Avainsana-arkisto: sustainability

AI to the rescue: Will Artificial Intelligence lead the way towards the Sustainability Development Goals and a New Green Deal Era?

Mikkel Stein Knudsen & Jari Kaivo-oja:

Recently, researchers have started to investigate the potential positive/detrimental role Artificial Intelligence (AI) might play in achieving the global Sustainable Development Goals (SDGs). This is a natural squaring of two prominent twin transition megatrends likely to shape global developments over the coming decade. We provide a snapshot of the recent literature.

The advances of AI have been trumped as vast and considerate in recent years, and it is now hard to find images of the future, which does not position significant roles for AI. SITRA’s analysis of megatrends highlights that AI applications permeate society. AI technologies feature prominently in the Finnish  100 Opportunities for Finland and the World and the European 100 Radical Innovation Breakthroughs for the future. The new, first annual Strategic Foresight Report of the EU (European Commission, September 2020) underlines that “Digital technologies and related business models, including Artificial Intelligence (AI) and the platform economy, will impact the job market”.

Several studies and surveys suggest that artificial intelligence platforms and apps help humanity towards sustainable development goals (SDGs). However, this optimistic assumption about this future trend is by no means to say that people should not use their brains and intelligence. It is important to identify the issues relevant to decision-making in which AI can support more sustainable development processes and choices with high-level impacts.

AI needs to be complemented by other instruments

Let´s take an example of human intelligence and AI. The Tinbergen Rule, the rule that was named after one of the first two Nobel laureates in economics in 1969, is a basic principle of effective policy. Distinguishing between policy targets, on the one hand, and policy instruments, on the other hand, Jan Tinbergen (in 1952) argued that to successfully achieve 𝑛𝑛 independent policy targets, at least the same number of independent policy instruments are required. The Tinbergen Rule distinguishes three types of variables: (1) Data, (2) Target Variables, and (3) Instruments. This rule has become known as the Tinbergen Rule. The Tinbergen Rule is very relevant in planning and building transition scenarios to reach SDGs. This means that tailoring policy instruments in the backcasting scenarios of SDGs should consider the Tinbergen Rule. All potential AI applications, which do not take the Tinbergen Rule seriously, are probably creating more policy failures than policy successes.

We can conclude that human intelligence and AI are complementary system planning issues – just mentioning the Tinbergen Rule as an example.

AI and SDGs

The Sustainable Development Goals (SDGs) consist of 17 globally agreed goals with 169 explicit targets guiding the national and global efforts of sustainable development. It is important to understand the extent to which the different goals and targets are linked with each other (Mainali et al., 2018), and to keep in mind that there might be both synergies and trade-offs when combining the individual SDGs. An interdisciplinary study from Nature Sustainability (Nerini et al., 2019) e.g. shows that efforts to combat climate change can reinforce all 17 SDGs, but also undermine efforts to achieve 12.

Since the links between SDGs themselves are complex and involves synergies, it is no surprise that the role of Artificial Intelligence is also complex. The role of artificial intelligence in achieving the Sustainable Development Goals by Vinuesa et al. (2020), provides the hitherto strongest overview of the links between AI and SDGs. With the use of a consensus-based expert elicitation process, the researchers conclude that AI may enable the accomplishment of 134 targets, but also undermine the accomplishment of 59 targets. Figure 1 illustrates this across the 17 different SDGs.

Fig 1. Source: Vinuesa et al., 2020

The analysis also shows that more academic publications are demonstrating the positive enabling potential of Artificial Intelligence (in SoMe-terms, #aiforgood) compared to those demonstrating the risk of inhibiting the SDGs. This might be explained by reporting bias (researchers are more likely to research and publish about potential new opportunities than about potential pitfalls) or by the fact that the discovery of detrimental effects might require a long-term study, wherefore we may only get to read academic research on this year from now.

