European Union

The financial crisis eventually went to the core of the institutional infrastructure of the euro - whose reform is still ongoing a decade later.

Britain on Monday (28 December) urged businesses to prepare for Brexit, just days before a transition period designed to smooth the UK's departure from the European Union comes to an end.

Britain and the European Union on Saturday (26 December) published the full text of the post-Brexit trade agreement aimed at governing their relationship when the UK definitively leaves the bloc's single market in just five days.

The European Union began a vaccine rollout Saturday (26 December), even as countries in the bloc were forced back into lockdown by a new strain of the virus, believed to be more infectious, that continues to spread from Britain.

Written by Mihalis Kritikos,

© Adobe Stock

Blockchain has the potential to promote compliance with traditional ethical principles, especially in the fields of healthcare, supply chain management and food safety. As artificial intelligence (AI) companies and other organisations seek ways to comply with ethical principles and requirements, blockchain could be seen as a means to ensure that AI is deployed in an ethically sound manner, under certain specific conditions.

Blockchains are open, decentralised ledgers that record transactions between two parties without the need for third-party authentication. Their ability to ensure that data are secure, well-protected and reliable, and thus can be shared in a secure and auditable manner, mean that blockchain applications are being used in a growing number of domains, such as healthcare management, cross-border payments and supply chain monitoring. Their implementation raises ethical concerns about security vulnerabilities, environmental impact – given the high amount of computing power needed, accountability, privacy and the apparent enabling of cybercrime. Various policy initiatives have been launched to address these challenges in the form of ethical design frameworks, guiding principles and the Blockchain Code of Ethics. At the same time, blockchain has emerged lately as a carrier of ethical values that could resolve societal challenges of high ethical import in several domains. Can the intrinsic features of blockchain technology help AI developers comply with the multiplicity of ethical demands in their field and in effect contribute to the ethical design and deployment of AI applications?

Potential impacts and developments

Blockchain technology has the potential to create ethical value by creating more transparent and traceable food supply chains to tackle major challenges such as unethical labour practices and environmental degradation. Its ethical value also lies in its ability to provide for secured proof of origin and ethical sourcing. It can also facilitate the sharing of medical data via the automation of some aspects of consent and data collection. Beyond the indirect effects of blockchain on the achievement of certain ethical aims within specific policy domains, this emerging technology appears to offer the means to facilitate the compliance of AI, in its various manifestations, with ethical principles and human rights standards.

It is well known that the quality, accuracy and representative nature of the data needed to train algorithms and develop human-centric machine learning models is central to the ethical soundness of AI applications. However, as there is no oversight mechanism and no standard methodologies to review the fairness of these algorithms or the privacy-friendly nature of the data analytics used, multiple calls have been made for the development of ethics standards and frameworks. The opacity of algorithmic operations and the use of self-learning algorithms for predictive policing, social security or diagnostics is currently at the epicentre of the ethical debate at EU level.

This is precisely where blockchain technologies can play an important role in helping AI applications and systems be designed and implemented in an ethically sound manner. One of the main advantages of blockchain lies in its ability to ensure that data are secure, private, reliable and valid, and thus personal data are not compromised. Therefore, blockchain enables cooperative and safe data-sharing, by cryptographically ensuring the trustworthiness of data. It may therefore be seen as a way to enable users to share their data with trusted stakeholders before the data are collected and processed by powerful AI systems in the context of specific decentralised AI platforms. In other words, the introduction of decentralised blockchain solutions in the context of AI may facilitate the removal of false or incorrect data sets, strengthen the privacy-friendly nature of AI data infrastructure and, essentially, contribute to its ethical design and deployment.

Given that blockchain can operate as a transparency machine where its users are assured that the data stored, on a datapoint-by-datapoint basis, have not been tampered with through the use of cryptographic hashing, digital signatures or smart contracts, it can increase the trust that is so necessary in the field of AI. Transparency is in fact one of the seven ethical requirements put forward by the High-Level Expert Group on AI and endorsed by the European Commission. This is also a necessary step to promote and protect the principle of explicability: the need for AI processes to be transparent and explainable.

As blockchain technologies offer users a detailed view of how data are being used, the introduction of these properties into the AI context could potentially help developers to design human-centric and responsible algorithms, and citizens to exercise their right to explanation and to effective remedy. In fact, allowing advanced AI models and large datasets to be widely shared, updated and re-trained could boost trust in algorithmic decision-making systems.

