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Structured reporting in radiology continues to hold substantial potential to improve the quality of service provided to patients and referring physicians. Despite many physicians' preference for structured reports and various efforts by radiological societies and some vendors, structured reporting has still not been widely adopted in clinical routine. While in many countries national radiological societies have launched initiatives to further promote structured reporting, cross-institutional applications of report templates and incentives for usage of structured reporting are lacking. Various legislative measures have been taken in the USA and the European Union to promote interoperable data formats such as Fast Healthcare Interoperability Resources (FHIR) in the context of the EU Health Data Space (EHDS) which will certainly be relevant for the future of structured reporting. Lastly, recent advances in artificial intelligence and large language models may provide innovative and efficient approaches to integrate structured reporting more seamlessly into the radiologists' workflow. The ESR will remain committed to advancing structured reporting as a key component towards more value-based radiology. Practical solutions for structured reporting need to be provided by vendors. Policy makers should incentivize the usage of structured radiological reporting, especially in cross-institutional setting. Critical relevance statement Over the past years, the benefits of structured reporting in radiology have been widely discussed and agreed upon; however, implementation in clinical routine is lacking due—policy makers should incentivize the usage of structured radiological reporting, especially in cross-institutional setting. Key points 1. Various national societies have established initiatives for structured reporting in radiology. 2. Almost no monetary or structural incentives exist that favor structured reporting. 3. A consensus on technical standards for structured reporting is still missing. 4. The application of large language models may help structuring radiological reports. 5. Policy makers should incentivize the usage of structured radiological reporting. [ABSTRACT FROM AUTHOR]

The emergence of increasingly capable artificial intelligence (AI) systems has raised concerns about the potential extreme risks associated with them. The issue has drawn substantial attention in academic literature and compelled legislators of regulatory frameworks like the European Union AI Act (AIA) to readapt them to the new paradigm. This paper examines whether the European Parliament's draft of the AIA constitutes an appropriate approach to address the risks derived from frontier models. In particular, we discuss whether the AIA reflects the policy needs diagnosed by recent literature and determine if the requirements falling on providers of foundation models are appropriate, sufficient, and durable. We find that the provisions are generally adequate, but insufficiently defined in some areas and lacking in others. Finally, the AIA is characterized as an evolving framework whose durability will depend on the institutions' ability to adapt to future progress. [ABSTRACT FROM AUTHOR]

The next-generation "Industrial Internet of Things" (IIoT) will support "Machine-to-Machine" (M2M) communications for smart Cyber-Physical-Systems and Industry 4.0, and require guaranteed cyber-security. This paper explores hardware-enforced cyber-security for critical infrastructures. It examines a quantum-safe "Software-Defined-Deterministic IIoT" (SDD-IIoT), with a new forwarding-plane (sub-layer-3a) for deterministic M2M traffic flows. A "Software-Defined Networking" (SDN) control plane controls many "Software-Defined-Deterministic Wide-Area Networks" (SDD-WANs), realized with FPGAs. The SDN control plane provides an "Admission-Control/Access-Control" system for network-bandwidth, using collaborating Artificial Intelligence (AI)-based "Zero Trust Architectures" (ZTAs). Hardware-enforced access-control eliminates all congestion, BufferBloat, and DoS/DDoS attacks, significantly reduces buffer-sizes, and supports ultra-reliable-low-latency communications in the forwarding-plane. The forwarding-plane can: (i) Encrypt/Authenticate M2M flows using quantum-safe ciphers, to withstand attacks by Quantum Computers; (ii) Implement "guaranteed intrusion detection systems" in FPGAs, to detect cyber-attacks embedded within billions of IIoT packets; (iii) Provide guaranteed immunity to external cyber-attacks, and exceptionally strong immunity to internal cyber-attacks; (iv) Save USD 100s of billions annually by exploiting FPGAs; and (v) Enable hybrid Classical-Quantum networks, by integrating a "quantum key distribution" (QKD) network with a classical forwarding plane with exceptionally strong cyber-security, determined by the computational hardness of cracking Symmetric Key Cryptography. Extensive experimental results for an SDD-WAN over the European Union are reported. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) has emerged as one of the central topics of 2023 with extensive media coverage of the most relevant technologies and issues associated with this subject. In a highly competitive digital media landscape, search engine optimization (SEO) has become cybermedia’s primary strategy to increase visibility and attract more readers. The objective of this paper is to analyze the visibility of content published by the media relating to artificial intelligence, focusing on a selection of related keywords. The research also aims to investigate how this visibility has impacted both the technologies themselves and the analyzed media outlets. A total of 69 media outlets from 12 European Union countries, the United States, and the United Kingdom were examined. The results reveal a pronounced dominance of U.S. media, closely followed by Spanish media. There is an uneven distribution of media outlets across most of the countries analyzed, with two or three most of the of visibility. The search queries that contribute the most visibility to the analyzed media align with an informational intent, are of the long-tail type, and are associated with OpenAI technologies, particularly ChatGPT. Moreover, these queries are primarily found in news sections dedicated to science and technology. The findings underscore both the increasing interest in the subject and the effective SEO practices of certain media outlets. [ABSTRACT FROM AUTHOR]

