Collaborating Authors

Europe Government

Machine Learning Can Help Detect Misinformation Online


As social media is increasingly being used as people's primary source for news online, there is a rising threat from the spread of malign and false information. With an absence of human editors in news feeds and a growth of artificial online activity, it has become easier for various actors to manipulate the news that people consume. RAND Europe was commissioned by the UK Ministry of Defence's (MOD) Defence and Security Accelerator (DASA) to develop a method for detecting the malign use of information online. The study was contracted as part of DASA's efforts to help the UK MOD develop its behavioural analytics capability. Our study found that online communities are increasingly being exposed to junk news, cyber bullying activity, terrorist propaganda, and political reputation boosting or smearing campaigns.

The impact of machine learning and AI on the UK economy


A recent virtual event addressed another such issue: the potential impact machines, imbued with artificial intelligence, may have on the economy and the financial system. The event was organised by the Bank of England, in collaboration with CEPR and the Brevan Howard Centre for Financial Analysis at Imperial College. What follows is a summary of some of the recorded presentations. The full catalogue of videos are available on the Bank of England's website. In his presentation, Stuart Russell (University of California, Berkeley), author of the leading textbook on artificial intelligence (AI), gives a broad historical overview of the field since its emergence in the 1950s, followed by insight into more recent developments.

European Parliament names MEPs on artificial intelligence, cancer plan and foreign interference …


The European Parliament announced the MEPs who will sit on its new special committees on artificial intelligence (AI), cancer and foreign interference …

Europe and AI: Leading, Lagging Behind, or Carving Its Own Way?


For its AI ecosystem to thrive, Europe needs to find a way to protect its research base, encourage governments to be early adopters, foster its startup ecosystem, expand international links, and develop AI technologies as well as leverage their use efficiently.

AI, Machine Learning Playing Important Role in Fighting COVID-19 - AI Trends


AI and machine learning are playing an important role in fighting the pandemic brought on by COVID-19, with technological innovation and ingenuity being applied to large volumes of data to quickly identify patterns and gain insights. Efforts are underway to speed up research and treatment, and better understand how COVID-19 spreads. Chatbots employing AI are speeding up communication around the pandemic. One example is from, a French startup that launched a chatbot to make it easier for people to find official government communications about COVID-19, according to an account from the World Economic Forum. The bot is getting realtime information from the French government and the World Health Organization, to help relay known symptoms and answer questions about government policies.

Europe's data revolution


The growth potential of the data economy is mind-blowing. In Europe alone, the figures and forecasts are eye-catching, to say the least. The European Commission expects the value of the data economy to rise to €829 billion by 2025, up from €301 billion in 2018. Focusing on the headline economic figures alone overlooks the enormous potential to use data to create lasting social change and improve the personal and professional lives of millions of European citizens. The term digital economy is a catch-all for a wide range of digital transformation activities.

