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15 + 10: European identities ; [eine Ausstellung anlässlich des EU-Beitritts zehn neuer Mitgliedsländer am 1. Mai 2004]
In: Kataloge des Österreichischen Museums für Volkskunde 84
Algorithmic governance & AI in the post COVID-19 society
We may dare to ask about rationale behind the recent devotion caused by Artificial Intelligence (AI). Whether it could be produced by the fear or, by contrast, it stems from the inner ignorance and uncertainty that blind us by attempting to give a quick explanation to a massive technological disruption directly caused by COVID19. AI is not a new phenomenon as such, despite the fact that what it could be new is the way AI is already interfering in citizens' daily life functions and services shaping them with a deep intensity as a result of the processing capacity of AI. Nonetheless, (i) little is known so far about the relationship between AI and governance, or what is worst, (ii) AI is being deployed without considering democratic accountability and far from our public eye and scrutiny. Acknowledging the complexity of such topic, this article constructively aims to analyse the ongoing technopolitical transformations occurring in the aftermath of the coronavirus crisis for the governance model of the Basque Country. This article is targeted to the political left (either Basque or Spanish nationalist) in pursuit of avoid delaying the work that should be implemented in response to questions, challenges, and policies for XXI. century algorithmic governance. The article concludes through three-intertwined-layer approach: (i) the first approach lists AI functional uses; (ii) the second approach presents brefly several AI projects being currently developed in different European countries; (iii) ultimately, a strategic roadmap lead to stakeholders in the Basque Country is outlined.
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Maltese-English parallel corpus MaCoCu-mt-en 1.0
In: http://hdl.handle.net/11356/1525
The Maltese-English parallel corpus MaCoCu-mt-en 1.0 was built by crawling the ".mt" internet top-level domain in 2021, extending the crawl dynamically to other domains as well. All the crawling process was carried out by the MaCoCu crawler (https://github.com/macocu/MaCoCu-crawler). Websites containing documents in both target languages were identified and processed using the tool Bitextor (https://github.com/bitextor/bitextor). Considerable efforts were devoted into cleaning the extracted text to provide a high-quality parallel corpus. This was achieved by removing boilerplate and near-duplicated paragraphs and documents that are not in one of the targeted languages. Document and segment alignment as implemented in Bitextor were carried out, and BicleanerAI (https://github.com/bitextor/bicleaner-ai) and Bifixer (https://github.com/bitextor/bifixer) were used for fixing, cleaning, and deduplicating the final version of the corpus. While the TXT format consists solely of pairs of source and target segments (one or several sentences), each segment pair in the TMX format is accompanied by the following metadata: - source and target document URL; - quality score as provided by the tool BicleanerAI; - translation direction identification: the source segment in each segment pair was identified by using a probabilistic model; - personal information identification ("biroamer-entities"): segments containing personal information are flagged, so final users of the corpus can decide whether to use these segments; - language variants: the language variant of English (British or American) was identified for every segment pair on document and domain level. Notice and take down: Should you consider that our data contains material that is owned by you and should therefore not be reproduced here, please: (1) Clearly identify yourself, with detailed contact data such as an address, telephone number or email address at which you can be contacted. (2) Clearly identify the copyrighted work claimed to be infringed. (3) Clearly identify the material that is claimed to be infringing and information reasonably sufficient in order to allow us to locate the material. (4) Please write to the contact person for this resource whose email is available in the full item record. We will comply with legitimate requests by removing the affected sources from the next release of the corpus. This action has received funding from the European Union's Connecting Europe Facility 2014-2020 - CEF Telecom, under Grant Agreement No. INEA/CEF/ICT/A2020/2278341. This communication reflects only the author's view. The Agency is not responsible for any use that may be made of the information it contains.
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