Moreover, blockchain’s traceability and data integrity features and its capacity to operate in a decentralised manner could be crucial in ensuring that the data used in AI systems are reliable, of high quality and bias-free. Blockchain’s use of immutable records of all the data, variables, and processes used by AI for its algorithmic decision-making processes could enable decision-makers in the field of AI to audit the main tenets of the systems/applications used, review and diversify datasets, set aside data that could lead to false negatives, and identify biased algorithms. That could eventually enable AI applications to be viewed as reliable sources of information and knowledge that could not develop any discriminatory or manipulative effects via deep fakes or predictive behaviour algorithms.

As a result, the accessibility and transparency qualities of blockchain programming, making it possible to audit all steps of the process – from data entry to processing outcomes – could serve as a solid basis for demystifying AI, enhancing the ethical nature of algorithmic decision-making systems and solving the AI black box problem through transparency and algorithmic impact assessments. That way, blockchain, by being publicly auditable, would help the public understand machine learning decisions, thus increasing the explainability of AI systems. Blockchain’s recording properties can help AI users and decision-makers trace, review and reframe all variables that feed into decisions made on the basis of machine-learning procedures.

Last but not least, not only could blockchain’s ability to operate without intermediaries prevent data manipulation, it could also allow small AI companies to obtain trustworthy data directly from their creators through decentralised blockchain data networks. This is particularly important for the ethical development of AI, as blockchain programming can also create an incentive system that could encourage users to contribute and share their data. Such a system could, in effect, enhance the robustness and fairness of data models, strengthen the quality of algorithmic data sets and bring forward a paradigm shift in the ethical governance of AI applications.

Anticipatory policy-making

As the issue of AI ethics has become a key part of discussions on governance and regulatory control of this transformative technology at both organisational and policy-making levels, new and creative ways need to be found to secure the efficient operationalisation of commonly agreed ethical principles. That requires not only the development of practical implementation guidance but also the employment of new tools.

Blockchain, due to its specific design qualities, can become part of ethical problem-solving in the field of AI in various ways. As legislators across the world seek ways to identify the sources and address the effects of data bias in the context of AI, and to introduce a proportionate risk assessment and management framework, blockchain architecture can become an integral element in the ethics-by-design approach. This concept has been proposed repeatedly by the European Parliament and was also reflected in its recent resolution on the framework of ethical aspects of artificial intelligence, robotics and related technologies.

In the light of the Commission’s upcoming legislative proposal on the control of AI and the recently proposed data governance act, the regulatory features of blockchain could offer numerous advantages, including anonymisation, enhanced data security, immutability, and consensus-driven tools. Its integration into the AI world could provide developers and users alike with an ecosystem of modalities and features that would enhance the effective implementation of ethical requirements and principles and, in effect, increase public trust in AI systems. Given the potential benefits of the introduction of blockchain properties into AI platforms, the establishment of EU-wide hybrid pilot platforms that could facilitate the convergence of AI and blockchain architectures could unleash the potential of blockchain as an ethical game-changer in the field of AI.

Read this ‘at a glance’ on ‘What if blockchain could guarantee ethical AI?‘ in the Think Tank pages of the European Parliament.

The EU issued a declaration expressing concern about the humanitarian situation, and the allegations of human rights violations and ethnic targeting in Ethiopia.

So far, Donald Trump, who has 27 days left in the White House until President-elect Joe Biden is sworn in on 20 January, has issued 70 pardons since taking office.

Written by Mihalis Kritikos,

© Adobe Stock

Thermal imaging cameras have been widely installed in recent months in office buildings, hospitals, shopping malls, schools and airports as a means of detecting people with fever-like symptoms. Given their capacity to perform temperature checks from a distance, they have been seen as an effective means to limit the spread of the highly contagious Covid-19 virus. Looking beyond manual temperature checking, this note provides an overview of the use of thermal-imaging empowered with artificial intelligence (AI) capabilities, its suitability in the context of the current pandemic and the core technical advantages and limitations of this technology. The main legal responses and ethical concerns related to the use of AI in the context of thermal imaging at entry points, to identify and triage people who may have elevated temperatures, are also examined.

Infrared thermal-imaging cameras can measure radiated energy emitted from the human skin in a contactless, safe and fast manner. Adding machine-learning capabilities allows them to survey large groups of people at points of entry in an inexpensive, non-invasive way and to process their temperatures in seconds in the context of the current pandemic. Within this context, AI-enhanced thermal imaging cameras are currently being used in sensitive locations around the world to spot those who may have a symptom of the virus. Is general fever measurement through thermal cameras an effective means to tackle Covid‑19? Are these cameras designed or sufficiently operationally mature to operate as medical devices or diagnostic tests? Should we consider the possible legal and ethical implications related to the use of these cameras, especially when paired with facial recognition software and movement-predictive algorithms? Are employees and passengers aware of their data protection rights, including their right to rectification as well as their right to benefit from a second measurement?

