2022-10-17

Developments in Quantum Science and Opportunities for Military Use

 Military Aspirations Concerning Quantum Science

Revolutions in quantum science have generated military abilities in two waves of revolution:

1. Quantum revolution generated technologies that enable nuclear power, semiconductors, lasers, magnetic resonance imaging and other imaging technologies.

2. Quantum revolution focuses on controlling individual quantum systems (atoms, electrons, photons, quasiparticles). Most of these dual-use technologies aim to improve measurement capability, sensing, precision, and computation performance. (Dowling & Milburn, 2003)

The USA launched National Quantum Initiative 2018, and U.S. DoD has joined the programme to “better enable the United States to maintain its global leadership in quantum information science” and “by supporting existing efforts and accelerating critical growth in the field.” (Gould, 2021)

“The quantum world hosts a rich variety of physics that could enable functionality far beyond what traditional technologies can achieve,” the National Security Agency said in a press release. “By probing and manipulating phenomena that occur at the single particle scale, the emerging field of quantum information science (QIS) aims to create new forms of computing, sensing and communications that could revolutionise how we process and transmit data.” (Harper, 2020)

  • In the near term, super-accurate clocks and quantum-based sensors could aid with precision navigation and timing, which is critical for military missions.

  • In the future, U.S. forces might have to operate in GPS-denied environments, and Pentagon officials are looking for alternatives to space-enabled navigation.

  • Quantum computing is information compression and subsequent acceleration, allowing computers to simultaneously process seemingly infinite possibilities. 

  • Experts are also eyeing quantum communications for defensive and offensive purposes. (Sayler, 2021)

In 2016, Beijing initiated an effort to achieve a quantum technology breakthrough by 2030. The planned US$10-billion National Laboratory for Quantum Information Sciences in Hefei, Anhui province, leads the nation’s drive for quantum computing and sensing. (IISS, 2019) 

The United Kingdom’s Defence Science Expert Committee has noted the importance of improved gravity sensors (quantum gravimeters), which could detect moving masses underwater, such as in submarines. (IISS, 2019)

Russia is also investing in quantum computing at the Russian Quantum Center, but it has not committed the same level of resources as other nations and remains behind China and the U.S. (IISS, 2019)

Figure 1: Announced public sector investments in Quantum computing (McKinsey) (McKinsey, 2021)

Some Interesting Applications and Proceedings of Quantum Science

Quantum computing refers to the utilisation of quantum information science to perform computations. Such a machine can be called a quantum computer, for example: (Krelina, 2021) 

  • A digital quantum computer is universal, programmable and should perform all possible quantum algorithms. On the other hand, classical computers can fully simulate the gate-level-based quantum computer. The difference is in resources and speed. For instance, the simulation of thoroughly entangled qubits increases the requirement of classical resources exponentially. 
  • Analogue quantum computer (Hamiltonian computation) typically uses quantum annealing. Quantum annealer differs from the digital quantum computer by the limited connectivity of qubits and different principles. Therefore, the utilisation of analogue quantum computers is more constrained but is still suitable for tasks such as quantum optimisations or Hamiltonian-based simulations. 
  • A Quantum simulator is used to study and simulate other quantum systems that generally are less accessible and is usually built as a single-purpose machine. The quantum simulator can be imagined as a non-programmable quantum circuit compared to a quantum computer.

Digital quantum computing has seen a fast evolution of:

  • 2023 IBM aims for 1121 qubits computer
  • 2022 IBM promotes their new z16 machine’s ability to handle real-time fraud detection for instant payments across the financial sector. (Saran, 2022)
  • 2021 IBM Eagle processor with 127 qubits (Rincon, 2021)
  • 2020 IBM Hummingbird with 65 qubits; Chinese superconducting processor with 56 qubits (Johnston, 2021)
  • 2019 Google Sycamore with 53 cubits; IBM Falcon with 27 qubits (van Amerongen, 2021)
  • 2016 IBM provided quantum computer as a service through their cloud (QCaaS)

In Quantum simulation, Siemens aims to use proprietary quantum methods to solve complex non-linear differential equations. These will be used in Siemens’ computer-aided product design and testing software in digital-twin simulations to support clients in the automotive, electronics, energy, and aerospace sectors. (Saran, Siemens looks at quantum computing to accelerate simulations, 2022)

Quantum optimisation generates two outcomes: quantum-inspired algorithms and speeding up the classical heuristic optimisation process. Typical optimisation applications may be found in logistics, supply chains, traffic, and targeting.

