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Promoting Fairness of the Music Ecosystem in a Platform-Dominated and Post-Pandemic Europe

Periodic Reporting for period 1 - Fair MusE (Promoting Fairness of the Music Ecosystem in a Platform-Dominated and Post-Pandemic Europe)

Reporting period: 2023-03-01 to 2024-02-29

Fair MusE, a 3-year project led by Católica Global School of Law and the Research for the Future of Law at Universidade Católica Portuguesa, will provide law & technology tools and practical resources for creators, companies, and other professionals to better understand the music industry and to take advantage of its continuous growth.

Fair MusE aims to provide European and national policymakers with policy recommendations and practical solutions for a more transparent ecosystem where music creators and professional industry partners can thrive, having a clearer view of how a data-driven economy is changing the music sector, commercially and legally.

In the second phase of Fair MusE, concrete and implemented results will include accessible, innovative, and future-proof solutions: (i) a data-sharing model enhancing the level of transparency in the European music copyright infrastructure; (ii) a Music Data Dashboard providing statistical insights on the economic value of Europe’s music sector; (iii) a digital toolkit helping to rank streaming services and social media platforms according to their fairness; and (iv) a White Paper with general policy recommendations for EU and national lawmakers.

Fair MusE will provide a timely response to the increased dominance of the biggest online music platforms and their algorithms, highlighting how the music sector can become more competitive, fair, and sustainable in Europe.

The project's consortium includes academics and industry experts who belong to four research hubs focusing – respectively - on political, legal, economic, and data-driven aspects of the music sector.
In the first year, the project achieved significant progress towards its objectives.

We focused heavily on analysing how EU law impacts the music industry, particularly the online services. Through tailored questionnaires and interviews, we gained insights into music creators' rights under EU law, paying close attention to copyright, contract law, platform regulation and competition law issues.

Another crucial aspect of the project involved delving into the supply side of the music industry and conducting an in-depth, interdisciplinary analysis of the notion of ‘fairness’. By actively engaging with industry professionals and stakeholders, we gained valuable insights into this concept within the digital music market.

To examine music streaming and fairness, we took a combined quantitative and qualitative approach, which involved conducting literature reviews and setting up infrastructure for data collection and analysis. We have established the groundwork for communication initiatives, beginning with crafting our brand identity, including our logo and visual representation. We've also launched various project channels such as our website and social media platforms, fostering the growth of our community through daily engagement and targeted efforts based on the preliminary stakeholder mapping.
As contemplated in Fair MusE’s original research proposal, the project incorporates four research hubs whose results are expected to go beyond the state of the art in each discipline:

1. Politics.
Fair MusE researchers are performing an analysis to understand the origin, nature, breadth, and degree of policy changes towards the governance of online platforms in Europe and the implications for the platform music ecosystem. This unprecedented policy analysis is enabling the consortium to (i) produce new knowledge on the COVID-19-enhanced impact of content platformisation on music production and dissemination and (ii) propose solutions with a clear fairness uptake potential.

2. Law.
Fair MusE researchers are currently developing: (i) a cross-country analysis of the impact of new copyright and contract law provisions and of EU competition law and regulation (including recently enacted or upcoming legislation such as the EU Artificial Intelligence Act and the EU Data Act) on online music platforms; and (ii) a Key Exploitable Result consisting of a law-data-and-technology concept and model agreement (‘Music Copyright Infrastructure’) built on the grounds of co-creation with Verifi Media and tested together with SIAE and other industry stakeholders of the consortium’s Advisory Board.

3. Economics and Business.
Fair MusE is contributing to the literature by integrating the latest advancements in its analysis of Value Networks, of music professionals’ perspectives and of innovative business models. Furthermore, Fair MusE’s analysis of the economics and business of the music industry considers the role played by data, since music streaming services and video-sharing platforms rely on curation practices and recommender systems to create value in music ecosystems. Such an ongoing analysis allows the researchers of Fair MusE to address the notion of fairness from an economic perspective, notably in its analysis of Value Networks. This is important because, while there is an increasing policy interest to ensure that music streaming platforms are fair, there is a research gap regarding the industrial and music professionals’ perspectives on fairness in the music platform market.

4. Computer and Data Science.
By analysing (secret) algorithmic strategies and business models, Fair MusE is producing new knowledge on the way platforms are affecting music diversity across the consortium members’ countries. Fair MusE has launched a campaign to recruit +1000 real users from the EU consortium countries to donate their playlist data. We will compare the patterns in the personal playlists against one another and with playlists from ten broadcast radio channels from each consortium country. In addition, we expect qualitative in-depth interviews on music habits, perception of bias, diversity, and serendipity with 100 users to add a qualitative dimension to the interpretation of the playlist data. An important contribution here is the development of fairness indicators based on the analysis of the data collected for online platforms’ algorithmic systems.
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