Potential impacts and developments

AI-based thermal-imaging technology allows for fast and scalable screening of employees and travellers, from a distance, while they are moving, and without asking individuals to queue for individual checks. It can identify potential Covid‑19 carriers by automating and streamlining the monitoring of an individual’s temperature, simplifying and standardising record-keeping, and by reducing the need for invasive or potentially error-prone manual tracking procedures.

The integration of optimised algorithms for fever detection and facial-detection algorithms, as well as mask wearing detection functions, in thermal cameras allows them to  recognise human faces obscured by masks and glasses and distinguish faces from nearby objects in real time by excluding other heat sources. Through the use of machine-learning algorithms, automated recalibration procedures and AI-powered statistical analytics, thermal imaging can achieve high measurement speed and accurate temperature screening of up to 95 %. The incorporation of advanced AI image-processing and video-analytics algorithms not only allows the detection of elevated skin temperature in high-traffic public places through quick multiple target screening but also facilitates the emission of automatic alerts to security personnel. The integration of accurate mask-on face-recognition functionalities in thermal-imaging cameras is currently being tested in the United States of America, Israel, China and several Latin American countries.

Some authorities are now able to identify patients with an elevated temperature, revisit their location history through automated analyses of closed-circuit television (CCTV) footage, and provide audio and visual notification of temperature-screening passes and failures. London Heathrow Airport has used the technology to carry out large-scale passenger temperature checks, whereas Los Angeles International Airport has begun piloting thermal-imaging cameras that can detect fever in travellers. The installation of these cameras in entry points could reduce bottlenecks and delays, screen dozens or hundreds of people without the latter violating social distancing requirements, but also requiring less manpower for temperature checks.

At the same time however, the European Union Aviation Safety Agency, the European Centre for Disease Prevention and Control and the World Health Organization (WHO) have concluded that thermal screening of passengers is a ‘high-cost, low-efficiency measure‘. There is little evidence of its effectiveness and accuracy in detecting and mitigating Covid‑19 cases, given that temperature is a bad proxy for having the disease. In addition, these measuring devices are sometimes not very accurate when used in high-traffic areas, where several individuals are moving in different directions at once, while being presented to the camera from different distances and at different angles.

Moreover, scanning may not detect people with early-stage illness, asymptomatic illness, those with symptoms that do not include fever, or those who take medicines to reduce their temperature. The UK Medicines and Healthcare products Regulatory Agency has noted that thermal cameras are not a reliable way to detect if people have the virus whereas the US Food and Drug Administration has concluded that, despite their multiple advantages, are not effective at determining if someone definitively has Covid-19.

Anticipatory policy-making

In view of the absence of a common international standard for health-screening at airports and workplace locations, the use of thermal-screening cameras triggers questions about their compliance with ISO 13154, which sets the standard for deployment and implementation, and operational guidelines for identifying febrile humans using a screening thermograph, as well as with IEC 80601-2-59:2017 requirements for the basic safety and essential performance of screening thermographs for human febrile temperature screening.

Do temperature checks using AI-assisted thermal cameras constitute processing of personal data wholly or partly by automated means within the meaning of Article 2(5) of the General Data Protection Regulation (GDPR)? Is the use of cameras to perform mass checks justified under the duty of care of the employer towards employees and proportionate under data protection and human rights laws? Is temperature-related data going to be analysed along with other biometric identifiers?

Many European Data Protection Authorities (DPAs), including in Belgium, France, Czechia, the Netherlands and Poland, have made a series of recommendations that range from absolute prohibition of their use for triaging people, to allowing thermal scanning under specific conditions. Such conditions include an analysis of the data life cycle and the verification that there is no recording of thermal images in accordance with the orientations on body temperature checks in the context of the Covid‑19 crisis that were recently issued by the European Data Protection Supervisor. An assessment of this kind should take account of the necessity, proportionality and effectiveness of this technological solution and provide for meaningful human involvement.