• Identify gaps in state-of-the-art research to support healthcare AI trustworthiness. • Explore the explainable AI and fusion in healthcare. • Explore legitimacy, morality, and robustness standards for AI policymakers. • Assessment quality, bias risk, and data fusion for medical AI trustworthiness. • Examine eight research gaps to guide future study and assist researchers. In the last few years, the trend in health care of embracing artificial intelligence (AI) has dramatically changed the medical landscape. Medical centres have adopted AI applications to increase the accuracy of disease diagnosis and mitigate health risks. AI applications have changed rules and policies related to healthcare practice and work ethics. However, building trustworthy and explainable AI (XAI) in healthcare systems is still in its early stages. Specifically, the European Union has stated that AI must be human-centred and trustworthy, whereas in the healthcare sector, low methodological quality and high bias risk have become major concerns. This study endeavours to offer a systematic review of the trustworthiness and explainability of AI applications in healthcare, incorporating the assessment of quality, bias risk, and data fusion to supplement previous studies and provide more accurate and definitive findings. Likewise, 64 recent contributions on the trustworthiness of AI in healthcare from multiple databases (i.e., ScienceDirect, Scopus, Web of Science, and IEEE Xplore) were identified using a rigorous literature search method and selection criteria. The considered papers were categorised into a coherent and systematic classification including seven categories: explainable robotics, prediction, decision support, blockchain, transparency, digital health, and review. In this paper, we have presented a systematic and comprehensive analysis of earlier studies and opened the door to potential future studies by discussing in depth the challenges, motivations, and recommendations. In this study a systematic science mapping analysis in order to reorganise and summarise the results of earlier studies to address the issues of trustworthiness and objectivity was also performed. Moreover, this work has provided decisive evidence for the trustworthiness of AI in health care by presenting eight current state-of-the-art critical analyses regarding those more relevant research gaps. In addition, to the best of our knowledge, this study is the first to investigate the feasibility of utilising trustworthy and XAI applications in healthcare, by incorporating data fusion techniques and connecting various important pieces of information from available healthcare datasets and AI algorithms. The analysis of the revised contributions revealed crucial implications for academics and practitioners, and then potential methodological aspects to enhance the trustworthiness of AI applications in the medical sector were reviewed. Successively, the theoretical concept and current use of 17 XAI methods in health care were addressed. Finally, several objectives and guidelines were provided to policymakers to establish electronic health-care systems focused on achieving relevant features such as legitimacy, morality, and robustness. Several types of information fusion in healthcare were focused on in this study, including data, feature, image, decision, multimodal, hybrid, and temporal. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) is a contemporary phenomenon of vast scale, surpassing the uses and opportunities brought by the advent of the Internet, but which generates fundamental rights risks and legal challenges at an exponentially higher level. In the present study, we aim to explore the concept of artificial intelligence, the types of AI technologies, and the requirements for market introduction, with direct reference to the provisions of the new European Union AI Act. For a better understanding of the concept of Artificial Intelligence, we will classify AI systems considering the following criteria: the degree of risk, the algorithms used, the capabilities and functions, and the level of autonomy of the system. The paper highlights key aspects of AI Act regulation, focusing on high-risk and prohibited AI systems. Finally, the penalties for noncompliance with AI Act provisions are briefly outlined. [ABSTRACT FROM AUTHOR]