While the article in Nature Communications provides numerous examples of how AI might be detrimental, another new article, just published online September 3rd, explicitly sets out to expose the political economy of environmental costs of Artificial Intelligence. International Relations Professor Peter Dauvergne takes on Artificial Intelligence as much more critical terms, as can be seen in Figure 2 below which cites some of the main conclusions of the paper. AI reinforces the status quo, enriches corporate billionaires and transnational companies, accelerates the extraction of minerals and fossil fuels, turbocharges consumerism, and results in an ecological displacement.

Fig. 2. Based on and featuring quotes from Dauvergne, 2020.

While Dauvergne is perhaps the most focused on highlighting the dark sides of the AI-evolution, numerous other recent papers also present the duality of AI as an enabler/inhibitor of sustainable progress. Noteworthy examples include Di Vaio et al., 2020, Truby, 2020, Goralski & Tan, 2020, Sharma et al., 2020, and Mohamed et al, 2020.

The duality of AI-progress

The dual imaginary of progress and challenge is reminiscent of the EU data privacy regimes analysed by our colleague at the Finland Futures Research Centre, Matti Minkkinen, in his brilliant doctoral dissertation published earlier this year. Here he shows three key imaginaries in the European data privacy debate: (i.) ‘Continuous growth’, (ii.) ‘tragic loss’, and (iii.) ‘Europe as a hero’. This Janus-faced duality of positives and negatives coupled with a discourse of a potentially unique European third way is also easily detectable in the European AI-discourse. The opening paragraphs of the EU White Paper on Artificial intelligence follow this exact trilogy of imaginaries, cf. figure 3 below.

Fig. 3. White paper on Artificial Intelligence (EU, 2020), annotated with data imaginaries (Minkkinen, 2020)

EU also positions AI and digitalization as fundamental pillars of the so-called twin transitions, namely simultaneous the green and digital transformations of society and businesses. AI and other enabling technologies are essential for building a New Green Deal, e.g. the bold and ambitious idea of creating a new Digital Twin of the Earth, Destination Earth.

However, the EU-approach reflects the frame that while AI can deliver great potentials, left unchecked it is more likely to harm. We need new initiatives and new regulations to steer the development and the deployment of technology in the right direction. This same frame exists in the majority of literature on AI and SDGs.

Truby (2020) provides a prime example:

  • Promising and feasible possibilities of AI-driven developmental progress are being overshadowed by the current unfettered experimentation with untested AI technologies in markets and societies” (…)
  • “The case will be made that the design of AI software would benefit from pre-emptive regulation based on international principles, and secondly that such principles include a sustainable development purpose.”

We try to illustrate a way forward in Figure 4 below. At the same time, we must make use of the new technological opportunities helping the world on the path to sustainable development, and make sure that sustainable principles also permeate the development and deployment of Artificial Intelligence.

Fig. 4.: Adapted from Knudsen & Kaivo-oja, 2018.

A key element in this is to limit the important mismatch highlighted across numerous articles, not least in the contribution of Vinueasa et al. (2020): “research suggests that AI applications are currently biased towards SDG issues that are mainly relevant to those nations where most AI researchers live and work”. If AI technologies are designed and developed for richer and more technologically advanced nations, they “have the potential to exacerbate problems in less wealthy nations” (Ibid.).

In short, AI for the global Sustainable Development Goals requires establishing a global AI ecosystem.

How do we progress from here?

Based on the snapshot of recent literature, we list a few key priorities for the future development of sustainable AI.

  • Transformation to an environment-friendly ICT-sector (reduced energy use, use of renewable energy, sustainable mining of raw materials, reduced e-waste)
  • AI for the global, greater good; inclusive approaches beyond AI as solutions for the chosen few.
  • Tackling algorithmic bias and algorithmic coloniality (decentralized AI, algorithmic transparency, codified ethics, certifications (?), and regulatory oversight).

What we need is an approach, which stands on the shoulders of the remarkable work in recent years on ethical and Principled Artificial Intelligence (Fjeld et al., 2020; LaGrandeur, 2020), and combines this with a stronger planetary focus. This will be a key challenge during the years to come.

