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Language researchers are usually aware of intellectual property and personal data (PD) requirements. The problem, however, arises when these two legal regimes have conflicting requirements. For instance, when copyright law requires the acknowledgement of the author, but personal data law enshrines the data mini-misation principle. It is a practical question for a language researcher whether he should namethe author of the text used for, e.g., building a language model, or followthe data minimisation principle not to name the author. The access right that a data subject has introducessimilar conflicts. The question is what the scope of the access rightis. Does it cover only processed personal data,or does it extend to data derived from PD?

Publisher Copyright: © 2021 Estonian Association Applied Linguists. All rights reserved. The study focuses on the sharing of linguistic data containing personal data, which is the processing of personal data. Therefore, the requirements of the General Data Protection Regulation (GDPR) must be complied with. Compliance with these requirements is the responsibility of the controller, who may use the assistance of processors to process the data. In international practice, it is not clear how the responsibility for the processing of personal data is divided between a specific researcher and a research institution. For example, the French and German models differ from the Estonian, Lithuanian and Finnish models. The Greek model offers a unique approach. In general, the employer (organization or legal entity) is responsible for the processing of personal data. At the same time, research has its own specificity, which is characterized by academic freedom and as well as mobility of researchers. The situation is further complicated by the sharing of language data through research networks such as CLARIN. In the present study, the authors analyze the division of duties and responsibilities between the researcher and the research institution (including research networks). The authors also analyze how data sharing should take place from a personal data protection perspective. It is important to clarify whether the data provider and the data recipient are both controllers, joint controllers or the recipient is the processor and how the responsibility for data sharing is shared. The authors of the analysis have an interdisciplinary and international background, covering different areas of law (data protection, labor law, contract law) and jurisdictions (Estonia, Italy, Greece, Lithuania, France, Germany, Finland) and language technology.

Artikli eesmargiks on selgitada, millises ulatuses mojutab keeleandmetele kohalduv oiguslik režiim keelemudelite arendamist ja kasutamist. Autorid lahtuvad oma kasitluses protsessiskeemist, alustades algandmetest ning lopetades keeletehnoloogiat sisaldavate valmistoodetega (nt koneliidesega kulmik). Keeletehnoloogias kasutatavad algandmed sisaldavad tihti autorioiguslikult kaitstavaid teoseid, autorioigusega kaasnevate oiguste objekte (esitus, salvestus) ja isikuandmeid (isiku haal, isiku kohta kaiv muu info), mida sailitatakse annoteerimata ja annoteeritud andmekogudes. Keelandmete oiguslikke kusimusi on juba varem uuritud. Oiguslikult on labi uurimata aga keelemudelite oiguslikud aspektid. Autorid on seisukohal, et reeglina ei mojuta keelemudelite edasist oiguslikku staatust kasutatud algandmete oiguslik režiim, sest autorioigusega kaitstavad teosed mudelis pigem ei saili. Kull aga voib oiguslikke probleeme tekitada isiku haale kasutamine keelemudelis. Autorid analuusivad voimalikke lahendusvariante nende probleemide uletamiseks. Artiklis vaadeldakse ka uue autorioiguse direktiiviga kehtestatavat andmekaeve regulatsiooni ja selle rakendamist keelemudelite loomise kontekstis. *** Influence of legal regime of language data on language models This article aims to explain the extent to which the legal regime applicable to language data affects the development and use of language models. In their approach, the authors follow a process chart, starting from raw data to finished products containing language technology (eg a refrigerator with a speech interface). The raw data used in language technologies often include copyrighted works, objects of related rights (performances, sound recordings) and personal data (voice, other information about the person) stored in non-annotated and annotated databases. The legal issues of language data have already been studied. However, the legal aspects of language models have not been throughly explored. The authors are of the opinion that, as a rule, the legal status of the language models is not affect by the legal status of the used raw language data, since copyrighted works usually do not remain in the model. However, the use of a person’s voice in a language model can create legal problems. The authors analyze possible solutions to overcome these problems. The article also outlines the regulation of data mining introduced by the new copyright directive and its implementation in the context of development of language models.

The article focuses on determining responsible parties and the division of potential liability aris-ing from sharing language data (LD) containing personal data (PD). A key issue here is to identify who has to make sure and guarantee the GDPR compliance. The authors aim to answer 1) whether an individual researcher is a controller and 2) whether sharing LD results in joint controllership or separate controllership (whether the data's transferee becomes the controller, the joint control-ler or the processor). The article also analyses the legal relations of parties involved in data sharing and potential liability. The finalsection outlines data sharing in the CLARIN context. The analy-sis serves as a preliminary analytical background for redesigning the CLARIN contractual frame-work for sharing data.

The authors address the legal issues relating to the creation and use of language models. The article begins with an explanation of the development of language technologies. The authors analyse the technological process within the framework copyright, related rights and personal data protection law. The authors also cover commercial use of language models. The authors’ main argument is that legal restrictions applicable to language data containing copyrighted material and personal data usually do not apply to language models. Language models are generally not considered derivative works. Due to a wide range of language models, this position is not absolute.