Simple Summary: Various measurements can be obtained on an animal. These measurements can provide valuable information on animal welfare. Sensors and smart algorithms can automatically perform those measurements and aid in achieving more automated meat inspection and welfare assessment at the slaughterhouse. This study provides an overview of animal welfare measurements at the slaughterhouse and gives examples of the available technologies to record and use these measurements. There are several technologies available, either applied in research, on farm or at the slaughterhouse. However, according to current European Union (EU) law the meat inspection must be performed by a veterinarian. Therefore, sensor technology cannot yet replace a human during the meat inspection, but it has potential to play an important role in the future. Currently it can already add value to the inspections and provide better insight into animal welfare issues than by human inspections alone. Animal-based measures (ABMs) are the preferred way to assess animal welfare. However, manual scoring of ABMs is very time-consuming during the meat inspection. Automatic scoring by using sensor technology and artificial intelligence (AI) may bring a solution. Based on review papers an overview was made of ABMs recorded at the slaughterhouse for poultry, pigs and cattle and applications of sensor technology to measure the identified ABMs. Also, relevant legislation and work instructions of the Dutch Regulatory Authority (RA) were scanned on applied ABMs. Applications of sensor technology in a research setting, on farm or at the slaughterhouse were reported for 10 of the 37 ABMs identified for poultry, 4 of 32 for cattle and 13 of 41 for pigs. Several applications are related to aspects of meat inspection. However, by European law meat inspection must be performed by an official veterinarian, although there are exceptions for the post mortem inspection of poultry. The examples in this study show that there are opportunities for using sensor technology by the RA to support the inspection and to give more insight into animal welfare risks. The lack of external validation for multiple commercially available systems is a point of attention. [ABSTRACT FROM AUTHOR]

The aim of this paper is to discuss the management aspect of artificial intelligence development policy by the national regulators of the 27 European Union (EU) member states. The solutions formulated by three of them—Germany, France (as a pioneers), and Poland—are analyzed in depth. The obtained results allow us to conclude that out of 27 EU countries, only one has not yet prepared its strategic project on artificial intelligence (AI) development, while among the existing policies one can find significant differences in the approach to the matter of strategic management. The research methods used are content analysis and comparative analysis of selected source documents. In the course of the deliberations presented, key legal acts concerning the areas of AI and modern technologies are cited. The presented work formulates a starting point for further research and directions of changes in the management of AI development policy. The attention of subsequent researchers should focus on the possibility of a detailed analysis of other documents published by EU member states, a comparison of policies of other countries across the world, and even an attempt to examine the global dimension of AI strategies. The article addresses the problem of creating law only following, rather than preceding, the emergence of technological changes, the lack of systemic regulation of AI tools and mechanisms, as well as the absence of integrated forms of international cooperation with a strategic and long-term dimension. [ABSTRACT FROM AUTHOR]

Background Although current efforts are made to diminish the incidence and burden of disease, cancer is still widely identified late at stage. This study aims to conduct a systematic review mapping the existent and emerging clinical research on artificial intelligence (AI) in the treatment of cancer and to underpin its integration challenges and opportunities in the European Union (EU) health sector. Methods A systematic literature review (SLR) evaluating global clinical trials (CTs; published between 2010 and 2020 or forthcoming) was concluded. Additionally, a horizon scanning (HS) exercise focusing on emerging trends (published between 2017 and 2020) was conducted. Results Forty-four CTs were identified and analyzed. Selected CTs were divided into three research areas: (i) potential of AI combined with imaging techniques, (ii) AI's applicability in robotic surgery interventions and (iii) AI's potential in clinical decision making. Twenty-one studies presented an interventional nature, nine papers were observational and 14 articles did not explicitly mention the type of study performed. The papers presented an increased heterogeneity in sample size, type of tumour, type of study and reporting of results. In addition, a shift in research is observed and only a small fraction of studies were completed in the EU. These findings could be further linked to the current socio-economic, political, scientific, technological and environmental state of the EU in regard to AI innovation. Conclusion To overcome the challenges threatening the EU's integration of such technology in the healthcare field, new strategies taking into account the EU's socio-economic and political environment are deemed necessary. [ABSTRACT FROM AUTHOR]

As Artificial Intelligence (AI) becomes more and more pervasive in our everyday life, new questions arise about its ethical and social impacts. Such issues concern all stakeholders involved in or committed to the design, implementation, deployment, and use of the technology. The present document addresses these preoccupations by introducing and discussing a set of practical obligations and recommendations for the development of applications and systems based on AI techniques. With this work we hope to contribute to spreading awareness on the many social challenges posed by AI and encouraging the establishment of good practices throughout the relevant social areas. As points of novelty, the paper elaborates on an integrated view that combines both human rights and ethical concepts to reap the benefits of the two approaches. Moreover, it proposes innovative recommendations, such as those on redress and governance, which add further insight to the debate. Finally, it incorporates a specific focus on the Italian Constitution, thus offering an example of how core legislations of Member States might contribute to further specify and enrich the EU normative framework on AI. [ABSTRACT FROM AUTHOR]