Mikkel Stein Knudsen
Project Researcher (M.Sc., Pol. Science), Finland Futures Research Centre, Turku School of Economics, University of Turku    

Jari Kaivo-oja
Research Director, Finland Futures Research Centre, Turku School of Economics, University of Turku.

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The project ‘Manufacturing 4.0’ has received funding from the Finnish Strategic Research Council [grant number 313395].

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Dauvergne, Peter (2020). Is artificial intelligence greening global supply chains? Exposing the political economy of environmental costs. Review of International Political Economy. Ahead-of-print. DOI.

Di Vaio, Assunta, Palladino, Rosa, Hassan, Rohail & Escobar, Octavio (2020). Artificial Intelligence and business models in the sustainable development goals perspective: A systematic literature review. Journal of Business Research. 121: 283-314. DOI.

European Commission (2020). White Paper: On Artificial Intelligence – A European approach to excellence and trust. Brussels, 19.2.2020. COM(2020) 65 final. Web: https://ec.europa.eu/info/sites/info/files/commission-white-paper-artificial-intelligence-feb2020_en.pdf

Fjeld, Jessica, Achten, Nele, Hilligoss, Hannah, Nagy, Adam & Srikumar, Madhulika (2020). Principled Artificial Intelligence: Mapping Consensus in Ethical and Rights-based Approaches to Principles for AI. Berkman Klein Center for Internet & Society: https://dash.harvard.edu/bitstream/handle/1/42160420/HLS%20White%20Paper%20Final_v3.pdf?sequence=1&isAllowed=y

Goralski, Margaret A. & Tan, Tay Keong (2020). Artificial intelligence and sustainable development. The International Journal of Management Education. 18: 100330. DOI.

Knudsen, Mikkel & Kaivo-oja, Jari (2018). Bridging Industry 4.0 and Circular Economy: A New Research Agenda for Finland? Tulevaisuuden tutkimuskeskuksen blogi. Web: https://ffrc.wordpress.com/2018/09/12/bridging-industry-4-0-and-circular-economy/

LaGrandeur, Kevin (2020). How safe is our reliance on AI, and should we regulate it? AI and Ethics. DOI.

Mainali, Brijesh, Luukkanen, Jyrki, Silveira, Semida & Kaivo-oja, Jari (2018). Evaluating Synergies and Trade-Offs among Sustainable Development Goals (SDGs): Explorative Analyses of Development Paths in South Asia and Sub-Saharan Africa. Sustainability. 10(3): 815. DOI.

Minkkinen, Matti (2020). A Breathless Race for Breathing Space: Critical-analytical futures studies and the contested co-evolution of privacy imaginaries and institutions. Turun Yliopiston Julkaisuja – Annales Universitas Turkuensis. Web: https://www.utupub.fi/bitstream/handle/10024/149425/AnnalesE55Minkkinen.pdf?sequence=1

Mohamed, Shakir, Png, Marie-Therese & Isaac, William (2020). Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology. DOI.

Nerini, Francesco Fuso, Sovacool, Benjamin, Hughes,  Nick, Cozzi, Laura, Cosgrave, Ellie, Howells, Mark, Tavoni, Massimo, Tomei, Julia, Zerriffi, Hisham & Milligan, Ben (2019). Connecting climate action with other Sustainable Development Goals. Nature Sustainability. 2: 674-680. DOI.

Sharma, Gagan Deep, Yadav, Anshita & Chopra, Ritika (2020). Artificial Intelligence and effective governance: A review, critique, and research agenda. Sustainable Futures. 2: 100004. DOI.

Tinbergen, Jan (1956). Economic Policy: Principles and Design. North-Holland. Retrieved from http://hdl.handle.net/1765/16740.

Truby, Jon (2020). Governing Artificial Intelligence to benefit the UN Sustainable Development Goals. Sustainable Development. 28(4): 946-959. DOI.