Improve alignment of research policy and societal values


Historically, scientific and engineering expertise has been key in shaping research and innovation (R&I) policies, with benefits presumed to accrue to society more broadly over time ([ 1 ][1]). But there is persistent and growing concern about whether and how ethical and societal values are integrated into R&I policies and governance, as we confront public disbelief in science and political suspicion toward evidence-based policy-making ([ 2 ][2]). Erosion of such a social contract with science limits the ability of democratic societies to deal with challenges presented by new, disruptive technologies, such as synthetic biology, nanotechnology, genetic engineering, automation and robotics, and artificial intelligence. Many policy efforts have emerged in response to such concerns, one prominent example being Europe's Eighth Framework Programme, Horizon 2020 (H2020), whose focus on “Responsible Research and Innovation” (RRI) provides a case study for the translation of such normative perspectives into concrete policy action and implementation. Our analysis of this H2020 RRI approach suggests a lack of consistent integration of elements such as ethics, open access, open innovation, and public engagement. On the basis of our evaluation, we suggest possible pathways for strengthening efforts to deliver R&I policies that deepen mutually beneficial science and society relationships. Alignment of R&I objectives with societal benefits, which transcend exclusive economic value, is a globally relevant concern ([ 3 ][3]). Aspiration of stronger science and society interrelationships have been visible in U.S. research management efforts, as well as in Canada and Europe. In H2020, to which the European Commission (EC) allocated nearly €80 billion for the 2014–2020 funding period, the EC enumerated RRI as a priority across all of H2020 activities (a “cross-cutting issue”) to deepen science and society relationships and be responsive to societal challenges. To date, €1.88 billion have been invested across 200 different R&I areas (e.g., quantum computing, graphene nanotechnology, human brain research, artificial intelligence) in more than 1100 projects related to various dimensions of RRI (see the figure). Inclusion of RRI in H2020 reflected the commitment of the European Union (EU) to the precautionary principle with regard to R&I policy, and the deepening commitment of the EC to mainstream concerns related to science and society integration ([ 4 ][4], [ 5 ][5]). RRI principles and practices have been designed to enhance inclusive and democratic modes of conducting R&I to reflect current forms and aspirations of society ([ 4 ][4]). Formal adoption and exploitation of RRI in H2020 coalesced around six thematic domains of responsibility (“keys”): public engagement, gender equality, science education and science literacy, open access, ethics, and governance ([ 6 ][6]). As a relatively young concept, these six keys cover only a part of RRI as it is discussed in the academic literature. Their integration in the European R&I ecosystem was advanced by various political- and policy-level ambitions ([ 3 ][3]–[ 5 ][5]). The forthcoming Ninth Framework Programme, Horizon Europe (2021–2027), includes further mention of RRI, as well as additional efforts to increase responsiveness of science to society through elements of the so-called “three O's agenda” (i.e., open innovation, open science, openness to the world) ([ 7 ][7]). Despite this fairly extensive history of EC investment in mainstreaming activities, a recent survey of more than 3100 European researcher recipients of H2020 funding showed that a vast majority of respondents were not familiar with the concept of RRI ([ 8 ][8]). Although these findings by no means suggest that researchers are irresponsible, they raise questions about the success of the EC approach to embedding normative targets for responsibility into R&I. The need for systematic evaluation is clear ([ 9 ][9]). Our study contributes to a legacy of research on the efficacy of framework programmes in light of various EC ambitions ([ 10 ][10]). To answer our question about policy integration and implementation of RRI in H2020, we conducted a mixed method investigation in three stages: (i) desktop research, (ii) interviews, and (iii) case research [see supplementary materials (SM) S10 for details]. First, we collected and reviewed relevant documentation of the four H2020 Programme Sections (Excellent Science, Industrial Leadership, Societal Challenges, Diversity of Approaches) and 19 respective subthemes available on the websites of the EC. This included reviews of documents at the following levels: policy, scoping, work package, calls, projects, proposal templates, and evaluations. Review of documents extended to all three periods of H2020 (2014–2015, 2016–2017, and 2018–2020) and employed the six EC RRI keys as indicators. Second, we conducted interviews with representatives ( n = 257) of seven stakeholder groups within the 19 subthemes of H2020. Third, using natural language processing algorithms, we obtained and analyzed texts describing project objectives of all the H2020 projects (ongoing and finished, n = 13,644) available on the CORDIS Portal, which provides information on EU-funded R&I activities. We examined how proposal language and RRI policies translate into project activities across H2020 using text-mining approaches. We carried out keyword frequency analysis by applying a selection of 10 to 12 keywords (SM S8) associated with each of the six RRI keys. This resulted in an “RRI score” for each of six keys for each H2020 project (SM S13). This subsequent case research covered all three H2020 periods (i.e., 2014–2015, 2016–2017, and 2018–2020). At each of these stages we produced reports for each corresponding subtheme (SM S11). The resulting body of 19 reports was then systematically reviewed for levels of policy integration. The policy-integration levels were qualitatively assessed with the EC's own indicator assessment ([ 6 ][6]). ![Figure][11] How well is Responsible Research and Innovation represented in Horizon 2020? Limited high-quality reference to Responsible Research and Innovation (RRI) suggests that it has largely