Quantum-enhanced machine learning breakthroughs are waiting for quantum memory and quantum coding of data. However, earlier benefits may be gained from quantum sensing and imaging and ML applied to generated quantum data.

Quantum cryptoanalysis has algorithms ready but lacks computing performance. Shor’s algorithm can exponentially speed up the factorisation of large prime numbers used in RSA, D.H. and ECC. Grover’s searching algorithm reduces the brute-force time by half. Around 2128 quantum operations may be required to brute-force the 256-bit AES key. A regular computer takes around 70 years to break AES 256 encryption. (Allison, 2018)

Quantum communications use low-loss optical fibre or free-space channels (most realistic between satellites) and photons to transfer information. However, a network requires several repeaters or switches because of fragile photon transmission. 

Quantum key distribution (QKD) exchanges private keys over a separate connection and is encrypted at a photonic level. The encryption key is generated using a pair of entangled photons so the possible interception will be detected before the transmission even happens. The method extends the use of average prime numbers for mass encryption since the key is transferred separately and more securely. Naturally, a denial-of-service attack will suppress the whole key exchange and message transfer system. (Allison, 2018) In 2016, China launched the quantum science satellite “Micius”, which claims to demonstrate ground-satellite-ground QKD. (IISS, 2019)

Quantum sensing and metrology is the most mature area of quantum technology. Quantum sensors can produce precise information about electrical signal, magnetic anomalies and inertial navigation.

Quantum clocks are based on single-ion providing uncertainty below 10 -18, whereas current atomic clocks commonly provide around 2x10 -12 uncertainty.

Quantum navigation operates via a process called atom interferometry. If you cool atoms to just millionths of a degree above absolute zero, then hit them with beams of light, you can trick them into a quantum superposition. Each atom takes on two states simultaneously: moving and still. Each state reacts differently to forces, including gravity and acceleration. That allows you to measure things like distance more accurately than GPS—without needing a hackable signal from space. “These inertial sensors can be used wherever there is a need for a position or navigational information, and where a GPS outage is unacceptable, or GPS is unavailable.” (Tucker, 2021)

Quantum imaging systems exploit photon correlations allowing better noise suppression and higher resolution. Applications include quantum radar, lidar, quantum 3D, behind-the-corner, low-brightness, and medical imaging. 


Status of Quantum Science from a Military Viewpoint

China, E.U., and the U.S., among other states, are expecting a lot from research and development around quantum physics applications. From a military viewpoint, the application situation looks, for example: (Parker, 2021)

  • Quantum key distribution is mature and provides an untampered way of transferring sensitive encryption keys over fibre
  • Quantum clocks are tiny and accurate to provide much better accuracy than previous atom-clocks
  • Quantum sensors are more sensitive than conventional ones, although quantum radar application did not meet the DoD expectations in 2021.  
  • Quantum computing is advancing with speed – the problem is the programs. Currently, the most feasible applications are certified randomness, scheduling optimisation, route and fleet optimisation and site-selection optimisation. (McKinsey, 2021) Nevertheless, states are extracting or capturing encrypted data today to decrypt them in the future. (Vincent, 2021)
  • Quantum communications are in the prototype and demonstration phase, particularly in China. (IISS, 2019)



Bibliography

Allison, P. R. (2018). Prepare now for quantum computers, QKD and post-quantum encryption. Computer Weekly. Retrieved from https://www.computerweekly.com/feature/Prepare-now-for-quantum-computers-QKD-and-post-quantum-encryption

Dowling, J. P., & Milburn, G. J. (2003). Quantum technology: the second quantum revolution. Philosophical Transactions of the Royal Society. doi:https://royalsocietypublishing.org/doi/10.1098/rsta.2003.1227

Gould, J. (2021). Senators push quantum computing at DoD. C4ISRNET. Retrieved from https://www.c4isrnet.com/congress/2021/04/16/senators-push-quantum-computing-at-dod/

Harper, J. (2020). Pentagon Trying to Manage Quantum Science Hype. National Defense. Retrieved from https://www.nationaldefensemagazine.org/articles/2020/12/10/pentagon-trying-to-manage-quantum-science-hype

IISS. (2019). Quantum computing and defence. In IISS, The Military Balance 2019 (pp. 18-20). Retrieved from https://www.iiss.org/publications/the-military-balance/the-military-balance-2019/quantum-computing-and-defence

Johnston, H. (2021). Quantum advantage takes a giant leap in optical and superconducting systems. Physics World. Retrieved from https://physicsworld.com/a/quantum-advantage-takes-a-giant-leap-in-optical-and-superconducting-systems/

Krelina, M. (2021). Quantum technology for military. EPJ Quantum Technology. doi:https://doi.org/10.1140/epjqt/s40507-021-00113-y

Parker, E. (2021). Commercial and Military Applications and Timelines for Quantum Technology. Santa Monica: RAND Corporation.