Vinuesa, Ricardo, Azizpour, Hossein, Leite, Iolanda, Balaam, Madeline, Dignum, Virginia, Domisch, Sami, Felländer, Anna, Langhans, Simone Daniela, Tegmark, Max & Nerini, Francesco Fuso (2020). The role of artificial intelligence in achieving the Sustainable Development Goals. Nature Communications. 11: 233. DOI.

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Article picture: pixabay.com

Energy, Sustainability and Foresight talk in Lima, Peru

Marianna Birmoser Ferreira-Aulu

On Monday 19 November, Project Researcher Marianna Birmoser Ferreira-Aulu gave a lecture on Futures Studies, Energy and Sustainability in UTEC (Universidad de Ingeniería y Tecnología) in Lima, Peru.

The event was organized by the prospectiva start-up consultancy company Project A+. It started with an introduction on Futures Studies and Foresight, by their Prospective and Strategic Management Chief Omar Del Carpio. Del Carpio is also the CEO of the Peruvian Foresight and Innovation Biofuture Lab. After his introduction, Mrs. Ferreira-Aulu gave her talk using her Master’s Thesis as an example of how Futures Studies can be an empowering field of work.

The lecture ended with a panel of discussion together with Ricardo Rodríguez -Director of the International Federation of Systems Research (IFSR), Julien Noel -Director of the faculty of engineering, and Omar del Carpio.


Is there a Future after the Belo Monte Dam?

Ferreira-Aulu’s work is entitled ”Is There A Future After The Belo Monte Dam? Building Futures Scenarios For The Volta Grande Do Xingu In Amazonia, Brazil.” (full PDF here)

In her thesis, published in 2017, she produced four scenarios of alternative futures for the Volta Grande do Xingu region, taking into account the socio-environmental impacts already caused by the Belo Monte Dam, currently being built in the Brazilian Amazonia, as well as future impacts, which can be different, depending how different actors behave on the days to come.

Despite Ferreira-Aulu’s rusty Spanish (or very fluent portuñol) the audience was attentive and interested. In addition to the students and teachers from UTEC university, the audience also counted with fellow futurists, consultancy companies, producers of EIAs in Peru, as well as representatives from the Peruvian Ministry of Energy and Mines.

The Q&A in the end was a lively and rich discussion between panellists and the audience. A video of the full lecture in available in the Facebook, and the language of the lecture was Spanish (or Portuñol).

Marianna Birmoser Ferreira-Aulu
MA Futures Studies, Project Researcher
Finland Futures Research Centre

Photos: Foresight and Innovation Biofuture Lab

Bridging Industry 4.0 and Circular Economy: A new research agenda for Finland?

Mikkel Stein Knudsen and Jari Kaivo-oja:

Emerging academic research concerns how the principles, practices, and enabling technologies of Industry 4.0 might unlock the potentials of Circular Economy (CE) and sustainable manufacturing (Jabbour et al., 2018; Stock et al., 2018). Digitalisation (Ellen Macarthur Foundation, 2016;  Antikainen et al., 2018) and the use of Big Data (Hazen et al., 2016; Nobre & Tavares, 2017; Jabbour et al., 2017) are seen as key enablers for increased sustainability and for the implementation of a circular economy. Technology is also a necessary enabler of a move towards Product-Service Systems (Tukker, 2015; Antikainen et al., 2018). As Moreno & Charnley (2016) notes the fundamental drivers behind Circular Economy and Industry 4.0 overlap. It is an obvious fact that the combination of Circular Economy and Industry 4.0 leads us towards the Green Economy vision.

However, research output integrating the two important fields is still very scarce and plenty of unexplored research areas remain. Tseng et al. (2018)  deliver a telling example of the hitherto missing research: While separate queries in Scopus using “Industry 4.0” and “Circular Economy” yields 4060 and 2452 results respectively, a combined search using both “Industry 4.0” and “Circular Economy” as keywords provide only three results (all published in 2017). Combined searches for “Circular Economy” and ´digit*´ (i.e. digital, digitalisation etc.) provide similarly limited results (Antikainen et al., 2018). Stock et al. (2018) make the point even broader, as they conclude, there are rarely any sustainability assessments for Industry 4.0 available”. All transition paths are not automatically leading us to sustainable development and greener infrastructures, which typically mean sustainable land use, widely adopted green consumption lifestyles and broad industrial use of nature saving technologies.