been referred to without proper understanding, or as an empty signifier. Data combine all four Horizon 2020 (H2020) program sections and reflect the amount and quality of representation of six RRI keys and three “O's,” across three levels: samples of internal H2020 program documents, H2020 stakeholder interviews, and H2020 project objectives. Comparison across keys within a given level is straightforward; all values are drawn from the same underlying materials. Comparison across levels within a given key should focus on relative proportions of the four colors within a given level, not on absolute values; analyses drew upon different types and amounts of underlying materials in each level. See supplementary materials for details. GRAPHIC: X. LIU/ SCIENCE This assessment demonstrates which elements of the RRI framework were initially defined by the policy-makers (desktop level), which RRI attributes the stakeholders were most aware of (interview level), and which RRI elements were manifested in project proposals (case level) (SM S12; see the figure). RRI as a concept has been present in most of the four Programme Sections of H2020, and particular RRI policy elements emerge as prominent in certain subthemes, especially those addressing societal challenges or explicitly promoting the uptake of RRI. But RRI overall has largely been referred to either without proper understanding of its definition, or as empty signifier, suggesting lack of compliance with the EC's interpretation of the RRI concept (see the figure; SM S9). Integration of the three O's agenda, contemplated as a successor to the RRI framework, lagged behind that of the six RRI keys; a finding consistent with introduction of the agenda in the later stages of H2020. Our results suggest that the integration of the RRI framework into H2020 has fallen short of stated EC ambitions. Our data show substantial discrepancies between the inclusion of RRI concepts within official subtheme documents (e.g., on policy and work programme levels), and awareness of RRI by interviewees working on projects funded by such subthemes (see the figure). Absence of RRI keys across the majority of programme subtheme evaluation criteria is a telling example. Such evidence suggests that (i) the RRI framework is still an evolving concept, the development of which hinders its proper understanding by those who are supposed to use it; (ii) such individuals have only superficial understanding of the notion for its effective exploitation; and (iii) although the RRI framework is present on the declarative, strategic policy level (scoping and subtheme general description), it wanes in funding calls (policy operationalization) and is largely absent in evaluation criteria used in proposal assessment. Collectively, these points further suggest that applicants have little in the way of consistently aligned incentives to regard RRI as relevant in proposal design and submission. Although (i) and (ii) are primarily a matter of a lack of adequate information, awareness and training, (iii) points to limitations of European science policy efforts related to the pursuit of RRI. Such translation failures are typically caused by interplay of different logics of negotiation at the different levels ([ 11 ][12]), a linear model of innovation appealing to scientific excellence in R&I ([ 12 ][13]), actors' resistance to change, path dependencies, cognitive boundaries, and competing policy agendas ([ 13 ][14]). As the issues covered by RRI are normatively claimed to be of high relevance by political decision-makers, as evidenced in several EC documents, we conclude that the problem is one of policy integration strategy and implementation ([ 14 ][15]). The lack of clarity in conceptualizing RRI for research policy and governance, the limited understanding among key stakeholders, and the concept's conflation with other—often conflicting—policy goals (e.g., scientific excellence, economic value, technological readiness) hinder the emergence of a specific RRI-oriented policy frame ([ 15 ][16]). Such conflicting policy goals are palpable at the core of European research funding (e.g., supporting either mission-oriented innovation or curiosity-driven basic research in key funding instruments) and highlight the structural tensions between the normative ideals and potential instrumentalization ([ 3 ][3]). There are some limitations of this study that must be taken into account when interpreting results. First, the measurements were cross-sectional and though representative, are not exhaustive. Generalizability of findings could be increased if the study were to extend in a longitudinal fashion and possibly to better elaborate causal relationships among factors. Second, although we employed mixed methods in our investigation, the number of interviews and case studies could be further increased to provide additional qualitative information about the dynamics of RRI at the project level. Third, as the framework programme remains ongoing, our analysis was not able to evaluate the entire H2020 corpus. Although the results indicate evidence of patchy RRI implementation, highlighting the need for more consistent support to help align EC science policy and societal values, the progress made is nontrivial, given the history of science ([ 1 ][1]). A clear discrepancy exists between the expressed strong normative position on RRI and its integration in concrete policies and practices. Fully integrating RRI as a strong normative position into research funding and governance is a necessary but not sufficient first step to creating a working policy system that drives RRI integration. Longer-lived investments are needed for building a shared understanding and awareness of the relevance of responsibility in R&I among key stakeholders. Integrating responsibility into research funding further requires RRI to shift from a “cross-cutting issue” to a “strategic concern” that receives consistent and sustained embedding in call texts and project selection criteria. This will require “policy entrepreneurs” who can stimulate interactions across subthemes to foster alignment of RRI integration and translation. In addition, a range of integration policies are required at the system level and within subthemes, in