Beyond privacy concerns, the gradual installation of AI-enhanced thermal-imaging cameras enabled by facial recognition technology as a fever-detection tool in public spaces raises questions about their effects on the civil liberties of travellers and employees alike including questions of surveillance creep, namely the collection of biometric data beyond the current emergency context. The gradual introduction of this technology in airports and office buildings to proactively detect an elevated temperature also raises questions about what happens when people are detected as having fever, especially in cases of false positives:

Can they be banned from the airport or their workplace? Are robust safeguards in place to verify the technical accuracy of these public health measures, including meaningful human overview and control of the system? Are ethically and legally sound standardised technical protocols in place that could prescribe additional tests and temperature checks, data verification, and robust data protection safeguards?

In view of the novelty and possible limitations of the technological solutions being proposed, it would seem reasonable that any remote temperature-screening finding should be accompanied by secondary temperature screening, temperature checks by a healthcare professional and health questionnaires, and should be directed by public health guidance. They should be viewed as only one layer of protection in the context of the wider ecosystem of public-health emergency responses to the current pandemic.

Read this ‘at a glance’ on ‘What if AI could improve thermal imaging, to help fight coronavirus?‘ in the Think Tank pages of the European Parliament.

Political leaders in Europe on Thursday (24 December) hailed the belated sealing of a UK-EU post-Brexit deal that aims to lay the groundwork for long-term future cooperation. Britain British Prime Minister Boris Johnson lauded what he termed “a good deal...

The French government on Thursday (24 December) announced measures to support fishermen and fishmongers, including up to €30,000 in individual aid, after the European Union and the UK reached a post-Brexit trade agreement.

Britain, while clinching a trade deal with the EU, said Thursday (24 December)  it was backing out of a European student exchange programme and replacing it with a global scheme named after computing pioneer Alan Turing.

Madrid and London have yet to reach agreement on the status of Gibraltar, Spanish Prime Minister Pedro Sanchez said Thursday (24 December) after Britain and EU finally sealed a Brexit trade deal.

European Council President Charles Michel welcomes the agreement on the future EU-UK relationship as major step forward.

UK Prime Minister Boris Johnson boasted on Thursday (24 December) that the Brexit-question has been put to bed for a generation, as he announced the agreement of a new EU-UK trade treaty which will take effect from 1 January.

European Union fishing fleets will have to give up a quarter of their current catch in British waters over the next five and a half years, officials said Thursday (24 December).

The European Union and Britain on Thursday (24 December)  struck a post-Brexit trade deal to cushion the economic blow of the UK's imminent departure from the single market after 10 months of tortuous negotiations.

Statement by the President of the European Parliament David Sassoli and the Head of Parliament's UK Coordination Group David McAllister on the agreement reached on future EU-UK relations.
Committee on Foreign Affairs
Committee on International Trade

Source : © European Union, 2020 - EP

Statement by the President of the European Parliament David Sassoli and the Head of Parliament's UK Coordination Group David McAllister on the agreement reached on future EU-UK relations.
Committee on Foreign Affairs
Committee on International Trade

Source : © European Union, 2020 - EP

The Council prolonged the mandate of its two Common Security and Defence Policy missions in Somalia: the civilian capacity-building mission EUCAP Somalia, and the military training mission EUTM Somalia, until 31 December 2022.

Written by Vadim Kononenko,

© Adobe Stock

Technological innovation has always been an indispensable part of recovery from economic, social and environmental crises. Technology is often diametrically opposed to matters of aesthetics and culture. Yet historical experience and foresight suggest that in times of recovery technology and culture can combine to create a virtuous feedback loop. This could facilitate the EU’s post-pandemic recovery and also help tackle the potentially disruptive effects of the ‘green transition’.

With its current European Green Deal plan, the EU is striving to achieve climate neutrality in its economy by 2050 and, simultaneously, set itself on the path to recovery from the adverse effects of the global pandemic. Technology will inevitably play a significant part in this process. However, history also suggests that culture and aesthetics have a significant role to play in recovery from a crisis, be it war, economic recession or an epidemic.

Well-known artistic and architectural movements such as the Renaissance, Romanticism and Neo-Classicism came about in direct or indirect response to various shocks in Europe, for example, the plague of the 13th century, the Industrial Revolution of the 18th century, and political upheavals of the 19th century. Most recently, the 20th-century modernist movement was spearheaded by the recovery from the two world wars and skyrocketing post-war economic growth. None of these cultural movements developed autonomously from technology, however. Modernism, for example, was underpinned by the invention of steel and concrete construction techniques.

