About the AI & Media Lab
The Dutch media sector is always moving in sync with the digital transition. Whereas prior innovations drastically shifted traditional media organisations’ working methods to include the internet, mobile phones and social media, the media sector now faces the challenge of effectively, responsibly and meaningfully developing and implementing artificial intelligence (AI) and data science. This concerns the full scope of the media field; from methods for complex data analyses to technology that contributes to public engagement. This makes the media sector a hotbed of experimentation for the cultural sector and creative industry.
Human-centred AI development
The AI & Media Lab is a collaboration between Utrecht ľ¹Ï¸£ÀûÓ°ÊÓ, ľ¹Ï¸£ÀûÓ°ÊÓ of Applied Sciences Utrecht (Hogeschool Utrecht), and a varied network of partners from media, digital culture, and creative industries. The lab’s objective is to contribute to the digital transition at media, digital culture, and creative organizations by developing new knowledge, applications, and methods in the field of AI and data science. Human-centered values and user-centered development are core to our values and identity. Within a broader focus, the lab is also an .
Transdisciplinary cooperation
As part of the collaboration, multiple research groups are involved including Multimedia, Human-Centered Computing and Social & Affective Computing at Utrecht ľ¹Ï¸£ÀûÓ°ÊÓ and the professorships Artificial Intelligence, Human Experience & Media Design and Kwaliteitsjournalistiek in Digitale Transitie [Quality Journalism in Digital Transition] at the ľ¹Ï¸£ÀûÓ°ÊÓ of Applied Sciences. Alongside academics, we work with professionals from the media, digital culture, and creative industries to achieve the intended goals through transdisciplinary collaboration including fundamental and applied research as well as practical application. Beyond this, we commonly involve students from various disciplines and levels of education in research and contribute to a human capital agenda that can also be useful for organizations in a wide range of sectors.
Focus and Activities
The media, digital culture, and creative industries face challenges through AI including how to effectively, responsibly, and meaningfully develop and implement AI and data science. This concerns a range of applications from methods for complex data analyses to technology that contributes to public engagement. As a knowledge ecosystem, the AI & Media Lab contributes to a research and education programme with and for our partners to co-create knowledge, recommendations, and applications. We conduct fundamental and applied research, organize workshops and seminars, and work together to solve urgent issues in the media, digital culture, and creative industries.
Themes
A number of the research themes staff at AI & Media Lab are working on include:
Games & Esports
- AI applications that support the design and development of entertainment games and applied/serious games.
- AI applications that provide insights into player characteristics, esports teams, and player-game interactions.
Journalism
- AI applications that support journalists in their practice.
- AI applications that critically assess online media.
Combating Harm in Online Environments
- AI applications that counter polarization, misinformation, hate speech, and toxicity.
- AI applications that support individuals exposed to harmful behaviours.
- AI applications that support moderation in online communities.
Production
- AI applications for production processes such as personalised content access, automated archiving and access for the benefit of news services, automated production of news items, background reports and promos
- AI applications for journalists and other (media) professionals, such as research tools that help collect prejudice-free, valid information and tell stories that provide insight into qualitative and quantitative performance as well as the substantive and instrumental needs of users/audience groups
Accessibility
- AI applications for increasing the safety of and confidence in online interactions such as identifying fake news, filtering and other forms of online gatekeeping for media professionals
- AI applications for multimodal access to media collections based on textual, visual and audio characteristics.
User interaction
- Human-AI interaction: which information should AI help generate and how? How can (media) professionals and users modify the ways algorithms work as well as their output? How can confidence in and acceptance of AI among professionals be improved?
- Speech interaction and conversational agents (chat bots)
- AI for personalised interactions that result in improved commitment and are perceived to be more seamless.