If we – ‘we’ as researchers, as Finland, as the international society – should harness the potential synergies of these two emerging business systems, and strive for a transition to a greener economy, there is therefore plenty of work ahead. It seems likely though that solving this integration puzzle, however, will also bring major (business) opportunities and a competitive advantage for the future.

Industry 4.0 and a new sustainability optimism?

Stock et al. (2018) note that most literature linking sustainability and Industry 4.0 do so with a basic tenor of optimism. Opportunities for increased sustainability by using novel technological opportunities in combinations with new business models take centre stage. Improved traceability of smart products through the entire supply chain and during the products’ use phase allow manufacturers continuously to optimize the performance of both product and production, which may deliver a more efficient use of resources. For industrial practitioners sustainability, environmental, and social opportunities is also a noted driver for implementation of Industry 4.0 (Müller et al., 2018). Highlighting what is at stake for a green economy transition, Erol (2016) even asks thought-provokingly if Industry 4.0 is the very last chance for a truly sustainable production?

Notably, the United Nations also talks of ‘Big Data for Sustainable Development’, and how “new sources of data, new technologies, and new analytical approaches, if applied responsively, can enable more agile, efficient and evidence-based decision-making and can better measure progress on the Sustainable Development Goals (SDGs) in a way that is both inclusive and fair”.

Source: United Nations

While this ‘optimistic’ strand of research is obviously both highly relevant and highly inspiring, increased technology uptake could also happen unsustainably. Rise of enabling technologies behind Industry 4.0 is mirrored by rising demands for scarce resources such as (certain) metals and also highly dependent on increasing consumption of energy.  We can probably sum things up this way, “Industry 4.0 and its related technologies may facilitate more sustainable production, but sustainability is not an endogenous feature of Industry 4.0.”

Industry 4.0 and its related technologies may facilitate more sustainable production, but sustainability is not an endogenous feature of Industry 4.0.

Dual challenges: A sustainable Industry 4.0 and Industry 4.0 for sustainability

In the context of sustainability, new technologies might indeed come Janus-faced. Additive manufacturing and 3D printing disrupts supply chains and reduces the need for large inventories, such as in the aero-industry (cf. Khajarvi et al., 2014). Instead, parts are manufactured (printed) at the time of actual demand, increasing efficiency and reducing waste. On the other hand, beyond specific supply chains, when every part and product can be produced anywhere and at any given time, it takes little fantasy to imagine marked reductions of product lifecycles and overall increases in consumption. Additive manufacturing is therefore not a guarantee for more sustainable production and consumption (cf. review by Kellens et al., 2017 & Holmström & Gutowski, 2017).  On average, production processes using additive manufacturing even results in a higher environmental impact than conventional production processes, although this could be compensated by functional improvements during the use stage of AM manufactured parts (Kellens et al., 2017). In her highly cited literature review, Aalto University’s Cindy Kohtala (2015) concluded “Distributed production holds promise of greater environmental sustainability, but it is not a given that it will be a new, clearly cleaner production paradigm.”

Figure 1. Environmental threats and benefits of distributed production (e.g. decentralized 3D-printing). Source: Kohtala, 2015.

Interconnectivity and continuous massive amounts of data also come with an environmental price: In Denmark for example, the government expects that international data centres will take up 20% of the current national electricity consumption by 2030. The global electricity consumption for mining cryptocurrency using Blockchain-technology already today exceeds the current national electricity consumption of Finland significantly, according to consumption estimates in a recent issue of The Economist (2018).

The challenge then is (simultaneously!) to build a sustainable Industry 4.0 and to use Industry 4.0 to build sustainability. In other words, society must: (1) Ensure to the widest extent possible sustainability and circular economy as a feature in the ecosystem of Industry 4.0-enabling technologies, (2) Explore and exploit the enabling potential of Industry 4.0 for building more sustainable business models and production systems. These challenges are illustrated in figure 2.