Rincon, P. (2021). IBM claims advance in quantum computing. BBC News. Retrieved from https://www.bbc.com/news/science-environment-59320073

Sayler, K. M. (2021). Defence Primer: Quantum Technology. Congressional Research Service. Retrieved from https://news.usni.org/2021/05/27/report-on-military-applications-for-quantum-computing

Tucker, P. (2021). Quantum Sensor Breakthrough Paves Way For GPS-Free Navigation. Defence One. Retrieved from https://www.defenseone.com/technology/2021/11/quantum-sensor-breakthrough-paves-way-gps-free-navigation/186578/

van Amerongen, M. (2021). Quantum technologies in defence & security. NATO Review. Retrieved from https://www.nato.int/docu/review/articles/2021/06/03/quantum-technologies-in-defence-security/index.html

Vincent, B. (2021). China May Steal Encrypted Data Now to Decrypt In Years to Come, Report Warns. Defence One. Retrieved from https://www.defenseone.com/threats/2021/11/report-china-may-steal-encrypted-government-data-now-decrypt-quantum-computers-later/187025/


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.







Bibliography

Andrews, D., Nicoletti, G. & Timiliotis, C., 2018. Going digital: What determines technology diffusion among firms? Brussels: European Council.

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].

De Goes, J. A., 2013. `Big data is dead. What's next? [Online] 

Available at: https://venturebeat.com/2013/02/22/big-data-is-dead-whats-next/

[Accessed July 2022].

EU, 2021. 2030 Digital Compass, Luxemburg: Publications office of the European Union.

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

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

Available at: https://emtemp.gcom.cloud/ngw/globalassets/en/information-technology/documents/insights/the-gartner-it-roadmap-for-digital-buisness-transformation-excerpt.pdf

[Accessed 2022].

Johnston, H., 2021. Quantum advantage takes a giant leap in optical and superconducting systems. Physics World, Issue October.

Kenney, M. & Zysman, J., 2016. The rise of the platform economy. Issues in science and technology, 32(3).

Stackpole, B., 2022. The promise of edge computing comes down to data. [Online] 

Available at: https://mitsloan.mit.edu/ideas-made-to-matter/promise-edge-computing-comes-down-to-data [Accessed July 2022].

UN, 2022. The Impact of Digital Technologies. [Online] 

Available at: https://www.un.org/en/un75/impact-digital-technologies [Accessed July 2022].


2022-08-25

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.

2022-05-04

Feasibility Study of Possible UAS Projects for a Small Armed Forces

The short paper studies the feasibility (required resources, competency, and data) of building some UAS capabilities referring to efforts invested in similar capabilities in other countries. First section provides the essential requirement for development of autonomous vehicles. Second section gives a quick overview in trends for unmanning intentions. Third section provides some references and proposes options for a small armed force without a support of strong national defence industry.

1. Requirements for Autonomous Vehicle Development

Typically, the development of autonomous systems requires the following process:

  1. Creation of a generative adversarial network (GAN)  that can learn from data extracted from live or simulated combat engagements taking place in a relatively stable environment (air or subsurface)
  2. Data captured from combat engagement or created in a synthesised game
  3. Computer performance to run a high number of simulations to teach the GAN
  4. Platform to take the learned AI “driver” to a real environment and start testing and continue learning
  5. Feedback loop, re-engineering of GAN, and data bias-removing function to proceed with teaching and improving the performance of the autonomous function.


Furthermore, the following functions or components are required to gain autonomous  features on a platform:

  • Sense to gather information about engaging entities and their environment
  • Perceive and understand the collected data
  • Decide to optimise action based on possible scenarios and their outcome
  • Act as control of all physical and logical entities required for impact. 

2. Current Trends in Unmanned Vehicles Development

An advanced autonomous unmanned system is destined to evolve toward low manual intervention, high autonomy, and high intellectualisation, no matter whether it is for military or civilian use. 



