (need-to-know vs need-to-share; air-gap security vs zero-trust security), so situational awareness does not meet the requirements of distributed tactics. (Mansoor and Murray 2019)

5. Boundless, urban battlespaces

• People reside primarily in urban environments, and military strategies aim to "capture the will of the people and their leaders, and thereby win the trial of strength." (Smith 2005)
• Participating actors in urban battlespace may include, for example, civilians, communal authorities, law and rescue institutes, local corporates, international corporates, non-governmental organisations, insurgents, commercial military companies, interest groups, militias, criminal organisations, adversary regular forces and adversary coalition units. (Waterman 2019)
• The urban environment is more complex as these actors do not carry clear signs for identification, their intentions may transfer from day to night, and they do not follow agreements on war crimes.

In conclusion, the following Table 2 reflects the above tendencies to classical tenets of tactics and illustrates the possible impact in battle techniques and tactics and, therefore, change of tactical sense- and decision making.

Table 2: How do visible tendencies of change in land warfare affect tactical tenets of ground combat?

Tenet / Tendency	Surprise	Manoeuvre	Massing of force	Firepower	Tempo
Transparency	Surprise in land domain may be gained through other domains and dimensions.	Swarming manoeuvre of smaller, less detectable platforms.	Concentration becomes lethal, but dispersion rules.	Target acquisition is more lethal if situational awareness is achieved.	The advantage is harder to gain in a transparent battlefield.
Effect	Systems effect creates surprise and disrupts force cohesion.	A large, moving, hot, and radiating platform is an easy target.	Calls for a mass of nimble, small, and mobile warheads	The 4IR produces software-defined effectors.	Dispersed effectors will increase friction and entropy.
Sustainment	N/A	Higher mobility and wider distribution obscures logistics.	Dispersed troops increase the logistical challenge.	Smart warheads require software maintenance.	Besides live supplies, the force needs technical maintenance.
Situational awareness	Digitalised C2 creates more cognitive bottlenecks.	Becomes a core enabler and vulnerability for the swarming of distributed effectors.	Becomes a core enabler and vulnerability.	Becomes a core enabler and vulnerability.	Becomes a core enabler and vulnerability .
Urbanisation	Provides concealment in the physical dimension.	Slows manoeuvre and promotes smaller, autonomous, and agile platforms.	Constraints massing of units, but prefers small, swarming effectors.	Favours defence but constraints offence.	Slows down units and increases their entropy.

Art of Military Sense- and Decision-making

A Concept for Sense- and Decision-making

The classical military decision-making framework defined by John Boyd is simplified as Observe, Orient, Decision, and Action (OODA) (Osinga 2007). Based on this framework, Figure 2 illustrates a concept for sense- and decision-making. In this context, sense-making consisting of observation and orientation, which interprets the equivocal data. (Mattila 2016) Furthermore, decision-making is searching and selecting alternatives optimising between projected results, capabilities, and constraints. (Mattila 2016) The concept has three different situational pictures: real-time events per domain, composed operational picture, and forecasted possible/intended situations, which are referred to existing information and, finally, shared and agreed upon at the socio-cognitive level.

Figure 2: Concept for Observe, Orient and Decide at the Military tactical level

The above Command and Control (C2) concept may be established with an emphasis on creative leadership or policy compliance. These emphases are founded in the culture from which armed forces are generated. For example, German culture from 1871 – 1945 promoted officers' autonomous and aggressive action on the battlefield. (Mansoor and Murray 2019) Conversely, after the forceful manipulation of Bolshevik government, Russian culture produced obedient younger officers and relied on experienced and resourceful commanders at the operational level. (Freedman 2022)

A Team of Military Officers in Decision-making

A successful military command should be a mixture of compliance with institutional management culture and creative operational art. (Kuronen 2015) German culture before WW II reflected the war as "an art, a free and creative activity founded on scientific principles." (Condell and Zabecki 2008) The US FM 5-0 requires adaptive leaders"…who do not think linearly, but  who instead seek to understand the complexity of problems before seeking to solve them…" (Cojocar 2011) On the other hand, NATO assesses military success with five measures of merit and only one of them, measures of performance (MoP), includes some personal leadership features. (CCRP 2002) The other four enforce doctrinal and process compliance. (NATO RTO 2002) The 1/5 ratio in expectations does not indicate innovative tactical decision-making from NATO officers.

At the tactical commitment level, all efforts should focus on gaining the initiative and, eventually, victory over the adversary (reduction of adversary combat power by more than 30%). (Oliviero 2021, 51) In reality, this is not necessarily evident for all officers: 

• Training enforces drills and tactical forms, so officers prefer to use familiar concepts to solve battlefield challenges in decision-making. 
• Viewpoints may be constrained by their basic training and arms. An infantry officer aims to gain ground, an armoured forces officer aims to gain distance, or an artillery officer assesses ranges, amount of ammunition and supplies to impose a particular effect. 
• The Red Force doctrine, officers are training against, remains linear, predictable, and unimaginative adversary. 
• Since live exercises are expensive, officers train their tactical decision-making in war games, which often neglect friction, fog, chaos, and cognitive stress present on the battlefield.

Studies (Henaker 2022) (Scott and Bruce 1995) (Loo 2000) have concluded that there are five different decision-making styles categorising individuals when making important decisions: Rational, Intuitive, Dependent, Avoidant and Spontaneous.

1. Rational seeks information systematically and prefers logical assessment. However, rational has challenges in creativity and implementation of decided intent.
2. Intuitive recognises details from the information flow and matches patterns that feel right. Intuitive relates positively to creativity and difficulty-solving. 
3. Dependent seeks social conformance from others before decision-making. The decision-making process may be distracted and in need of social support.
4. Avoidant tries to postpone decision-making because of their low self-esteem. Still, avoidant is compliant with policies, doctrines, and orders. Avoidant is not suitable for creativity and tends to have high stress levels.
5. Spontaneous tries to accomplish decision-making as soon as possible. Spontaneous does not like conflict situations but perform well in rash decision and high-risk situations.