Figure 2. Circular Economy for Industry 4.0 and Industry 4.0 for Circular Economy.

A new research agenda for Finland?

Finland is well poised to be an international leader in the bridging of Industry 4.0 and Circular Economy. Finland is already among the global drivers of Circular Economy. It is a stated objective of the current government to make Finland a “forerunner in the circular economy by 2025”. In addition, Finland is one of the most digitalised countries of the world, and a world-leader in many areas related to Industry 4.0. Our current project – Manufacturing 4.0 – aims at translating this into a success story for the general manufacturing industry of Finland.

It would seem natural then that Finland should also take the lead in bridging Industry 4.0 with Circular Economy. This could secure long-term competitive advantages for Finnish industry and simultaneously improve the local and global environment.

This new research agenda of bridging Industry 4.0 with Circular Economy would not start from scratch, but as the recent literature shows, there are still many research areas to explore. For us, a new research agenda could for example further address some of these key questions:

The countries, which are able to integrate Industry 4.0 approach to the principles of the Circular Economy, are the probably forerunners of Industry 4.0 revolution. However, as we can see above, the list of challenges in Industry 4.0 transformation is not short.  We know also that many economic activities in many countries are stuck in Industry 1.0-3.0 phases. This means that the Industry 4.0 approach with the Circular Economy approach does not solve all the sustainability problems of globalized world economy. However, remaining to Industry 1.0-3.0 models can also be a highly risky “project” for the long-run sustainability of world economy. Greener economic structures can be developed with Industry 4.0 technologies. We know that Industry 1.0-3.0 stages of development have not yet led us to needed sustainability levels, because climate change and other environmental problems are still far from solved.

In Fig 3 we present a scenario roadmap of Industry 4.0 and circular economy development. This scenario roadmap shows that in the process of Industry 4.0 development, it is not enough to change Industry 4.0 structures to meet the deep requirements of circular economy.

Figure 3. Scenario roadmap of Industry 4.0 and the Circular Economy.

Previous old phases of Industry 1.0, Industry 2.0 and Industry 3.0 require attention concerning the adoption of environmental principles of the Circular Economy. We underline that preconditions of Industry 1.0-3.0 are really pre-conditions for Industry 4.0, but also that the simultaneous transformation towards Industry 4.0 and Circular Economy requires both attention and multiple testing phases. From this perspective we can say: “Let´s try it – let´s pilot it”.


Mikkel Stein Knudsen
Project Researcher, Finland Futures Research Centre, Turku School of Economics, University of Turku

Jari Kaivo-oja
Research Director, Adjunct Professor, Dr, Finland Futures Research Centre, Turku School of Economics, University of Turku

Note: Authors thank for Try Out! and Manufacturing 4.0 projects for financial support.


Picture: pixabay.com


Cobalt: What the price of a mineral can make us inquire about the future?

Mikkel Stein Knudsen & Jari Kaivo-oja:

How can strategic foresight help prepare Finland for a healthy economic future? One element is to detect market movements, which, now and down the line, might affect Finland’s economy and manufacturing. The cobalt market is one such market.

The price of cobalt is surging. The price of the mineral has more than quadrupled over the past 26 months from a historic low of 21,750 $/ton in February 2016 to an all time high of 95,250 $/ton in March 2018. On Friday April 13 2018, trading closed at 92,000 $/ton.

Fig. 1. Five years trading prices of Cobalt.  

This price development is remarkable for a number of reasons, and, as this blog post aims to show, it provides us with important questions and links to the global sustainable energy transition, to a healthy and competitive Finnish economy, and to possible geopolitical challenges of the future. We should pay more strategic attention to the monitoring of the global economy from the perspective of the Finnish manufacturing base. In the future we need strategic value mapping systems, of manufacturing, which include (1) independent models of value, (2) specific strategy and technology models and (3) growth models implicit in the life-cycle of the technology underlying the business model of the family of business models.

