Publication: May 2020  
Author: Georg Rehm

Key findings

This briefing paper takes a look at the use of AI technologies in the wider audiovisual sector. A survey with ten questions concerning the most important aspects was circulated to 85 contacts at 73 organisations. A total of 22 responses were received. The main findings are as follows:

  1. Almost all respondents report broad use of AI technologies, especially for automated indexing, improved content accessibility as well as localisation. AI is used for processing audio or video, language or text data or for knowledge management purposes.
  2. Among the technologies used are ASR, TTS, NLP, NER, MT, summarisation, search and recommender engines, content classification, subtitling, vision and metadata extraction (see Appendix 2: Glossary – Terms and Abbreviations).
  3. AI technologies foreseen for future use are more experimental and include the automated detection of illegal content and deep fakes as well as flexible curation technologies.
  4. There is a big demand for large amounts of training data including labelled, structured and unstructured data, domain-specific training data, acoustic data and data for illegal content.
  5. There is also a need for more language technologies for all European languages, including ASR, TTS, MT, content curation services and metadata extraction as well as Linked Data.
  6. In terms of policies, it is suggested to focus upon an ethical framework regarding the use and misuse of AI that protects human values and fosters cultural and linguistic diversity. It should also protect against the misuse of AI for false news and misinformation.
  7. Regarding opportunities, many respondents suggest concentrating on the AI-based production of high quality content. In addition, AI allows unlimited localisation and makes it possible for a fragmented and culturally diverse ecosystem to survive in a world dominated by capital-intensive ventures based in the US.
  8. The consumption of intentionally created false or manipulative content is seen as an imminent danger. It is stressed that, as video is quickly becoming our main means of communication, there is a threat that relates to the use of AI for misinformation and manipulation, which could have an impact on the foundations of our democratic society.
  9. The awareness of the European AI tool market varies. Some perceive the market to be non-existent, others perceive it to be highly fragmented. Due to the dominance of non-European technology enterprises, European companies should be supported more.
  10. Collaboration at the European level is seen as essential because individual players have limitations and difficulties in using AI technologies. Europe’s multilingualism is seen as crucial: to guarantee inclusiveness and accessibility, tools need to be made available, especially for under-resourced languages.

The briefing paper concludes with the following four recommendations:

  1. Support long-term European platform initiatives.
  2. Reinforce the European AI and Language Technology providers landscape.
  3. Support the European Digital Public Space Vision (European Media Platform).
  4. Conduct an in-depth study of the sector.
Introduction: AI in the Audiovisual sector

This briefing paper is a contribution towards the identification of current activities, important priority topics and crucial needs in the area of Artificial Intelligence (AI) within the European audiovisual sector. The paper highlights the main topics and makes a number of long-term policy recommendations. Specifically, the paper concentrates on the impact and relationship of AI-based technologies with regard to the creation, production and consumption of audiovisual and multimedia content. It contributes to the identification of AI-driven use cases in the sector and characterises important aspects of the market of tool providers. It emphasises important components of the AI-driven value chain for audiovisual content and touches upon issues raised by the increased use of AI.

AI in the Audiovisual Sector: Potential scope

While AI itself is a broad and diverse field of research whose origins date back to the 1950s, the term is currently used almost exclusively for technologies developed with different forms of Machine Learning (ML), especially neural network-based approaches, often referred to as Deep Learning (DL). It is this powerful family of neural technologies especially that has, in recent years, contributed to breakthroughs in many applications, from robotics, to image and audio processing and to automated language analysis. As a consequence, the intersection between AI-based technologies on the one side and the audiovisual sector (including film, television, video games and multimedia) on the other, is extensive. Among many other fields of application, this could refer to: AI for camera technologies (picture stabilisation etc.); software for manipulating, editing, processing, enriching textual content, images, movies or audio files; Augmented Reality (AR), i.e., adding virtual images to real ones, anchoring artificial images to objects in a movie; deep fake detection: analysing movies, audio or text files to determine if they have been intentionally manipulated; AI-based television programme planning, i.e., user model-based dynamic programming; recommender systems for media repositories; (semi-)automated localisation and translation of content (video, audio, text) into other languages; autonomous non-player characters in video games; automated transcription and subtitling of video content; enhanced movie production using AI technologies. These are only a few selected examples of where AI and media meet, many more could easily be added.