Human vs Machine Decision-making in Future Battlefield

The section fuses the tenets of tactical combat with visible transformations and tries to reflect these new situations in human-centric and machine-centric decision-making as featured in previous sections. Table 3 illustrates the outcome of the fusion from the view of two champions:

• Human is assumed as an average decision-making officer with 3-4 years of military education and about five years of professional experience with, possibly, one year of experience gained in live tactical action. 
• Machine is assumed to be a high-performance computer running a combination of continuously learning algorithms, expert algorithms, and pre-trained algorithms with real-life or synthetic data. Digital connectivity is supposed to be at combat cloud level . 

Table 3: Human vs Machine decision-making in transforming tactical combat environment

Transforming tenets of tactical combat feature decision-making challenges	Human	Machine
Transparency increases information and requires more computing power to make sense of collected data. Tactics prefer smaller, profoundly dispersed, manoeuvrable effectors, which swarm for effect, and retreat quickly.	Available data and information may overburden the cognitive ability to comprehend the situation.	A machine can recognise images, find patterns from large data mass, and forecast complicated, interdependent behaviour.
Effect calls systems understanding for system-wide impact. Dispersed effectors are harder to control and coordinate. Software-defined precision requires better target acquisition and configuration.	The adversary must be understood as multi-dimensional actor-network (Inglis and Thorpe 2019). Dispersed effectors require coordination of larger volume of details.	A machine can map the COA spectrum, model complicated, interdependent systems, and optimise the action of small effectors.
Sustainment of distributed, cyber-physical platforms requires more flexible and expert maintenance.	Rising complexity of critical paths on availability or sustainment may overwhelm cognitive capacity under stress.	With a digital-twin model and scenario-based simulation, a machine creates an overall logistics picture and can optimise sustainment.
Awareness is achieved by delegating sense-making to lower cooperative level or improving the information management ability of a steeper, hierarchical command structure.	Socio-cultural structures and beliefs handicap the application of the optimum C2 method.	Socio-cultural structures do not constrain a machine, and it can act even with partial information environment.
Urbanisation increases entropy, slows the tactical pace, increases casualties, raises the need for sustainment, and makes the environment and situation harder to understand.	The urban environment increases entropy and requires more innovative decision-making.	A machine makes sense of complicated situation even with partial information, recognises faster volatile behaviour, and optimises effort and sustainment.

A Company Commander Meets an Ex-Machina Battle Captain

When a Human Commander meets an Ex-Machina Captain within a tactical scenario on a future battlefield, the parties of combat may have the different abilities for decision-making. In situation with equal forces, linear doctrines, and a reasonably stable battlefield, the company commander does not have a chance against Ex-Machina. A creative human commander may gain an advantage in more chaotic conditions and with innovative tactics. Are our military institutes educating agile officers? Still, higher man-machine teaming performance indications are positive in Dota 2 strategic game, but it remains to be studied in future articles.

 

Figure 3: Man vs machine in tactical decision making

Telecommunications service provider, Cyber security and European future

 Possible Evolution of European Society

Assuming that the Russia – Ukraine war will linger for several years without a final resolution (as Russia wants and Europe yields), the fact remains that the time for cheap Russian energy in Europe is passed. Consequently, the accelerated green transfer will disrupt European industry, energy-intensive manufacturing will vanish, and cyber-physical products and services will need to become the primary European export goods within the next five to ten years. Furthermore, Europe may compete with Asia and America with accelerated transformations in the industry (4th industrial revolution), focused science and technology investments (3D and AI-enabled engineering and design), getting rid of geographical distance (Metaverse) that constraints human collaboration, man-machine teaming that accelerates the design and manufacturing performance, open data that provides large enough models for human and machine behaviour, and with forward-looking European market (EU digital acts). On the other hand, the European future depends on fewer younger generations who can disrupt industry, economy, and finance by teaming with machines as the population ages. Finally, Europe needs more coherency to deal with energy transfer, digital transformations, total security, and protecting political and economic interests.

Figure: Digital Compass for Europe 2030 (DigitalEU)

Probable Evolution of Technology

The migration journey starting with digitisation, following digitalisation and further digital transformation, proceeds at a pace defined by knowledge, competency, cooperation, business, digital maturity, and trust. (Andrews, et al., 2018) Nevertheless the complexity, the rate of change has been unforeseeable since digitisation impacted over 50% of the world population within two decades. (UN, 2022) Currently, the world feels the impact of the following three waves of evolution in information and communications technology (ICT):

1. Wave: Mobile Internet and Platforms

• The Internet with IP protocol, WWW and Browser
• 3-4G providing mobile data connection
• Smart mobile devices
• Platforms for social behaviour and economic transactions (Kenney & Zysman, 2016)
• Big data and business analysis/intelligence

2. Wave: Cyber-physical products and services

• 5 G provides near-zero latency connections for masses of connected devices
• The Internet of Things will produce 75% of organisations' data by 2025 (Stackpole, 2022)
• Migration of algorithms and machine learning automate digitised processes and provide a variety of man-machine interfaces
• Cloud computing provides computing power for services like IaaS, PaaS, and SaaS, which are easy to replicate and provide

3. Wave: Real-time networks of machines and Metaverse for humans

• Non-latency and high bandwidth access networks (Wi-Fi 6, 5G and 6G) are connected through fibre optical connections for networks able to slice capacity for immersive 8K perception for humans and real-time connections between machines.
• Quantum technology will increase computing performance, disrupt encryption, and improve the sensitivity of sensors, accurate timing, and communications bandwidth. (Johnston, 2021)
• The automated function of networked machines enables the 4th industrial revolution, autonomous transportation, and smarter cities.
• Edge computing and data-driven machine learning improve the level of machine cognition (Brown, 2022)
• Digitisation and increasing connected devices will increase the amount of data by 2025 to 175 Zettabytes. Human cognition requires machine support and smart data to identify any pattern from the amount of data. (De Goes, 2013)
• Human-machine interface migrates from screen and keyboard to 3D Metaverse. (Gartner, 2021)

Europe has already lost wave two because US and China-hosted platforms have engaged most of the social, economic, and financial transfers, prominent US-borne LEO satellite constellations will compete with terrestrial wideband access to the Internet, integrated circuits manufacturing is outsourced, and the majority of software development takes place in US, China, or India. Furthermore, China pushes its cheap infrastructure and automation packages to global markets.

