APA news agency wins the EANA Award 2023
APA, the Austrian national news agency, is the winner of the EANA "Maxim Minchev" Award for News Agency Quality in 2023, following the deliberation of the jury formed by members of the EANA Board Elmir Huremovic, Stefano de Alessandri, Fabrice Fries and Alexandru Giboi. Clemens Pig, EANA President and CEO of APA, did not participate in the decision making process. According to the Board, the main criteria followed when evaluating each submission were Innovation, Applicability, Turnover vs Costs and Coverage.
TASR, PA Media, LUSA, Anadolu Ajansi, ANA-MPA and NTB also submitted very interesting proposals for the EANA Award.
According to the presentation submitted by APA, "The #APA-Playbook Trusted AI incorporates all kinds of factors and activities a news agency can play in this field, among them guidelines and quality rules, verified and validated data, the selection of basic technologies, mandatory labelling of AI content, transparency, product security, traceability, technology agnosticism as well as a safe space for information processing. With services in Visual AI (Face-, logo- and object recognition), Text AI (Content generation, automation and classification) and Speech AI (Speech2Text, Speaker recognition), APA caters the needs of both its traditional media clients and non-media clients from the enterprise and institutional sectors with state-of-the-art AI solutions."
APA CEO Clemens Pig expressed his delight about the award: “The EANA Award is a marvellous confirmation of our strategy and our day-to-day work. I would like to sincerely thank all of our colleagues at APA, particularly the members of AI Task Force, for their commitment and the results. In a digital interpretation of our basic mission (trusted content), we are evolving into a collaborative platform closely linked to media production systems (trusted AI). A concrete vision is, for example, the development of an AI media hub as a shared space for knowledge for media enterprises, in which artificial intelligence can be trained and deployed on the basis of fact-based and clean information.”