AI in the Audiovisual sector: Scope of this paper

This briefing paper is based on a rather broad interpretation of “audiovisual sector”, which includes not only the areas of audio and video but also the area of textual content, which is an inherent additional modality in nearly all audiovisual use cases, especially with regard to the (ubiquitous) multimedia applications in the World Wide Web and mobile apps, which combine text, video and audio seamlessly. As a consequence, and also because these different modalities (audio, video, text) are converging more and more, in addition to the areas and domains of film, television and games, we also include online publishing, content curation (including localisation) and multimedia. With regard to AI-based technologies, the key intersection of all of these different areas and fields is language itself, which is an inherent part of video content, audio content and textual content and for which various AI-driven technologies exist, which are usually referred to as Language Technologies (LT) or Language-centric AI. This area is divided between the analysis or generation of (a) written, i.e., textual language (Natural Language Processing, NLP) or (b) spoken language (Speech Technologies).


This briefing paper is primarily informed by a specifically prepared survey (cf. appendix). The survey contains ten questions (see below), tailored to the specifications set out in the terms of reference. Its main goal was exploratory, i.e. to map the main topics and trends in terms of the use of AI in the audiovisual sector. Accordingly, and to enable the respondents to answer in a flexible way, the survey consisted almost exclusively of free text fields (in contrast to multiple choice questions) with length limits. The survey was circulated to 85 contacts at 73 organisations, all of which are stakeholders of the wider audiovisual sector. The contacts were carefully selected from the author’s own list of contacts (approx. two thirds of the contacts) and representatives from important stakeholders identified through desk research (approx. one third of the contacts). The survey was circulated via email on 6 March 2020 with a response deadline of 11 March 2020 (three workdays). The following stakeholders were included: public and private broadcasters, film business, video game developers, publishers and publishing houses, telecom providers, technology service providers, umbrella associations, research and academia.

Responses: General Overview

Despite the very short deadline and the rapidly developing Covid-19 pandemic, a total of 22 responses were received. This unexpectedly high response rate demonstrates the commitment of the respondents. Responses were received from Germany (11), France (3), Belgium (2), Latvia (2), Greece, Spain, The Netherlands and the UK (1 each). Representatives of the following stakeholders responded: technology or service provider (8), public broadcaster (3), public broadcast archive (2), research (2), consultancy firm, cultural organisation (philanthropy), film business, news agency, private investment network, public broadcast research institution, publishing association (1 each). The respondents have the following job titles/profiles: Director, Deputy Director, Head of Department, Programme Manager (7), CEO (5), Head of Research (3), AI/ML Lead (3), Head of Innovation (2), Other (2).

List of Questions
  • Current use of AI: Do you currently use AI-based technologies in your organisation? Yes (in production use), Yes (experimental use), No, Prefer not to answer
    If yes: In which areas do you apply AI-based technologies? If you use AI in several different areas, please feel free to focus on those areas that you perceive to be the most important ones.
  • Future use of AI: In addition to your answer in Q1, do you have plans to use AI-based technologies in your organisation in the next 24 months?
  • Yes (in production use), Yes (experimental use), No, Prefer not to answer
    If yes: Please list the planned areas of application of AI-based technologies. If you plan to use AI in several areas, please feel free to focus on those areas that you perceive to be the most important ones.
  • Needs, demands and requirements: What are your organisation’s concrete needs, demands and requirements in terms of AI-based technologies (and in which areas)?
  • EU policies: Do you see a need for establishing EU policies (including regulation and recommendations) for the use of AI-based technologies in the audiovisual sector and why?
  • Opportunities of AI in the content life-cycle: AI-based technologies can be used for the creation, production or consumption of audiovisual content. In which of these three phases of the content life-cycle do you see the biggest opportunities for AI-based technologies and why?
  • Dangers of AI in the content life-cycle: AI-based technologies can be used for the creation, production or consumption of audiovisual content. In which of these three phases of the content life-cycle do you see the biggest danger of AI-based technologies and why?
  • European AI tool market: Please provide a short description of how you assess the market of European AI tool providers for the audiovisual sector (for example, in terms of market access, market size, market diversity, pricing, competitiveness, market dominance etc.).
  • Opportunities of AI (in general): Independent of your organisation, in which areas do you see the biggest potential or set of opportunities (incl. technical, social, ethical, economic, legal aspects) for AI-based technologies in the audiovisual sector?
  • Dangers of AI (in general): In which areas do you see the biggest dangers or threats (incl. technical, social, ethical, economic, legal) of AI-based technologies in the audiovisual sector?
  • European collaboration: In which broader areas regarding the use of AI-based technologies in the audiovisual sector do you see a need for increased European collaboration or coordination?

Link to the full study

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1 Comment

Anyuci shd · September 21, 2020 at 6:12 pm

AI use of for audiovisual content. Silicon valey has already developed an AI based software which enables searches in huge amount of video digital content. In this list it is missed the possible use of AI in revolutionising film arhive work. Please, consider it, and also and follow what happens in other parts.

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