The question of the moral status of AI and the extent to which that status ought to be recognised by societal institutions is one that has not yet received a satisfactory answer from lawyers. This paper seeks to provide a solution to the problem by defending a moral foundation for the recognition of legal personhood for AI, requiring the status to be granted should a threshold criterion be reached. The threshold proposed will be bare, noumenal agency in the Kantian sense. Agency has been identified by Alan Gewirth as the source of the rights claims of our own species and, at risk of contradiction, is a foundation that must be expanded to all agents or else we contradict the foundation of our own rights. This is something that ought to be recognised through the granting of legal personhood to all noumenal agents by any system that requires such personhood for the enforcement of rights, or else the rule restricting legal personhood cannot be seen as a valid legal norm. Having laid out the case, the paper will move on to defend this natural law conception against the narrower definition of legal personhood proposed by Bryson et al. with regards to AI. It will argue that bare agency is a sufficient, though not necessary, criterion for the ascription of legal personhood in any system that sees the status as necessary for the ascription of legal rights. The paper will conclude by analysing the proposals currently making their way through the legislatures of the UK and European Union. They will be assessed for their compatibility with the claim that a functioning legal system necessarily must recognise the legal personhood of all noumenal agents regardless of their origins, and whether they are future-proofed for the possibility that AI may meet this threshold. [ABSTRACT FROM AUTHOR]

The presented paper focuses on the analysis of strategic documents at the level of the European Union (EU) concerning the regulation of artificial intelligence as one of the so-called disruptive technologies. In the first part of the article, we outline the basic terminology. Subsequently, we focus on the summarizing and systemizing of the key documents adopted at the EU level in terms of artificial intelligence regulation. The focus of the paper is devoted to issues of personal data protection and cyber security included in these strategic documents. The final part contains recommendations for future research and evaluation of its key features. [ABSTRACT FROM AUTHOR]

European law now requires AI to be explainable in the context of adverse decisions affecting the European Union (EU) citizens. At the same time, we expect increasing instances of AI failure as it operates on imperfect data. This paper puts forward a neurally inspired theoretical framework called "decision stacks" that can provide a way forward in research to develop Explainable Artificial Intelligence (X-AI). By leveraging findings from the finest memory systems in biological brains, the decision stack framework operationalizes the definition of explainability. It then proposes a test that can potentially reveal how a given AI decision was made. [ABSTRACT FROM AUTHOR]

This paper is devoted to issues which have not been sufficiently explored in European literature, and which have had fragmented consideration in comparative literature. These issues raise the question of whether the EU legislator should develop a framework of criminal law rules which would regulate the use of Artificial Intelligence (hereinafter: AI) in the near future, and what such rules should specifically address. The authors recognise two issues of particular importance for the future regulation of AI development within the EU, and offer their perspective on the areas which should be subjected to regulation in this regard. In order to provide a systematic overview of this topic, the paper starts with a description of the recent regulatory action of the EU in the field of AI, with special reflection on the Ethics Guidelines for Trustworthy AI. The authors then describe what are, in their opinion, the most important intersections of AI and criminal law in the broader sense, and in conclusion present their views of which areas should be specifically regulated by EU legislature in this context. [ABSTRACT FROM AUTHOR]

The paper examines the policies of European countries regarding the use and development of applications based on Artificial Intelligence. Along with the examination of the strategic documents of the European Commission, some of them are studied at national level. Also, the situation in this field in the Republic of Moldova is analyzed. [ABSTRACT FROM AUTHOR]

Artificial intelligence holds great promise in terms of beneficial, accurate and effective preventive and curative interventions. At the same time, there is also awareness of potential risks and harm that may be caused by unregulated developments of artificial intelligence. Guiding principles are being developed around the world to foster trustworthy development and application of artificial intelligence systems. These guidelines can support developers and governing authorities when making decisions about the use of artificial intelligence. The High- Level Expert Group on Artificial Intelligence set up by the European Commission launched the report Ethical guidelines for trustworthy artificial intelligence in 2019. The report aims to contribute to reflections and the discussion on the ethics of artificial intelligence technologies also beyond the countries of the European Union (EU). In this paper, we use the global health sector as a case and argue that the EU's guidance leaves too much room for local, contextualized discretion for it to foster trustworthy artificial intelligence globally. We point to the urgency of shared globalized efforts to safeguard against the potential harms of artificial intelligence technologies in health care. [ABSTRACT FROM AUTHOR]