The blog post thus briefly covers five main questions:

  1. Why is the price of cobalt suddenly surging like it is?
  2. Why is the price development of cobalt important for Finland?
  3. Why might the cobalt market impose challenges for sustainable transition?
  4. Why does the cobalt market have geopolitical implications?
  5. How can we assess future implications of this issue?

The aim of the post here is not so much to provide answers, but rather to develop insights and key questions for additional research, which we believe would be of interest for the Government, Finnish policymakers, Finnish businesses, industrial stakeholders and academics across a range of fields. We should present a strategic important question: What is the role of Finnish manufacturing in global value creation and production networks?

The price of cobalt as a proxy for demand for electric vehicles?

The main driver of the dramatic price surge is linked by market participants to rising demand for electric vehicles (EVs) (Financial Times, 2018; The Economist, 2018). In the EV-sector lithium-ion (Li-ion) batteries are the preferred battery technology due to it’s energy density (Zubi et al., 2018), with cobalt used for lithium metal oxides. 75% of the global cobalt consumption is going into the battery sector (Fröhlich et al, 2017). As demand for EV’s increase, so does the demand for batteries, and so does the demand for cobalt.

The price of cobalt might therefore be a telling proxy for the general optimism surrounding the business ecosystem of electric vehicles – and the surging price of cobalt can be seen as an indicator that the car and battery industries, at least, are now betting big on EV markets. Of course, this price analysis is not only price indicator trend analysis, we should perform in the context of global economy. However, this is an interesting strategic case example with broader importance. We need to pay more attention to the price monitoring system of strategic resources relevant for the Finnish manufacturing base and economy.

Possible research ideas: Market development and global uptake of electric vehicles; linkages between EV sales and global cobalt consumption, the price monitoring system of strategic resources relevant for the Finnish manufacturing base and economy. 

Finland and the cobalt industry

The largest cobalt refinery in the world is located in Kokkola, and Finland is the second largest producer of the refined cobalt in the world after China. Current (2017) Finnish production is at 12,200 tons of Cobalt per year (GTK, 2018). Finland is not a marginal player in this field of global manufacturing…

While a large majority of the cobalt used for refining is imported (thereby possibly limiting profits added by the price surge), the value of the refined cobalt outputs have increased remarkably. If each ton of refined cobalt is worth $70,000 more than two years ago, an annual production of 12,200 tonnes of refined cobalt is worth $850m more.

The surging price of cobalt alone therefore by itself lifts Finnish exports by as much as €0,5bn in 2018 compared to 2016.

There are current plans of mining for cobalt at Terraframe (formerly Talvivaara) and near Kuusamo, although the developments are not quite without issues (Terraframe, 2017; Yle, 2018; Lapin Kansa, 2018).

Through mining and refining of cobalt as well as through a number of other aspects, this growing battery manufacturing value chain might be a key value-producing network for the Finnish economy of the near future. We need proactive industrial and manufacturing policy platform based on private-public governance. One important idea behind this blog post is that we need a more proactive industrial policy in Finland.

It has indeed already been noted that Finland is well positioned for this growth market (Aamulehti, 2017; Business Finland, 2017), and this month  (April 2018), the Ministry of Economic Affairs launched a new program for Batteries for Finland 2018-2020 in order to strengthen this agenda further (Työ- ja elinkeinoministeriö, 2018). In addition to attracting new international mining investments, the plans aim at generating a higher value part of the battery manufacturing chain.

One important strategic aspect of economic trend research is that we can understand that relative advantages are variable dynamic factors. Therefore, they should be constantly monitored on the basis of global economic changes. Of course, prices changes are such factors.

Possible research ideas: Scenarios and a strategy architecture for Finnish cobalt mining and refining, Orchestration of the EV battery business ecosystem. 

Can lack of cobalt hinder a sustainable transition?