which the issue of RRI is adopted as a goal. This is pertinent as, in case of such integration failures, it is often the normative position that is called into question instead of the implementation strategy, or actual integration pathway. The EC would benefit from enhancing previous efforts to integrate RRI and so affirm its role as a leader of ethically acceptable and societally responsible R&I on the world stage. Otherwise Europe needlessly undercuts its ability to direct research toward tackling societal challenges in ways compatible with its values. [][17] 1. [↵][18]1. M. Polanyi, 2. J. Ziman, 3. S. Fuller , Minerva 38, 1 (2000). [OpenUrl][19][CrossRef][20][Web of Science][21] 2. [↵][22]1. N. Mejlgaard et al ., Science 361, 761 (2018). [OpenUrl][23][FREE Full Text][24] 3. [↵][25]1. R. von Schomberg, 2. J. Hankins 1. R. von Schomberg , in International Handbook on Responsible Innovation: A Global Resource, R. von Schomberg, J. Hankins, Eds. (Edward Elgar, 2019), pp. 12–32. 4. [↵][26]1. R. Owen, 2. P. Macnaghten, 3. J. Stilgoe , Sci. Public Policy 39, 751 (2012). [OpenUrl][27][CrossRef][28][Web of Science][29] 5. [↵][30]1. D. Simon, 2. S. Kuhlmann, 3. J. Stamm, 4. W. Canzler 1. R. Owen, 2. M. Pansera , in Handbook on Science and Public Policy, D. Simon, S. Kuhlmann, J. Stamm, W. Canzler, Eds. (Edward Elgar, 2019), pp. 26–48. 6. [↵][31]DGRI, “Indicators for promoting and monitoring responsible research and innovation: Report from the expert group on policy indicators for responsible research and innovation” (Report, European Commission, 2015); [\_rri/rri\_indicators\_final\_version.pdf][32]. 7. [↵][33]DGRI, Open innovation, open science, open to the world: A vision for Europe” (Directorate-General for Research and Innovation, European Union, 2016); . 8. [↵][34]1. S. Bührer et al ., “Monitoring the evolution and benefits of responsible research and innovation: Report on the researchers' survey – Study” [Report KI-1-18-886-EN-N, Directorate-General for Research; Innovation (European Commission), 2018]. 9. [↵][35]1. A. Rip , J. Responsib. Innov. 3, 290 (2016). [OpenUrl][36] 10. [↵][37]1. H. Rodríguez, 2. E. Fisher, 3. D. Schuurbiers , Res. Policy 42, 1126 (2013). [OpenUrl][38] 11. [↵][39]1. M. Howlett, 2. J. Vince, 3. P. Del Río , Politics Gov. 5, 69 (2017). [OpenUrl][40] 12. [↵][41]1. K. Rommetveit, 2. R. Strand, 3. R. Fjelland, 4. S. Funtowicz , “What can history teach us about the prospects of a European research area? Joint Research Centre scientific and policy reports” (Report JRC84065, European Commission, 2013). 13. [↵][42]1. H. Colebatch , Public Policy Admin 33, 365 (2017). [OpenUrl][43] 14. [↵][44]1. B. G. Peters et al ., Designing for Policy Effectiveness: Defining and Understanding a Concept (Cambridge Univ. Press, 2018). 15. [↵][45]1. R. Owen, 2. E.-M. Forsberg, 3. C. Shelley-Egan , “RRI-practice policy recommendations and roadmaps: Responsible research and innovation in practice” (Report, RRI-Practice Project, 2019); [\_Policy\_recommendations.pdf][46]. Acknowledgments: This project received funding from the EU's Horizon 2020 research and innovation programme under grant agreement no. 741402. We acknowledge all the consortium members who contributed to the data collection and writing of the reports (SM S11), which this study is based on. We express our gratitude to H. Tobi and N. Mejlgaard, as well as to the reviewers, for their helpful and constructive comments. [1]: #ref-1 [2]: #ref-2 [3]: #ref-3 [4]: #ref-4 [5]: #ref-5 [6]: #ref-6 [7]: #ref-7 [8]: #ref-8 [9]: #ref-9 [10]: #ref-10 [11]: pending:yes [12]: #ref-11 [13]: #ref-12 [14]: #ref-13 [15]: #ref-14 [16]: #ref-15 [17]: [18]: #xref-ref-1-1 "View reference 1 in text" [19]: {openurl}?query=rft.jtitle%253DMinerva%26rft.volume%253D38%26rft.spage%253D1%26rft_id%253Dinfo%253Adoi%252F10.1023%252FA%253A1026591624255%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [20]: /lookup/external-ref?access_num=10.1023/A:1026591624255&link_type=DOI [21]: /lookup/external-ref?access_num=000165793800001&link_type=ISI [22]: #xref-ref-2-1 "View reference 2 in text" [23]: {openurl}?query=rft.jtitle%253DScience%26rft.stitle%253DScience%26rft.aulast%253DMejlgaard%26rft.auinit1%253DN.%26rft.volume%253D361%26rft.issue%253D6404%26rft.spage%253D761%26rft.epage%253D762%26rft.atitle%253DEurope%2527s%2Bplans%2Bfor%2Bresponsible%2Bscience%26rft_id%253Dinfo%253Adoi%252F10.1126%252Fscience.aav0400%26rft_id%253Dinfo%253Apmid%252F30139865%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [24]: /lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiRlVMTCI7czoxMToiam91cm5hbENvZGUiO3M6Mzoic2NpIjtzOjU6InJlc2lkIjtzOjE0OiIzNjEvNjQwNC83NjEtYiI7czo0OiJhdG9tIjtzOjIxOiIvc2NpLzM2OS82NDk5LzM5LmF0b20iO31zOjg6ImZyYWdtZW50IjtzOjA6IiI7fQ== [25]: #xref-ref-3-1 "View reference 3 in text" [26]: #xref-ref-4-1 "View reference 4 in text" [27]: {openurl}?query=rft.jtitle%253DSci.%2BPublic%2BPolicy%26rft_id%253Dinfo%253Adoi%252F10.1093%252Fscipol%252Fscs093%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [28]: /lookup/external-ref?access_num=10.1093/scipol/scs093&link_type=DOI [29]: /lookup/external-ref?access_num=000312510500007&link_type=ISI [30]: #xref-ref-5-1 "View reference 5 in text" [31]: #xref-ref-6-1 "View reference 6 in text" [32]: [33]: #xref-ref-7-1 "View reference 7 in text" [34]: #xref-ref-8-1 "View reference 8 in text" [35]: #xref-ref-9-1 "View reference 9 in text" [36]: {openurl}?query=rft.jtitle%253DJ.%2BResponsib.%2BInnov.%26rft.volume%253D3%26rft.spage%253D290%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [37]: #xref-ref-10-1 "View reference 10 in text" [38]: {openurl}?query=rft.jtitle%253DRes.%2BPolicy%26rft.volume%253D42%26rft.spage%253D1126%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [39]: #xref-ref-11-1 "View reference 11 in text" [40]: {openurl}?query=rft.jtitle%253DPolitics%2BGov.%26rft.volume%253D5%26rft.spage%253D69%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [41]: #xref-ref-12-1 "View reference 12 in text" [42]: #xref-ref-13-1 "View reference 13 in text" [43]: {openurl}?query=rft.jtitle%253DPublic%2BPolicy%2BAdmin%26rft.volume%253D33%26rft.spage%253D365%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [44]: #xref-ref-14-1 "View reference 14 in text" [45]: #xref-ref-15-1 "View reference 15 in text" [46]:

UK rolls out AI-based cancer detection for NHS patients


Leader in AI-powered cancer diagnostics, Ibex Medical Analytics and provider of digital pathology services in the NHS, LDPath, have announced the UK's first rollout of clinical grade AI application for cancer detection in pathology. This platform will support pathologists in enhancing diagnostic accuracy and efficiency. Over the years, a global increase in cancer cases has coincided with a decline in the number of pathologists around the world. Traditional pathology involves manual processes that have remained the same for years. These processes involve slides to be analysed by pathologists using microscopes, and reporting is often carried out on pieces of paper.

UK regulators call Google, Apple search engine deal a 'barrier' to competition


UK regulators have criticized a browser deal between Apple and Google as a "significant" barrier to search engine competition. The CMA claims that current laws are not enough to properly manage and regulate large technology companies and their platforms, such as Apple, Google, or Facebook, and in particular, deals between different entities can become barriers to innovation and competition. Within the report, the agency highlights a deal made in 2019 between Google and Apple, in which the former paid roughly £1.2 billion ($1.5bn) to become the default search engine on a variety of mobile devices and systems in the United Kingdom alone. According to the regulators, the iPhone and iPad maker received the lion's share of this payment. "Rival search engines to Google that we spoke to highlighted these default payments as one of the most significant factors inhibiting competition in the search market," the CMA says.

The surprising future of fintech


Thanks to open banking, fintech early adopters likely already have accounts that round up transactions to boost savings or connect to third-party tools for loan applications, budget management and more. But the new wave of fintech startups are proving there's much more that can be done using open banking, the two-year-old mandate from UK regulators that required banks to easily allow their customers to share their data with third parties such as apps. "Open banking offers people the chance to get personalised, tailored support to help them manage their money by allowing regulated companies to securely analyse their bank data," says Lubaina Manji, senior programme manager at Nesta Challenges, one of the organisations behind the Open Up 2020 Challenge, alongside the Open Banking Implementation Entity (OBIE). "It's enabled the creation of new services and tools to help people with every aspect of money management – from budgeting to investing, and much, much more, all in a safe and secure way." And some of the innovations from finalists in the Open Up 2020 Challenge have surprised with their ingenuity and customer focus, she says, citing Sustainably's round-up tool for automated charity donations, and Kalgera's neuroscience-informed AI to help spot fraud targeting people with dementia – two projects that highlight the purpose-driven idea behind open banking and the aim to get financial support to show who need it the most.