3. Examples of Military Autonomous Systems and Required R&D Investments

The following table provides examples from different military autonomous/semiautonomous systems, their development efforts, and options for a small armed force to proceed with similar capability.

UAS Capability

Reference

Investments and time

Options for a small armed force

Unmanned Surface Vehicle

Cost-effective, enduring ISR vessel:

Saildrone Explorer[1] combines wind-powered propulsion technology and solar-powered meteorological and oceanographic sensors to perform autonomous long-range data collection missions in the harshest ocean environments.[2]

It navigates up to 12 months autonomously through large areas of the oceans based on waypoint-to-waypoint navigation through wind and currents.[3]

2012 Saildrone Inc. Established

2017 two pilot vessels

2019 Antarctic circumnavigation

2021 sailed into category 4 hurricane

2021 deployed in the Red Sea

Up to 2021, together, $174M venture capital raised

1. Acquire several of these and deploy. Concentrate on collecting data and creating models that understand better the oceanographic environment and build data sets for nextgen autonomous features.

Unmanned Combat Surface Vehicle

Multipurpose vessel for coastal defence:

JARI USV[4], CSIC developed an unmanned combat boat 20-ton multipurpose vessel with torpedoes, a vertical missile launcher, and air defence.[5] Remotely controlled, autonomous navigation, automated action, swarming with other vessels.[6]

2018 a mock-up model in ADD

2019 see trials with a prototype

2019 IDEX

2021 manufactured and ‘combat ready’ model in AirShow China[7]

 

1. Acquire JARI platforms and establish R&D cooperation with CSIC.

2. Acquire a testing vessel with IP and establish an Open Hackathon to get concepts for autonomous features. Continue as an open-source development programme.

 

 

 

 

Unmanned Sub-Surface Vehicle

Subsurface autopilot[8]: A autonomous pilot program that can manage a variety of underwater vehicles[9]

Dynautics, UK development story since 2018:

- SPECTRE remote control autopilot system which is retrofittable to standard manned boats

-Developed the CAM concept, which allows SPECTRE to be used on underwater vehicles with 6 degrees of freedom

- Developed advanced Dynamic Positioning algorithms, which are now used on a wide variety of unmanned surface and subsurface vehicles for position stability down to 10 mm in three axes.

- Developed the data fusion algorithms used in our gyro-stabilised compass

- Collision Avoidance algorithms enable the vehicle to react to multiple fixed or moving obstacles.

1. Acquire a COTS programme and implement it on existing sub-surface platforms

 

 

 

 

Unmanned Ground Vehicle

Platoon support vehicle: Milrem Robotics THeMIS UGV, Estonia.

Remote-controlled driving, autonomous navigation ability along a given route.[10]

2015 prototype

2017 weapon system integration

2019-2020 in operation

2020 sold to 11 countries

2021 EU iMUGS-project builds a standard UGV solution with $32,6 M[11]

1. Acquire the Milrem Intelligent Function Integration Kit (MIFIK) and start implementing it on an existing platform

2. Acquire THeMIS UGVs for tactical development and seek possibilities to join the iMUGS

 

 

 

 

Unmanned Air Vehicle

Autopilot any aircraft:

China refurbished their old fighter jets with unmanned kits and made them multipurpose UAVs[12]

2013 first indications

2021 Won simulated dogfights[13]

2021 seen readiness for SEAD operation[14]

1. Cooperate with PLA to develop “Intelligence Victory” air combat AI

2. Contract a Remotely Piloted Aircraft System provider[15] and build the core system.

Unmanned Combat Air Vehicle

Swarming attack copter: The Golden Eagle 150B Swarm drone is an unmanned attack aircraft manufactured by China North Industries Group.[16]

2017 IDEX as 500 artillery fire control

2018 AirShow China 500 with air to ground missiles[17]

2020 150B with swarming features carrying bomblets[18]

1. Acquire MOTS from China and deploy

2. Build own capability using Drone racing, FPV, sports[19]

Suicide Combat Air Vehicle

Air-to-Ground munition: The AeroVironment Switchblade is a miniature loitering munition that locks onto and tracks a target once selected.[20]

2011 prototype

2012 deployed in ISAF

2015 unarmed variant

2020 anti-armour variant

Development est. $10M, an M300 costs est. $6000[21]

1. Acquire MOTS products and deploy with PG to replace Artillery, Helicopter, and CAS support.

 

 

 

 

Unmanned Air Vehicle Logistics

Autonomous delivery drone: UAV transport packages, medical supplies, food, or other goods.