Wave three still provides an opportunity for European engineering, democracy, and economy, as Europe has some advantages in science and technology (S&T) together with active innovation and entrepreneurial culture. However, Europe will benefit from this opportunity only if the transformation is faster than the more voluptuous but slower competitors. Moreover, besides strong S&T, the transformation requires a supportive environment for small and medium enterprises (SMEs) that provide added value to common markets. Therefore, the European availability of capital, infrastructure, services, channels, supply chains, platforms, and cooperation networks are essential enablers.

Information Security Remains Essential for European Future

Since the disrupting transformation needs to happen faster than any previous journey on the evolutionary path, there will be several critical hurdles to overcome. Mitigating these hurdles requires a social contract based on trust within the democratic political and liberal (venture capitalism, individualism, private property) economy systems. While society and its services are digitising faster than ever, digital trust  has become a foundational enabler. Suppose people lose their trust in digital services, cyber-physical products, the information provided by authorities, digital healthcare, or smart facilities they live in. In that case, the transformation will halt, and the European opportunity to gain from the ongoing development wave will be lost.

Naturally, fast development produces mistakes and failures. Hopefully, industry and service providers will learn quick enough to keep the negative impact small and short. Nevertheless, the problem becomes more severe because the state-level competitors intentionally fragment digital trust while generating an advantage for their authoritarian style (loss of privacy, big brother control, new class society) cyber-physical services. (Fleming, 2022)

In conclusion, the inside and outside sources of security failures need to be managed better than during the previous waves of digital evolution. The fundamental ways of mitigation include, for example:

1. The digitised national critical infrastructure must be more robust and resilient against failures. In addition, the whole supply chain of components intended to create critical infrastructure needs inbuilt security (processes like SecDevSecOps) . 
2. All operators of critical infrastructure services need to have preventive, real-time monitoring, and reactive measures to manage cyber behaviour and possible violations in their area of responsibility. In addition, security operations require automated threat analysis, behaviour monitoring and reaction to incidents because human responses and persistence are insufficient.
3. The edge processing and storing of data requires distributed security policy and trust between operators and users. Therefore, data security that supports low-latency implementations becomes crucial for new services supporting green transfer, 4IR, smart cities, design & engineering and automated traffic.
4. Identity and access management in the digital realm create the foundation for trust. Notably, the exponentially rising number of connected devices will challenge average enterprises. A service provider or broker would make it easier for enterprises to improve their automation with trusted machine-to-machine transactions.
5. The security processes for development and operations take time to mature. Only at higher maturity levels will the processes systematically learn from mistakes and near-misses and improve their performance and quality. Unfortunately, SMEs do not have time to establish teams with high process maturity. Hence, they need providers or jump-start partners to accelerate their abilities.
6. Europe does not educate competent people enough to suffice for all entities to take care of their security.  Furthermore, small enterprises do not have time to establish security to meet higher digital trust. Therefore, security service providers and B-to-B cooperation are essential in building digital trust between all stakeholders.
7. A Service provider must comply with existing and emerging legislation of European Digital Markets, Data Privacy and Protection, sustainable digital infrastructure, etc. (EU, 2021) The compliance requires both in-organisation and third-party auditing, multi-country cooperation, and transparent performance indicators.

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Brown, S., 2022. Why it's time for 'data-centric artificial intelligence'. [Online] 

Available at: https://mitsloan.mit.edu/ideas-made-to-matter/why-its-time-data-centric-artificial-intelligence [Accessed July 2022].

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[Accessed July 2022].

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Fleming, J., 2022. Director of Government Communications Headquarters, UK [Interview] (11 October 2022).

Gartner, 2021. The IT roadmap for digital business transformation. [Online] 

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[Accessed 2022].

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Data as an Enabler for Global Development and Interstate Relations from a Military Viewpoint

 Summary

The paper provides one logical scenario for global development, interstate relations and possible confrontation in Northern Europe from a military viewpoint with a data-centric flavour.  The aim is to provide a model for use in national defence planning.

In this scenario, exponentially extending digitisation and use of digital technology enforce production (e.g., big data) and use of data (e.g., data economy).  The extent of data transfers processes with automation, user interfaces (XR/Metaverse), and increases the amount of information.  Moreover, improving understanding with human competency and machine learning changes the behaviour of a socio-technical system.

The first wave of global competition for digital dominance is ongoing.  Since the cyber environment is an international artificial structure, it does not fit under traditional national or international governance structures.  Mingled powers of open market and governmental control have created digital colonisation, where the US-based corporates and China dominate the cyber environment, its services and content.  Some countries like Russia, Iran, Turkey, Vietnam, and the UAE are actively trying to protect their national cyber infrastructure by technically filtering the content and services of the Internet.  In addition, European Union uses regional regulation to protect the sovereignty of data and the common market. 

The next wave of digitalisation will build up faster and will be about 2-3 times larger than the first wave measured in the amount of data.  The second wave may transfer the current digital dominance if countries are digitally mature and digital trust is firm enough.  The ongoing development transfers international dependencies and enforces different power politics.

The contemporary militarisation of the cyber and information environment has culminated in the Russian power projection 2014-2022.  For example, Ukraine stores its nationally critical information abroad, safe from the Russian invasion.  Russian operational preparations included cyber, data, and information impact joint with kinetic effects to create electrotechnical shock during February 2022.  Furthermore, Russia arranges the media, social media, and cyber infrastructure in their captured areas of Donbas to gain control over public opinion. 

The current indication of data valuation in military operations and future possibilities of digitalisation will change the coming confrontation between states.  Therefore, the transformation of international relations needs to be understood in national defence preparations.

Evolution of Information and its Use

The evolution of production, storing and processing of information impacts humans and organisations at physical, information and cognitive levels. (Walton, 2019) In essence, information supports all structures to improve the probability of intended results and minimise harmful outcomes. (Christian, 2018) Furthermore, digitising makes information (data) easier to replicate and disseminate, making it more critical to collect and process data for humans, organisations, and global systems to cope with accelerated change and create new knowledge. (Thorpe, et al., 2008) As the perceived value of data increases, the metrics of data (i.e., pace, friction and quality) (Walton, 2014) turn out to be more critical for economic and social systems. Fast forward to the evolution, large amounts of data enable humankind to take steps toward superintelligence in enhancing human cognition with artificial intelligence and developing autonomous artificial intelligence. (Bostrom, 2014) As information grows (Hidalgo, 2015), Table 1 provides a view of some evolutionary information steps and examples for practical applications.