A sustainable global transition requires new technologies for energy production, transportation, etc. However, these new technologies are dependent on various metals, including cobalt. In 2016 Finnish researchers from VTT and the Geological Survey of Finland assessed this ‘Role of critical metals in the future markets of clean energy technologies’ in a peer-reviewed article (Grandell et al., 2016). Here availability of other metals (e.g. silver) is deemed even more critical, but for cobalt the researchers find that with assumptions of a global clean energy transformation, cumulative demand for cobalt for the period until 2050 can exceed known global resources by almost 200 pct.

In other words, positive scenarios for fast climate change action can be challenged by the lack of minerals. If the world transitions with the use of current technologies, there might simply not be enough cobalt available for the job.

It is not without reason that a recent published study concluded that “Cobalt, however, is a reason for major concerns in the Li-ion battery sector” (Zubi et al., 2018).

Possible research ideas: Critical metals as possible limiting factors for cleantech-technologies; Designing optimal policies for reducing dependence on critical metal; Substitutionality of critical metals in various technological fields.

Why does the cobalt market have geopolitical implications?

The main supplier of cobalt in the world is the Democratic Republic of Congo (DRC), which supplies more than 50% of the current global production of cobalt (Fröhlich et al., 2017). Having one dominant global supplier entails supply risks, increased by political and economic instability. In 1978, civil unrest in the DRC quickly increased the price of cobalt by 6.5 times (Bailey et al., 2017), the so called “Cobalt Crisis” (Shedd et al., 2017). Depending on the stability and development of the DRC, there might be concerns regarding continuous supply.

The second supply-related concern relates to the dominant position of China. A 2015-paper in Energy Policy stated that “Whereas experts in the minerals industry are mostly aware of China’s strong position, many stakeholders in and advocates for renewable technologies are not” (Stegen, 2015). This strong position certainly holds true for cobalt, leading to concerns of what might happen if China corners the cobalt market (The Economist, 2018). The Chinese company China Moly  was also in talks to take over Freeport Cobalt’s refinery in Kokkola, but the deal fell through in the summer of 2017 (Reuters, 2018).

If there is a global scarcity of certain minerals, and if one nation holds the key to these minerals, it is easy to imagine the availability might have important geopolitical implications (cf. Øverland et al., 2017).

Possible research ideas: Security and geopolitical implications of mineral resources for clean energy technologies; black swans and resilience research.

What can we say about the future?

Like with any other raw material, the price and the criticality of cobalt hinges on supply and demand. In the terms of minerals these fundamental variables can meaningfully be subdivided into specific variables (adapted from Martin et al., 2017):

Fig. 2. Determinants of price and criticality of minerals (inspiration from Martin et al., 2017)

The supply of cobalt available for the market will be driven both by the amount of cobalt resources and reserves naturally available, by the amount of cobalt that is recycled, and by the amount of cobalt actually produced. The production supply will be a function of price and profitability, but other issues like social and environmental concerns might also affect production constraints, e.g. in Finnish mining projects.

Similarly, demand for cobalt will be a function of the demand for technologies using cobalt, but also shaped by the technical and economic feasibility of using alternative raw materials or using alternative technological solutions (ie. substitutionality).

A thorough foresight or technological forecast study should therefore consider each of these variables individually, in the case of Finland or even globally. Given the potentially major role of cobalt for sustainable transition, for global geopolitical concerns or ‘just’ for the economy of Finland, this would however be a very interesting endeavour to pursue.

Possible research ideas: Scenarios for global cobalt demand; Scenarios for Finland’s mining industry.

References and additional information

Mikkel Stein Knudsen
Project Researcher, Finland Futures Research Centre, Turku School of Economics, University of Turku

Jari Kaivo-oja
Research Director, Adjunct Professor, Dr, Finland Futures Research Centre, Turku School of Economics, University of Turku

This research work has been supported by the Finnish Strategic Research Council [grant number 313395]. The blog text refers to the preliminary foresight and background analyses of the Manufacturing 4.0 project.

Photo: Tesla, pixabay.com