2013 concept for rapid delivery[22]

2014 prototypes

2015 Ali Baba started delivery

2016 first fully autonomous delivery in the US

2021 Delivery networks based on UAVs[23]

 

 

1. Align with regulations, buy COTS drones, and start delivering small goods[24]

 

 

 

 

Unmanned Air Vehicle Medical

An autonomous VTOL UAV for evacuation:

Dragonfly manufactured DP-14 Hawk[25], a rotary-wing craft that uses relative positioning enabling self-launch and self-recover with 8-inch accuracy [26]

2016 US Army seeking potential evacuation drone

2017 they found DP-14 Hawk, an industrial UAV[27]

1. Acquire an industrial cargo UAV, modify it for evacuation and deploy it widely to recover lost people, replace emergency helicopters, and evacuating vehicles.



References:
BlackBerry 2022: Ultimate guide to autonomous systems
Robotic Systems and Autonomous Platforms, 2019
RT Staff 2018: Breaking down autonomous systems, Robotic Business Review
Tao Zhang et al, 2017: Current trends in the development of intelligent unmanned autonomous systems, Frontiers of Information Technology and Electronic Engineering 18, 68-85
Wikipedia 2022: Generative adversarial network

Links:

[1] https://www.thenationalnews.com/mena/2022/01/31/us-tests-drone-boats-that-can-sail-for-12-months-on-solar-power/

[2] https://www.saildrone.com/technology/vehicles

[3] https://www.thedefensepost.com/2021/12/15/us-navy-unmanned-saildrone/

[4] https://en.wikipedia.org/wiki/JARI_USV

[5] https://asia.nikkei.com/Business/Aerospace-Defense/China-s-latest-fighter-jets-drones-display-war-making-capability

[6] https://www.defenceview.in/inside-chinas-unmanned-surface-vessel-fleet/

[7] https://navalpost.com/china-launches-unmanned-warship-named-jari/

[8] https://sgp.fas.org/crs/weapons/R45757.pdf

[9] https://www.dynautics.com/products-unmanned-surface-vehicle/marine-autopilots/spectre-autopilot-autonomous-underwater-vehicles/

[10] https://milremrobotics.com/defence/

[11] https://www.armyrecognition.com/weapons_defence_industry_military_technology_uk/estonian-made_milrem_themis_ugv_unmanned_ground_vehicle_in_service_with_11_countries.html

[12] https://www.defensenews.com/global/asia-pacific/2021/10/20/china-shows-off-drones-recycled-from-soviet-era-fighter-jets/

[13] https://www.businessinsider.com/china-pits-fighter-pilots-against-ai-aircraft-in-simulated-dogfights-2021-6?r=US&IR=T

[14] https://www.thedrive.com/the-war-zone/41386/flanker-fighter-appears-among-unmanned-aircraft-at-chinas-secretive-drone-test-base

[15] https://www.businesswire.com/news/home/20210309005661/en/Reliable-Robotics-Remotely-Pilots-Aircraft-from-Private-Control-Center-a-First-for-Commercial-Aviation

[16] https://asia.nikkei.com/Business/Aerospace-Defense/China-s-latest-fighter-jets-drones-display-war-making-capability

[17] https://defencehub.live/threads/china%E2%80%99s-cr500-%E2%80%98golden-eagle%E2%80%99-unmanned-helicopter-finds-export-customer.3265/

[18] https://www.militarydrones.org.cn/golden-eagle-150b-uav-p00306p1.html

[19] https://www.fai.org/drone-sports?upcoming=1&f%5B0%5D=fai_event_year%3A2022&display=list

[20] https://www.avinc.com/tms/switchblade

[21] https://www.avinc.com/images/uploads/product_docs/201215_AV_Product_Catalog_R09.pdf

[22] https://en.wikipedia.org/wiki/Delivery_drone

[23] https://www.weforum.org/agenda/2021/11/drone-delivery-supply-chains/

[24] https://airsupply.com/

[25] https://www.aeroexpo.online/prod/dragonfly-pictures/product-181533-26559.html

[26] https://www.dragonflypictures.com/wp-content/uploads/2014/06/DPI-DP-14-Hawk-Spec-Sheet_v11.pdf

[27] https://taskandpurpose.com/gear-tech/army-drone-helicopter-medevac/