Industrial robots are a strategic future technology and an important part of the development of artificial intelligence, and they are a necessary means for the intelligent transformation of manufacturing industry. Based on global industrial robot trade data from 1998 to 2017, this paper applies the dynamic complex network analysis method to reveal the spatial and temporal variation characteristics and trade status evolution of the global industrial robot trade network. The results show that the global industrial robot network density has steadily increased, and the industrial robot trade has been characterized by ‘diversification’. The number of major industrial robot exporters in the world is increasing, and the import market is increasingly diversified. The export market structure is relatively tight, the centrality of the global industrial robot trade network shows a downward trend, and the dissimilarity of the ‘core-edge’ clusters decreases year by year. The trade status of ‘catch-up’ countries represented by China has rapidly increased. However, Japan, Germany, and Italy are still in the central position of the industrial robot trade. Moreover, trade of the ‘catch-up’ countries’ is dominated by imports, and exports of industrial robot products are insufficient. Finally, policy suggestions are provided according to the results. [ABSTRACT FROM AUTHOR]

Recent years have seen a surge of studies in machine learning in health and biomedicine, driven by digitalization of healthcare environments and increasingly accessible computer systems for conducting analyses. Many of us believe that these developments will lead to significant improvements in patient care. Like many academic disciplines, however, progress is hampered by lack of code and data sharing. In bringing together this PLOS ONE collection on machine learning in health and biomedicine, we sought to focus on the importance of reproducibility, making it a requirement, as far as possible, for authors to share data and code alongside their papers. [ABSTRACT FROM AUTHOR]

People are increasingly leaving digital traces of their daily activities through interacting with their digital environment. Among these traces, financial transactions are of paramount interest since they provide a panoramic view of human life through the lens of purchases, from food and clothes to sport and travel. Although many analyses have been done to study the individual preferences based on credit card transaction, characterizing human behavior at larger scales remains largely unexplored. This is mainly due to the lack of models that can relate individual transactions to macro-socioeconomic indicators. Building these models, not only can we obtain a nearly real-time information about socioeconomic characteristics of regions, usually available yearly or quarterly through official statistics, but also it can reveal hidden social and economic structures that cannot be captured by official indicators. In this paper, we aim to elucidate how macro-socioeconomic patterns could be understood based on individual financial decisions. To this end, we reveal the underlying interconnection of the network of spending leveraging anonymized individual credit/debit card transactions data, craft micro-socioeconomic indices that consists of various social and economic aspects of human life, and propose a machine learning framework to predict macro-socioeconomic indicators. [ABSTRACT FROM AUTHOR]

The publication presents a picture of modern steelworks that is evolving from steelworks 3.0 to steelworks 4.0. The paper was created on the basis of secondary sources of information (desk research). The entire publication concerns the emerging opportunities for the development of the steel producers to Industry 4.0 and the changes already implemented in the steel plants. The collected information shows the support environment for changes in the steel sector (EU programs), the levels of evolution of steel mills, along with the areas of change in the steel industry and implemented investment projects. The work consists of a theoretical part based on a literature review and a practical part based on case studies. The work ends with a discussion in which the staged and segmented nature of the changes introduced in the analyzed sector is emphasized. Based on the three case studies described in the paper, a comparative analysis was conducted between them. When we tried to compare methods used in the three analyzed steel producers (capital groups): ArcelorMittal, Thyssenkrupp, and Tata Steel Group, it can be seen that in all organizations, the main problem connected with steelworks 4.0 transition is the digitalization of all processes within an organization and in the entire supply chain. This is realized using various tools and methods but they are concentrated on using technologies and methods such as artificial intelligence, drones, virtual reality, full automatization, and industrial robots. The effects are connected to better relations with customers, which leads to an increase in customer satisfaction and the organizations' profit. The steel industry will undergo further strong changes, bringing it closer to Industry 4.0 because it occupies an important place in the economies of many countries due to the strong dependence of steel producers on the markets of the recipients (steel consumers). Steel is the basic material needed to make many products, and its properties have been valued for centuries. In addition, steel mills with positive economic, social, and environmental aspects are part of the concept of sustainability for industries and economies. [ABSTRACT FROM AUTHOR]