Table 1: Some evolutionary steps of information

Steps of Evolution	Enabling techniques and capabilities	Examples
Transfer of genetical information and organic learning	Genetical heritage	Revolutionary change emerges from genetical variations (i.e., mutations, natural selection, genetical transfer, specialisation) (Saetre & Ravinet, 2019)
Transfer of information orally	Development of language	Songs, stories, and sagas in the transfer of information over generations. Communication and cooperation advanced human and social survival so much that signs and voices developed into words. In support of explaining more abstract things, grammar and sentences emerged. (Nowak & Krakauer, 1999)
Written transfer of knowledge	Art of writing and printing	1440 Gutenberg's printing machine 1774 Telegraph 1829 Typing machine 1876 Telephone 1894 Radio 1920 Television 1923 Newspaper
Creation and dissemination of content in electrical means	Analogue management of voice and pictures	Development of telephony, radio, and television technology. The emergence of the movie industry and radio- and television companies. (NIMC, 2019) 1950-1960 spreading of black and white television networks 1960 spreading of FM radio networks 1975 video recorder 1981 Personal computer
World Wide Web (1 and 2), Social media, Mobile applications	Digitation of analogic information = DATA	The revolution of digital channels and content usage from 1995, 16 million Internet users to 5.3 billion users by 2022. The smart mobile phone has become a primarily used device to consume content on the Internet as the average user spends 3.15 hours with the phone. (Wait, 2021) Over 1.96 billion web pages offer digital content and services, of which over 38% are hosted in the USA. (W3Techs, 2022)
Metaverse	Digital text and pictures migrate to a 3D virtual realm (Web3) in the human-machine interface	Internet of Things, 5G mobile networks, edge computing, artificial intelligence, and metaverse user interfaces. Lower cognitive level machines transfer information, learn from each other and create content for humans cooperating with them through virtual/extended reality interfaces. 2003 RFIF commercial launch 2008 EU recognises IoT 2010 China announces IoT to be a key to the industry 2012 Switzerland launched the "Smart City of Switzerland" project 2013 low-price processing platforms Arduino and Raspberry Pi gain commercial recognition 2025 foresees over 70 billion IoT devices connected. (Khanna & Kaur, 2019)
Cognitive machines	Machine-to-machine information transfer and artificial knowledge become more critical than information presentation in human-machine interfaces.	Higher cognition level machines produce, learn and process information to create artefacts like cyber-physical products or social services. (Brynjolfsson & McAfee, 2014) Human migrates from the subject (producer) to the object (consumer) concerning knowledge-based goods. (Tegmark, 2018) It is estimated that in about 2035-2040, artificial intelligence will be able to: ·       Cognitive applications at the level of human ·       Learn from data or by observing action faster and more precise than today ·       Possibly replicate autonomously ·       Create art, compose songs, and write books and papers. (Chowdhury, 2021)

Evolution is not linearly progressing but a combination of several phases affecting at the same time. Hence, one may argue that all steps of evolution are present and somehow interrelated with each other globally. The part where digitisation has migrated information to data is called the cyber environment. Currently, the cyber environment is evolving with the exponential speed in almost all spheres of life in human society, e.g., electronics, robotics, digitalisation, digital transformation, and artificial intelligence. The performance of information technology doubles every 18 months. (Electrical 4U, 2020) The content of the Internet (WWW) is increasing by over 4 million hours daily (Schultz, 2019), meaning that the information base of humankind is doubling every 13. months. (Schilling, 2013) The Internet of Things and automation is increasing ten times within the next decade. (IOT News, 2020) All these information sources create data that can be read, rewound, reused and recontextualised several times. No wonder why humans experience information or cognitive overload (Kirsh, 2000) with their contemporary user interfaces and decision paralysis (Heath & Heath, 2013) with options for choice. Figure 1 illustrates how the evolution of data and digital technology changes the structure of human life from physical to social levels.

Figure 1: Digitisation of information changes the foundations of human society (CC-BY-ND Juha Kai Mattila)

Information Evolution Impact on Interstate and Military Relations

This section reflects the impact of information evolution on interstate relations in general and particularly in the projection of military force.

The Development of Data Centricity Between States

The digitisation of information and its exchange has changed governments and interstate cooperation. Since digitalisation has made it easier to produce and disseminate information and more people receive digital information than any other medium, the value of information is higher both in instate and intrastate governance. Data is perceived to have geographical value; it is a way to control behaviour; it provides ways of power in confrontation and competition.

1. Regional control of information

The European Union is an example of geographical control of data as part of the development of information society and economy. In 2018, European Commission launched the General Data Protection Regulation (GDPR) (EU, 2018) to define how data shall be protected, processed, encrypted, ensured privacy, transferred outside of the EU region (Sharp Cookie Advisors, 2020), and who is responsible for data in different phases of its life cycle. Furthermore, GDPR requires data to be stored within the EU region, so service providers must build a regional infrastructure and organisation to provide digital services within the region. With this regulation, the EU aims to build digital trust by ensuring coherent data processing for its citizens, preventing data migration to foreign countries hosting the platforms, and establishing principles for a knowledge economy within the region. (McKinsey, 2022) In addition, EU digital market and services regulation further enhances regional data economy ambitions. (EU, 2022) 

2. Protection of sovereign data environment

China and Russia are examples of information dissemination control and intention to align the domestic story when they strongly regulate the building and operation of national digital infrastructure for telecommunications, radio and TV broadcasting, media distribution and social media. (Vinkour, 2022) Furthermore, both countries strongly filter residents' access to Internet content (Kerner, 2022) and monitor their residents' digital and physical behaviour by collecting and analysing data. (Economy, 2018)