7th International Conference of the Faculty-of-Law-of-the-University-of-Latvia on Legal Science - Functions,Significance and Future in Legal Systems, Riga, LATVIA, OCT 16-18, 2019 The purpose of this article is to explain the extent to which the legal regime applicable to language data affects the development and use of language technology (LT). The main focus of the paper is on EU law. The article also maps possible text and data mining (TDM) issues. The authors focus on TDM for research purposes outlined in the Digital Copyright Directive 2019/790.The authors follow a process approach of LT development, which starts from raw data collection and leads to LT products such as a refrigerator with a speech interface. Particular attention is given to language models.The raw data used in LT often include copyright-protected works, objects of related rights (e.g., performances) and personal data in the form of person’s voice or other information stored in non-annotated and annotated databases.The authors’ main argument is that the legal regime of language data does not usually affect the use of language models since copyrighted works are not likely to remain in models. In the process of developing a language technology application, language models are the first intermediate result that can be free from legal restrictions affecting language data. The use of a person’s voice as identifiable personal data in a language model can create legal challenges. In some cases, developers of language technology must be careful how to address issues of processing of personal data contained in models.

Kui keeleressursside autorioiguslikke kusimusi on eelnevalt pohjalikult uuritud, siis isikuandmete kaitse temaatika keeleressursside kontekstis on suurelt osalt katmata. Teema on aktuaalne, sest 25. mail 2018 hakatakse kohaldama EL-i isikuandmete kaitse uldmaarust. Kaesolevas artiklis analuusitakse isikuandmete kaitse kusimusi keeleressursside loomisel ja kasutamisel teadustoo eesmargil kahes kontekstis: 1) andmesubjekt ehk isik, kelle andmed keeleressursis sisalduvad, on andnud oma andmete tootlemiseks nousoleku; 2) nousolekut ei ole ning isikuandmete tootlemine toimub teadustoo erandi alusel. Artiklis analuusitakse keeleressursside loomisel kasutuses olevaid nousolekuvorme ning tehakse ettepanekuid, kuidas keeleressursside kontekstis isikuandmete kaitse regulatsiooni jargida. *** Data protection issues relating to the development and utilisation of language resources Copyright issues related to language resources have received considerable attention. Personal data protection in the field of language research is an area which is not thoroughly explored yet. This topic is very relevant since the General Data Protection Regulation is applicable from 25 May 2018. The authors analyse the issues relating to personal data protection in the context of the development and utilization of language resources. Firstly, the authors analyse the cases where there is a consent which allows processing of personal data to develop and use language resources for research purposes. Secondly, the processing of personal data without consent for language research purposes is explored. The article is meant to provide practical information to language research community and create a foundation for further discussion.

Keeleressursside arendamisel ei osata praktikas sageli arvestada lähtematerjali puudutavate õiguslike piirangutega, mis tekitab tarbetuid õigusriske ja võib takistada loodud ressursside sihipärast kasutamist ja levitamist. Artikli eesmärk on kaardistada levinumad probleemid ja pakkuda kehtivale õigusele tuginevaid lahendeid, viimaste puudumisel aga teoreetilisi ja praktilisi tõlgendusi. Autoriõiguslikult kaitstavate teoste kasutamiseks keeleressurssides esitatakse lisaks litsentsipõhisele meetodile kaks teoste vaba kasutamise viisi, tsiteerimine ja nn teadustöö erand, koos vastavate täpsemate juhistega. Lisaks kirjeldatakse täiendavaid tingimusi, mis puudutavad suulist ja eriti spontaanses olukorras salvestatud kõnet, varem avaldamata teoseid, tuletatud teoste loomist ja keeleressursside avalikustamist. DOI: http://dx.doi.org/10.5128/ERYa9.20

This paper combines the communicative model of translation with performative linguistics to arrive at a translation model that is meant to proactively shape the attitudes of future translators. Central to this model is the claim that the translator, like any communicator, has a communicative intent that gets expressed in the target text. This is contrasted with machine translation, which is concerned with finding equivalents to translation units without actually having anything to say in the target language. The paper concludes by indicating a way of building a translation evaluation system on the proposed model., Dans cet article, je combine le modèle communicatif de traduction avec la linguistique performative pour en arriver à un modèle de traduction qui entend façonner pro-activement les attitudes des futurs traducteurs. L’idée autour de laquelle tourne ce modèle est que le traducteur, à l’instar de tout communicateur, a une intention communicative qui trouve son expression dans le texte cible. Il se situe ainsi à l’opposé de la traduction mécanique, dont l’objectif est de trouver des équivalents à des unités de traduction sans avoir en fait rien à dire dans la langue cible. Cet article se termine en indiquant une manière de construire pour les traductions un système d’évaluation fondé sur le modèle précédemment proposé.

Chatbots have become a part of day-to-day life, with their use increasing in tandem with the expansion of our digital society. As the professional literature makes clear by defining a chatbot as a computer system that acts as an interface between a user and a computer program by using oral or written language as the primary means of communication, it is important for a chatbot to understand what its user wants. Therefore, language technology is of key importance in the creation of these systems. The article focuses on chatbot-related copyright issues, with particular emphasis placed on copyrighted material used in the creation of chatbots. The first half of the article is devoted to explaining the technological character of a chatbot, and the authors’ focus in the second part is on copyright. The focus is primarily on Estonian law, although European Union law, which contributes to the Estonian legal space, is covered also. Behind this emphasis is the fact that the development of Estonian language-related technology takes place on the basis of Estonian law.