This paper studies the economically significant problem of the optimization of customs fraud control, which is a critical issue for many countries. The European Union (EU) alone handles 4693 tons of goods every minute (2018 figures). Even though 70% of goods are imported at zero tariff, the EU raised EUR 25.4 billions in 2018, and customs-related income transferred by member states to the EU accounts for nearly 13% of its overall budget. In this field, (a) the conflicting objectives are qualitative and cannot be reduced to a common measure (security and terrorism, health, drug market access control, taxes, etc.); (b) each submitted item has dozens of characteristics; (c) there are constraints; and (d) risk analysis systems have to make decisions in real time. Although the World Customs Organization has promoted the use of artificial intelligence to increase the precision of controls, the problem is very complex due to the data characteristics and interpretability, which is a requirement established by customs officers. In this paper, we propose a new Bayesian-based hybrid approach combining machine learning and multi-objective linear programming (MOLP), called multi-objective Bayesian with dynamic optimization (MOBADO). We demonstrate that it is possible to more than double (with a 237% increase) the precision of current inspection systems, freeing up almost 50% of human resources, and outperform past results with respect to each of the above objectives. MOBADO is an optimization technique that could be combined with any artificial intelligence approach capable of optimizing the quality of multi-objective risk analysis in real time. [ABSTRACT FROM AUTHOR]

The European-wide environmental obstacles of inefficient and unsustainable recycling systems and flows constrain household waste (HW) management, endangering the circular economy. The European 2020 strategy and ongoing environmental disasters indicate the ineffectiveness of the current HW sustainability practices. This paper introduces an artificial intelligence (AI) approach for calculating urban residual waste, based on its generation level. It reforms the current diverse and high discrepancy levels of HW residual for EU-countries and Ukraine. Adopting a k-means clustering method with a multi-criteria taxonomic development level index (TIDL), it produces uniform clusters with higher accuracy and manageability. Findings discover and remedy opaque managerial practices, enabling sustainable and environment-friendly development at national and regional levels for EU-countries. Results reveal an increased number of clusters in crisis, contributing to a methodological reference for environmental planning. In conclusion, this AI approach could have a European-wide impact on sustainable economic value-chain, converging toward an eco-friendly economy. [Display omitted] • Analysis of household waste management strategies in EU and Ukraine. • A methodological reference for environmental planning that moves away from the current centralized model. • Implementation of k-means household waste clustering approach with situational analysis and planning. • AI clustering approach with a multi-criteria taxonomic index for higher accuracy and manageability of waste. • Exploration of integrated AI-development economics for EU-Ukraine environmental policy. [ABSTRACT FROM AUTHOR]

Digitalization, robotization, artificial intelligence, and all kinds of new technologies that are known as Industry 4.0 or the fourth industrial revolution have great influence on the future of work because they will gather new jobs with new skills, and a majority of the senior workforce will probably have a lot of problems with those kinds of changes and challenges. The major objective of the paper is to recognize the dependence of the unemployment of the age category 55–64 upon selected explanatory variables. The explanatory variables were selected, and the expectations of their signs were presented in the research design. The secondary data of Eurostat and OECD 2015 has been used, covering the twenty-two member countries of the European Union (the countries that provided minimum wage were included only). The econometric analysis, specifically model specification and model quantification were the main methods used in the paper. The main outcomes and relevance of the model as well as its limitations have been compared with the findings of other authors in the discussion and implications for further research. [ABSTRACT FROM AUTHOR]

In this paper, we forecast the price of CO2 emission allowances using an artificial intelligence tool: neural networks. We were able to provide confident predictions of several future prices by processing a set of past data. Different model structures were tested. The influence of subjective economic and political decisions on price evolution leads to complex behavior that is hard to forecast. We analyzed correlations with different economic variables related to the price of CO2 emission allowances and found the behavior of two to be similar: electricity prices and iron and steel prices. They, along with CO2 emission allowance prices, were included in the forecasting model in order to verify whether or not this improved forecasting accuracy. Only slight improvements were observed, which proved to be more significant when their respective time series trends or fluctuations were used instead of the original time series. These results show that there is some sort of link between the three variables, suggesting that the price of CO2 emission allowances is closely related to the time evolution of the price of electricity and that of iron and steel, which are very pollutant industrial sectors. This can be regarded as evidence that the CO2 market is working properly. [ABSTRACT FROM AUTHOR]