3. Information warfare

The information has become a tool (weaponised) in international confrontations. (Paganini, 2015) Although "war" may not be the correct word for the phenomena in the information dimension, it is commonly used. (Rid, 2013) An example is Iran, which declares to wage a "heavy information war", jang-e narm, (Jones, 2019) against the US, Israel, and some Sunni governments. (Eisenstadt, 2017) Iran perceives that the US and its multinational digital enterprises are attacking their national information sphere and defends against the attack using media networks and the "Halal Internet", a part of Iran's national digital infrastructure, in which they filter both access to the Internet and content of digital information. (RSF, 2016) In their offensive operations (KFCRIS, 2020), Iran uses, for example, malicious software (CCDCOE, 2012), spies (Greenberg, 2021), denial of service (The Intercept, 2015) and stealing of data. (US Department of Justice, 2020) The coalition led by the US, on their part, restricts the function of Iran's international value stream, runs information campaigns, disseminates western entertainment, and prevents the exportation of edge technology. (Jones, 2019)

4. Knowledge as a medium in strategic competition

The US-China global competition (Brookings, 2019) is an example of using knowledge to acquire innovations, immaterial rights (Sworn & Harjani, 2022), and shares in global value chains. (Gereffi, 2011) The US is trying to continue its dominance in the digital economy and military force projection. On the other hand, China aims to develop its digitalised autocratic governance and surpass the US as the global centre of power. China implements an authoritarian strategy of public sector investments and opening domestic markets to selected corporates.

In contrast, in the US, the private sector with large digital economy companies (GAFAM) (Lekkas, 2022), a vast number of small, innovative enterprises and commercial cooperation are the ways and drivers. (Brookings, 2021) Competition has partially conflicted with denials of products in markets and places (ZTE, Tesla), ban of providers in critical national infrastructure (Huawei), industrial espionage, and constraints for service providers. (Timofeev, 2020) Both countries use the features of the domestic market to enable data-driven, national capabilities with residents' access to digital services, digitalisation of industry and commerce, smart cities, digitalisation of value chains (financial transactions, logistics, eMarket places) and investments in science and technology (quantum computing, artificial intelligence, digital abilities, 5 G and above technologies and data). (Ghiretti, 2021)

5. Digital colonisation

During the last four decades, international commerce has grown tenfold, financial transactions increased eight times, and travelling expanded five times worldwide. (O'Neil, 2022) Data and its flows are part of the above activities. One who controls dataflows can also control transactions and activities. At the global level, data exchanges have two hubs: The USA and China. (Vuorisalo & Aaltola, 2021) Other countries and their residents use these two countries for global commerce, finance, telecommunications services and media streaming and social media platforms. Hence, most data concerning user identity, transactions, or digital behaviour remains within service providers in these two countries for their valuation. One can call this digital colonisation since other countries depend on these two hubs' digital services and have to release their public and private data for the benefit of these two countries. (Van Niekerk, et al., 2022) The collected data makes it easy to analyse digital behaviour, events, and content, enabling the prediction of future behaviour (surveillance capitalism). (Zuboff, 2019)  Data and related products are sold further for marketing, political manipulation, and military operations. (Kippo & Kemppainen, 2022) Current digital colonisation is part of the developing data economy and may change when the next wave of technology migrates the flows of data from cloud to edge. (Baygi, et al., 2021)

In summary, knowledge, information, and data enable almost all international relations, from cooperation to conflict. Governments appreciate the value of data and information as a medium both in a domestic and global environment. As the digitisation of information proceeds and the cyber environment enlarges almost exponentially, governments seek new ways to project their power and gain influence with the means of diplomatic, information, military, economic, finance, intelligence, and law enforcement (DIMEFIL). States wield these means through ways of compulsion, institutional, productive, and structural to create an effect in the information dimension, impact physical data processing or transfer and change human behaviour through cognitive or social influence. Their strategic approach is:

1. First, to break the trust between governmental institutions, citizens, and organisations. 

2. Second, to create confusion, mistrust, fear of violence, terror, and feeling of compulsion.

3. Third, feed in an alternative story that changes decision-making or social behaviour according to the attacker's will. 

Figure 2 illustrates a model to describe a data-driven engagement between states.

Figure 2: A view of the use of information as part of the interstate process (Mattila, 2022)

Military Force Benefits from the Evolution of Digitised Information

Global and social transformation concerning information will also impact military affairs. Therefore, the military will use digitised information, data, and knowledge depending on adapted strategic posture (Mattila, 2020):

• Pathfinder military tries to use the edge of advanced technology as fast as possible while pursuing technical dominance over potential adversaries (China's intentions).
• Operational military tries to apply digitalisation and data to improve their forces' operational and tactical performance to gain/keep an advantage (e.g., ISIS).
• Evolutionary military use data at their own pace as technology has matured to fit their risk appetite (most European Forces).
• Protective military perceives to have achieved dominance over potential adversaries and tries to sustain the existing advantage (USA).

Figure 3 provides quadchart of these strategies.

Figure 3: Quadrant of military development strategies (CC-BY-ND Juha Kai Mattila)

The following four cases provide examples of different strategic implementations:

1. The US military forces have tried to sustain their perceived technical dominance by preventing others from accessing their technological advantage (Protective):

• 1993–2003 digitalisation of operational level command and control (Network Centric Warfare) (Chizek, 2003)
• 2020 launched the preparation of tactical level digitalisation (Joint All-domain C2) (Clark, 2020)
• 2022 preparation of digitalisation in other parts of US military institute (Chief of Digital and Artificial intelligence) (Vergun, 2022)

2. The Russian armed forces have adopted the benefits of digital evolution with the following examples (Operational):

• 2007 Russia integrated cyber effects as part of their information operations against Estonia.
• 2012 During the Chechnyan war and Putin's re-election, the leadership of Russia understood that control of the information realm is critical for staying in power. (Giles, 2012)
• 2014 during the manning of Crimea, Russia applied deception, metanarratives, and cyber means to manipulate the perception of a variety of audiences. (Pynnöniemi & Racz, 2016)
• 2016 the information security doctrine defined the information area of operation, which includes technology and cognitive components. (Lilly & Cheravitch, 2020)
• 2022 the Russian leadership can control domestic digital infrastructure, broadcasting, social media, and media content. (Vinkour, 2022) (Budnitsky, 2022)

3. The Islamic State of Iraq and Sham (ISIS) organisation, recruiting, information operations and operational command and control benefitted from civilian IC technology (Operational) as follows:

• ISIS used anonymous portals for file transfer and collaboration between jihadist parties. (Shehabat & Mitew, 2018)
• ISIS used social media platforms to recruit over 40 000 fighters from over 110 countries. (Ward, 2018)
• ISIS used digital channels for ways of strategic communication, coercion through publishing acts of terror, and manipulation through propaganda. (Pellerin, 2016)
• ISIS captured the telecommunication infrastructure in their area of operation and used it to support their command and control. (CJTFOIR, 2017)

4. The generation and operations of the IT Army of Ukraine is an example of diginative networked force aiming to reach a pathfinder ability to wield distributed denial of service (DDoS) and breaching attacks against Russian digital infrastructure: (Soesanto, 2022)

• A volunteer force was called in through Twitter, Facebook, and Telegram accounts creating a command channel with around 11500 participants.
• Next day, the command channel distributed the first assignment to attack against 31 network addresses of 31 banks, businesses, and government websites.
• Within three weeks, the cyber cluster had been organised into three services: the IT Army, the Internet Forces of Ukraine, and the e-Enemy.
• An example of fires control: After providing target information of IP address and four ports, various control channels distributed the target to around 18 800 effectors within 4 hours.
• Within three months of establishing the networked force, the cluster has attacked about 2000 Russian resources.

Almost all current military organisations and organised violence groups use data and digital technology, available or within their ability to use, for capabilities that improve force projection in conflicts. 

The Development of Data, Human and Machine Towards a Socio-technical System

Digitisation and the growing data change the human-machine relationship and cooperation, creating new and emerging capabilities. For example, in 1951, Allan Turing designed the first chess-playing machine. In 1997, the IBM Deep Blue machine won for the first time against a reigning human champion (Gary Kasparov) in that game. Currently, chess games are categorised so that machines are playing against machines, and human-machine teams are playing against each other. (Knemeyer & Follet, 2019) The development of human-machine interaction in a variety of games has indicated that:

1. A high-performance machine wins an expert human in seeking variations from a large combination of possibilities (10120). (Maharaj, et al., 2022)
2. A more intelligent algorithm with less computing capacity may win over a less intelligent algorithm with high computing performance. (Maharaj, et al., 2022)
3. A machine learning algorithm with a broader training data set can win a search-optimised designed algorithm. (Maharaj, et al., 2022)
4. A novice in good cooperation with a machine and following a high-performing process may win over a master who uses higher computing power but a weaker process. (Phillips-Levine, et al., 2022)
5. A less cooperating group of high experts will lose against the optimised algorithm. (Cabitza, et al., 2021)
6. Well-functioning team of experts may win against an optimised algorithm. (Cabitza, et al., 2021)
7. Lesser experts interacting better with each other, and their algorithm may win a less coherent group of higher experts using the same algorithm. (Cabitza, et al., 2021)
8. Everyone with an available computer and algorithm will win one team of experts with a laptop and algorithm. (Knemeyer & Follet, 2019)

In summary, a party whose human-human and human-machine interaction works better will probably win. In contrast, a massing of human-machine teams may have higher odds over a lesser number of teams. Improved data (pace, friction, quality), interfaces (human-machine and machine-machine), and social structures (e.g., trust, communication) decrease entropy and friction in a socio-technical system, as illustrated in Figure 4.

Figure 4: Core components and interfaces of a balanced socio-technical system (CC-BY-ND Juha Kai Mattila)

Military organisations have an advantage over other organised violence to generate balanced socio-technical systems since they control the force generation life cycle from R&D to lessons learnt of troops (human-machine teams). Specifically, the advantage enables the development of culture, competency, process, data, and technology in coordinated steps, experimenting with different combinations and keeping up with a continuous but balanced improvement. On the other hand, other organised violence entities do not have the above control but are dependent, for example, on available products, data, service contracts, and recruitable competencies. 

Ongoing Evolutionary Steps in Digital Technology and Usage of Data

The migration of digitisation, following digitalisation and further digital transformation, proceeds at a pace defined by knowledge, competency, cooperation, business, digital maturity, and trust. (Andrews, et al., 2018) Nevertheless, the rate of change has been unforeseeable since digitisation impacted over 50% of the world population within two decades. (UN, 2022) The developed countries are feeling the impact of the following steps evolution:

1. Mobile Internet and Platforms

• The Internet with IP protocol, WWW and Browser
• 3-4G providing mobile data connection
• Smart mobile devices
• Platforms for social behaviour and economic transactions (Kenney & Zysman, 2016)
• Big data and business analysis/intelligence

2. Cyber-physical products and services

• 5 G providing near-zero latency connections for masses of connected devices
• Internet of Things will produce 75% of organisations' data by 2025 (Stackpole, 2022)
• Migration of algorithms and machine learning automate digitised processes and provide a variety of man-machine interfaces
• Cloud computing provides computing power for services like IaaS, PaaS, and SaaS, which are easy to replicate and provide

3. Real-time networks of machines and Metaverse for humans

• Non-latency and high bandwidth access networks (Wi-Fi 6, 5G and 6G) are connected through fibre optical connections for networks able to slice capacity for immersive 8K perception.
• The automated function of networked machines enables the 4th industrial revolution and autonomous transportation
• Edge computing and data-driven machine learning improve the level of machine cognition (Brown, 2022)
• Digitisation and increasing connected devices will increase the amount of data by 2025 to 175 Zettabytes. Human cognition requires machine support and smart data to identify any pattern from the amount of data. (De Goes, 2013)
• Human-machine interface migrates from screen and keyboard to 3D Metaverse. (Gartner, 2021)

The above steps are foreseeable scenarios. Nevertheless, the developed data and digital technology will change work, economy, governance, and free time in societies, but the pace of transformation is determined by social, political, and business decisions. (Kenney & Zysman, 2016) Furthermore, the transformation does not come without risks and failures. Data and algorithms-based processes, information and decision-making are more abstract, hence harder to comprehend and explain. Consequently, transformation produces both intended and unintended results (DRCF, 2022), including wicked system problems created by well-meaning intentions. (Rainie & Anderson, 2017)

Possible Evolutionary Scenario in Nordic Countries

Based on the foresight and trends explained in previous sections, this part uses the scenario planning method (Chermack, 2011) to describe a possible future scenario further. This scenario is loosely based on linear extrapolation and prospective systems analysis (De Jouvenel, 2000) of the evolution within the past ten years in Northern Europe. This approach does not include forecasting (Van der Heijden, 2000), the typical second component of futures research. Firstly, the scenario method defines foundational assumptions and then creates a general scenario of 2032. Thirdly, it sets assumptions about the evolution of the threat environment and fourthly, it provides a confrontational scenario between state entities in Northern Europe in 2032.

