BRAID Fellowship: Responsible AI in Cultural Heritage
Defining Responsible AI in cultural heritage communities
What is 'Responsible AI'? This AHRC funded Bridging Responsible AI Divides (BRAID) Fellowship, led by Dr Anna-Maria Sichani in partnership with the National Archives and the Alan Turing Institute, is helping to develop and embed a comprehensive, digital skills training provision for responsible AI for the cultural heritage and research community to empower the informed, responsible and ethical use of AI.
BRAID Fellowship
Led by Dr Anna-Maria Sichani
Project Content & Production
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Module and Information Design / Visualisation
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Project Logo, Branding & ID
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Presentation Deck and Content Design
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Promotional & Event Collateral
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Research Poster
Presentation Decks
Static and animated versions
(for live presentations)
Digital skills training provision for the cultural heritage community as an infrastructural, community-driven investment.
Such training provision, by the community and for the community, will also ensure scalability and sustainability of current and future AHRC strategic funding investment in computationally driven innovation infrastructure in cultural heritage and Arts and Humanities.
Training is not a one-time event but an ongoing journey. As AI strategies evolve and new tools emerge, training in responsible AI is an investment that consistently pays dividends in the form of improved quality, and greater, responsible innovation.
'Training as infrastructure'
Module Information Design:
‘AI Technical Primer’
What is AI?
A brief history of AI
Data - driven AI
Machine Learning
Deep Learning
Generative AI
Foundational Models
Large Language Models
Computer Vision
Module Information Design:
‘Responsible AI in action’
Responsible Infrastructure
Responsible Data
Responsible Models
Development
Documentation
Access & Availability
Responsible Systems
Usage
Access
Module Information Design:
‘AI in Cultural Heritage’
AI for cultural heritage and collections management, use and research
AI for visitor experience
AI for general operations and management (HR, etc)
AI as a tool and AI as a method
Case studies:
Appraisal and Selection
Metadata Generation
Archival Description
Access- OCR- HTR
Digital Preservation
Visibility and Engagement
Module Information Design:
‘Openness & AI in Cultural Heritage’
Open-source AI
Public AI
Commons-based AI governance frameworks
Open heritage data
AI transparency vs 'open-washing'
The Spectrum of Openness in AI
Module Information Design:
‘Legal concerns in AI & Cultural Heritage’
Open cultural heritage data:
Cultural heritage data and copyright
Cultural heritage data and the public domain
Availability and reuse:
AI and Cultural Heritage - Legal Considerations under UK Law
EU AI Act and Cultural Heritage
TDM Exception in a Nutshell
AI Transparency