Potential impacts and developments

It is logical to assume that the EUs unprecedented green transition to a carbon-free economy will be accompanied by new technologies and also, perhaps, a new cultural movement. Some policies featuring cultural and technological aspects have emerged in recent years, in the form of the Davos Declaration and Baukultur and, most recently, the New European Bauhaus initiative of the European Commission. Yet the question remains: how can technology and culture align to further a green post-pandemic recovery in Europe, particularly given the extreme negative impacts of the pandemic on the cultural sector?

Among the many pertinent aspects of the interconnected dynamics of technology and culture, two in particular stand out:

• There is a disruptive side to every recovery, as the many accompanying changes leave ‘stranded assets’ in their wake: investments that prematurely lose their value. Rapidly changing technology is often a factor that contributes to this phenomenon. For example, recovery from the Great Depression was closely related to the rise of the automobile industry, leading to the decline of American urban city centres. The green recovery, which is based on renewable energy technologies, is generating different kinds of stranded assets, for example, coal mines and pipelines or the beautiful but single-glazed windows of historical buildings. The rapid rise in teleworking is leaving a massive amount of unused office space as stranded assets. Culture could be the answer in cases such as these. To match the circular economy, a new aesthetic of car-free urbanism and ‘green and blue‘ cities is emerging. Likewise, re‑purposing old coal plants and empty office buildings into green neighbourhood and museum clusters is an increasingly popular and effective solution. In this regard, culture is helping to tackle the social impacts of technological disruption.
• Conversely, culture itself can benefit from technological change. This has been seen during the pandemic, in which digital technologies have greatly aided the creative sector. Museums, concert halls and other cultural institutions have taken to live-streaming, online events, and open access to digital material. It is likely that these technologies will continue to serve the cultural sector in the recovery phase as well. However, the question is how sustainable this online content is, both for the economic survival of institutions and creators, and for the alignment of digital technologies with environmental targets.

Overall, however, both culture and technology have the potential to open up opportunities for sustainable and inclusive recovery. According to a recent analysis by the Organisation for Economic Co-operation and Development (OECD), cities and regions should consider the cultural and creative sectors and cultural participation as drivers of both economic and social advancement.

Anticipatory policy-making

When it comes to maximising the effectiveness of the contribution of technology and culture, anticipatory policy-making is key. In recent years, future-oriented strategic thinking has proliferated in new cultural domains, including architecture, design, and heritage. Foresight in these cultural domains can help policy-makers design policies to aid the green recovery. As far as the technology–culture nexus is concerned, anticipatory policy-making could explore the following three areas:

Citizen-centred approach: People’s collective memories, beliefs and attitudes to particular aesthetics constitute what anthropologists call ‘tacit culture’. It functions as a link between function and form, and appears to transcend political preference, age and ethnicity. For example, a recent poll suggests that 75 % of Americans prefer a classical style in public buildings, whereas only 25 % prefer a modernist style. Another study examining the views of hospital patients in Europe and Japan showed a consensus across countries on what people consider important in terms of the aesthetics of a hospital environment. This means that when working out policies on how buildings should be retrofitted to be rendered climate-neutral and how cities need to change according to circular economy principles, policy-makers would benefit from considering these tacit cultural trends and consulting widely on citizens’ aesthetic preferences. A useful step towards citizens’ dialogues would be the inclusion of cultural and heritage-oriented themes in the Conference on the Future of Europe process.

Strategic foresight and impact assessment: As EU policy-making is currently undergoing a profound embedding of foresight and impact assessment into its workings, culture remains somewhat overlooked. The current Better Regulation guidelines list environmental, social and economic impacts as the most important, with increased attention being directed towards the impact on the United Nations sustainable development goals (SDGs). As culture and heritage are at the heart of the SDGs, there is room for a more robust assessment of European added value in the fields of culture and heritage. Useful work has been done in this regard by Unesco, putting heritage impact assessment (HIA) on a par with the more widely used environmental impact assessment (EIA). The impact of new technologies in the cultural sector, such as digitalisation and AI, could be improved with the aid of such assessment.

Culture as innovation: As the OECD report notes, cultural institutions have difficulties gaining recognition as an innovative sector and accessing support measures that are typically reserved for more technological forms of innovation. While many innovations in the cultural sector do include technology – digitalisation, for example – there are other forms of innovation that are based on creative content. Examples include projects in which citizens ‘adopt’ a monument, social-media projects that popularise sustainable renovation and cultural heritage among young people, and grassroots non-profit cooperatives that promote and facilitate the salvage and reuse of construction materials.

Read this ‘at a glance’ on ‘What if technology and culture combined to boost a green recovery?‘ in the Think Tank pages of the European Parliament.