Possible Development of Societies and Economy in Northern Europe 2032

The scenario "Feasible" is based on the following assumptions of development by 2032:

1. The Nordic income distribution society survives the Russian-created energy crises starting in 2022. The democratic system serves citizens sufficiently even when the feeling of polarisation increases. Nevertheless, the situation does not create inner conflict yet. The economic and financial deepening of the European Union proceeds slowly and only gradually improves the EU market region compared to more progress leveraging US and China markets.
2. Government structure and services are digitised gradually, but digital transformations occur elsewhere. Automation and the 4th industrial revolution transformed services, industry, traffic, and logistics. Regional software development and data engineering competency have an opportunity to grow with the 4th industrial revolution and, finally, replace the global platform service providers. 
3. Nordic countries can sufficiently keep their working-age population producing wealth and increase the educated younger generation through labour-based immigration and international students staying in the country after graduation. Nevertheless, public nursing and education cannot replace home nurture and Metaverse addicts too much. Hence, social exclusion continues growing and fuelling polarisation. Moreover, the major tax-paying part of the population feels more critical about the increasing amount of pensioners, long-term unemployed, and uneducated. 
4. The energy crisis, which emerged in 2022, accelerates the transfer of European energy production. However, industry, products, and consumption suffer from higher energy costs than in the US and Asian markets. For example, China will leverage their cheaper energy bill and improve competency assets in increasing their productivity and gaining more global markets with cyber-physical products. The decreasing fossil energy incomes may increase social unrest in current OPEC and other major oil-producing countries and possibly launch "Arab Spring"-like uprisings. (U.S. JCS, 2016)
5. People spend their time more in virtual worlds than in traditional broadcasting, media, and social media channels, where their system 1 (Kahneman, 2011) will get faster and more complete needs fulfilment. Global gaming and social media companies can renew their offerings fast enough to sustain their market share and continue consolidating their entertainment and media portfolios. Regional media companies may survive in niche segments either sponsored by public resources or narrowly targeted advertisement selling.
6. The physical and mental well-being becomes more fragile, and polarisation for those physically active and with live social networks and those isolated in a virtual world and staying home defines social structure.
7. The existential threats (nuclear holocaust, climate change, scarcity of resources and distinction of species) gain more evidence in everyday life, and their secondary impact (refugees, unnormal weather, threat with weapons of mass destruction) change public opinions and political decision-making. Furthermore, the fast progress of digital and biotechnology changes the everyday work and economic structure too quickly, creating social unrest.

The assumptions mentioned above may lead to the following scenario, "Feasible 2032", from a socio-technical perspective:

• Energy crises, reaching for carbon neutrality and culmination of the societal structure polarise public opinion and fracture democratic consensus-seeking. The number of employees decreases, and the unemployed increases while the industrial culmination automates industry, traffic, governance, and services. As work-based income creation becomes challenging, the public sector may be forced to provide meaningful activities for the inactive part of the population. Maybe even longer military service becomes an option.
• The global platform and media providers are so dominant in the segments of entertainment and social media. Hence, the regional providers have not survived. The US and China continue competing and extending their data colonisation of centralised platforms worldwide. 
• People fulfil their need to be accepted in virtual environments and second life -platforms, where social code of conduct may differ remarkably from the rules of social cooperation in the physical world. (Keltinkangas-Järvinen, 2010) Empty home, ritual religion, and negligible fatherland do not enforce national feelings or willingness to sacrification on behalf of the country. The structure of social capital is in transfer (Putnam, 2000), making a postmodern human more fragile, easier to manipulate and seeking protection of authority during crises. (Timcke, 2021) Autocratic regimes may have better advantages than democratic systems for strategic and operational surprises in interstate power projection.
• The human-machine interface is mostly 3D -virtual (Metaverse) (Ball, 2022) or required in the 4th Industrial Revolution (Kopletov, 2020). A legacy interface like screen, keyboard, and mouse have migrated to miniaturised VR or XR devices, widely used for studying, technical design, creating arts and music, and consuming digital products.
• The data-driven enterprise processes data in real-time, data supports all corporate decision-making, cooperation, and business process performance. Agile data sources are available for all processes, data is valuated as a product, data management is automated, and every corporation is a member of a more comprehensive data ecosystem, which supports the control of the entire value chain. (McKinsey Digital, 2022)
• High-performance computing, quantum processing, and digital modelling enable R&D, design, and creation of digital twins for cyber-physical structures and products, which helps engineering sciences to develop and migrate complex socio-technical systems. However, culture and competency deficiencies remain significant obstacles to implementation and adaptation.
• Faster digitalisation than in the rest of Europe and over 5% (of GDP) of investments in science and technology keep the Nordic Countries on top of the Global Talent Competitiveness and Global Innovation Index with improved utilisation of talent and innovation. Therefore, foreign competency and capital are available for new Nordic enterprises.
• 5/6 G networks, edge computing, machine learning and connected things (IoT) have transformed the business processes and models of Nordic industry, logistics, infrastructure services and health care to compete successfully in providing cyber-physical products and services to the slowly improving European market. 

The confrontation scenario and its possible development in Northern Europe in 2032

"When it comes to predicting the nature and location of our next military engagements, since Vietnam, our record has been perfect. We have never once gotten it right, from the Mayaguez to Grenada, Panama, Somalia, the Balkans, Haiti, Kuwait, Iraq, and more—we had no idea a year before any of these missions that we would be so engaged."

- U.S. Secretary of Defence Robert Gates (Gates, 2011)

"I don't think there's been a time in the history of warfare where things have been changing as rapidly,"

- U.S. Chairman of the House Armed Service Committee, Adam Smith (Williams, 2022)

Assuming that the threat environment evolves within the next ten years in Northern Europe as follows:

1. After losing most of its military land and artillery forces in attrition warfare against Ukraine, domestic income from fossil energy remains low, and import restrictions on western technology remain in place because of war crimes, Russia has not been able to re-establish and modernise its military might. As a result, to some degree, Russian space, air, and naval forces sustain their ability to control areas of operation and support power politics. However, the Red Army has significant challenges in the digitalisation and automation of its weapon and sensor platforms. Therefore, the operational art seeks to exploit anything existing, asymmetric ways of warfare and innovative ways to utilise commercial technology and products.
2. The Russian information environment remains under the control of an autocratic regime, and domestic opinion manipulation uses themes of religion, nationalism, and fear of outside enemies to maintain Slavic integrity. Moreover, the tacit memory between individual citizens recalls the massive loss of human power in the special operation of 2022 – 2023.
3. The Russian cyber environment is enclaved from the Internet with tight content and packet filters, and Russian platforms and services compensate for global digital services. Moreover, with Chinese support, Russia has implemented a vast surveillance system to gain more control of the physical and logical behaviour of their residents.
4. In Europe, populism using conservative values and totalitarian flavoured regimes create confrontations, but economic and infrastructure dependencies stabilise relationships. Nevertheless, polarisation and ideological powers generate terrorism within Europe.
5. Existential threats in Figure 5 and their secondary effects create refugees and inequality that impact European public opinion and deteriorate stability.
6. Digitalisation and proceedings in biotechnology transfer societies and create new weaknesses and connections in trust relations between citizens, government, and power sources.
7. The competition between China and the USA projects market and product restrictions also in Europe.
8. The integration of NATO and their defence capabilities have evolved following the Russian power projection 2014-2023 and can deter 3rd generation adversaries. As a result, northern European defence systems are integrated, and Nordic military capabilities are used seamlessly.
9. Instead of a hierarchically commanded, industrially generated military force, a knowledge economy-driven military force is a value network of military organisations, corporations, and non-profit organisations, which generates, supports, and uses vertically and parallelly synergetic military power. The military capability of the defence value network is based on information exchange, trust, and common language. (Niemelä, 2002)

Figure 5: One state-level threat model (Mattila, 2022)

The above assumptions and previous generic scenarios may create the following confrontation scenario between Nordic countries and Russia: (U.S. JCS, 2016) (RAND, 2020) (Kelly, 2022)

a) Strategic dimension

• The Russian regime tries to contain its position and privileges by controlling tightly domestic information environment and opinion creation. Moreover, Russia tries to create chaos in their neighbours' public opinion creation and political decision-making. 
• Fabricated conflicts are waged as infinite (Carse, 2013) information operations a la Lenin (Strachan, 2008), adjusted to create enough leverage for domestic themes and spread confusion outside Russia. Russian goal is a continuous confrontation (according to the struggle of classes tradition) from a higher moral position that provides motivation and coherence to Slavic people. Therefore, sustaining the control and regime of Russia.
• War, by definition, is too black and white for recent confrontation and conflict. The conflicting parties are not only states. Violence is not a military monopoly. The scarcity of conventional resources creates innovative ways of power projection and manipulation. At the core of conflict lies the control of the attention of different audiences. (Ford & Hoskins, 2022) 
• Russian sources of power in international confrontation are more comprehensive than the traditional diplomacy and military. Other means include information, economics, finance, intelligence, and law enforcement, together with the leverage of other threats in Figure 5 and their impact. (Mattila, 2022)
• Besides compulsory ways, Russia uses institutional, productive, and structural avenues of effect to culture confrontation, create chaos in neighbours, and maintain coherency within the country.

b) Operational dimension

• Russian centralised, autocratic command of effectors and avenues of effect (e.g., political, information, economy, finance, social, technical, military, institutional) generate the ability for joint operations. The joint operations may be used, for example, to found, ameliorate, contain, constrain, deter, coerce, degrade, corrupt, penetration (Hoffman, 2018) and destroy. (Mattila, 2011)
• Russian operational art seeks targets from adversary society's entire value stream, aiming to deteriorate information transfer, digital trust, social integration, and logistic chains between entities.
• Besides conventional military forces, Russia is using sources of power organised in ideological sects, criminal groups, terrorists, corporations, international organisations (NGO), new cooperative institutions (U.S. JCS, 2016), governmental organisations, military corporations (e.g., Wagner), militias, other states, and coalitions. (Creweld, 1991)

c) Tactical military dimension

• Russia seeks asymmetric avenues for impact and combines tactical capabilities through all six military domains: space, air, maritime, land, cyber, and electromagnetic.
• Authoritarian and deep hierarchical command and control culture minimises the tactical level initiative, slows the pace of action (McChrystal, et al., 2015), and cements doctrinal or institutional organisational function.
• The conflict escalates to violence in metropoles, where an urbanised population provides enough physical and cognitive masses, polarisation is more apparent, and enough media and social media agents to enforce information impacts. (Brown, et al., 2019)

d) Information dimension

• Russia benefits from commercial and social behavioural data, which coordinates precise targeting in the Nordic socio-technical systems.
• Machine learning and vast amounts of data enable human-machine cooperation, which, following an optimal process, always wins pure human sense- and decision-making.
• Development cycles and product life cycles are shorter. Therefore, competing organisations need to be more flexible in their strategy and agile in their production for creating cyber-physical products and services. Model-driven design, digital twins, and simulation are profound enablers in continuous integration and release.
• Information dimension enforces all confrontation and conflict in other avenues of effect with impact at cognitive and social levels. (Ford & Hoskins, 2022)

e) Technical dimension

• The extending digitisation of the Nordic critical infrastructure increases Russian opportunities for cyber attack vectors and physical level vulnerabilities for kinetic effect.
• The internationally integrated and interdependent, complex digital infrastructure includes vulnerabilities to impact critical functions via secondary systems and supply chain.
• Consolidated Metaverse provides several avenues of effect for individual-level system one need satisfaction.
• Converged functions and miniaturised technology generate autonomous, multifunctional, and multisensory consumables, which may be used as such or with minor adjustments for violence.

The above-defined scenario may be used to develop state-level forces for international confrontations.