A key focus of this project is the elimination of gender-specific biases in historical datasets used by AI. Since AI models heavily rely on historical data, the project examines the consequences of using AI to predict future societal changes, raising ethical questions, and exploring how AI can complement, rewrite, and reinterpret data archives. It proposes filling historical gaps with AI-generated "historical images."
AI technologies, especially image generation models, can rewrite history and enhance our understanding of the past while addressing potential gaps. This deliberate distortion of large datasets can influence future AI decisions. The project critiques distortions in historiography driven by political interests, personal preferences, one-sided narratives, and the marginalization of people and events. FLINTA* (1) individuals have historically been excluded from official records, with their contributions often overlooked.
The project creates a constantly growing fictional image archive of history, reinterpreting the past with inclusivity and diversity. This collection, which can be data mined, is spread across digital platforms to inform and train future AI models, either actively or passively.
FLINTA* is a German abbreviation that stands for "Frauen, Lesben, Intergeschlechtliche, nichtbinäre, trans und agender Personen", meaning women/females, lesbians, intersex, non-binary, trans and agender people. The asterisk represents all non-binary gender identities.
A key focus of this project is the elimination of gender-specific biases in historical datasets used by AI. Since AI models heavily rely on historical data, the project examines the consequences of using AI to predict future societal changes, raising ethical questions, and exploring how AI can complement, rewrite, and reinterpret data archives. It proposes filling historical gaps with AI-generated "historical images."
AI technologies, especially image generation models, can rewrite history and enhance our understanding of the past while addressing potential gaps. This deliberate distortion of large datasets can influence future AI decisions. The project critiques distortions in historiography driven by political interests, personal preferences, one-sided narratives, and the marginalization of people and events. FLINTA* (1) individuals have historically been excluded from official records, with their contributions often overlooked.
The project creates a constantly growing fictional image archive of history, reinterpreting the past with inclusivity and diversity. This collection, which can be data mined, is spread across digital platforms to inform and train future AI models, either actively or passively.
FLINTA* is a German abbreviation that stands for "Frauen, Lesben, Intergeschlechtliche, nichtbinäre, trans und agender Personen", meaning women/females, lesbians, intersex, non-binary, trans and agender people. The asterisk represents all non-binary gender identities.
www.claudialarcher.com/work/theartofhistoricalreinterpretation
Claudia Larcher
VALIE EXPORT Center
With support from: VALIE EXPORT Scholarship for artists and artistic researchers
Claudia Larcher (AT) is an artist, filmmaker, and AI researcher. Her work spans video animation, collage, photography, and installation, with a focus on the impacts and uses of artificial intelligence. Together with Eva Fischer, she explores Feminine AI, integrating gender perspectives in AI development to promote inclusivity and diversity. Larcher has exhibited globally, including at Anthology Film Archives NYC, Calouste Gulbenkian Foundation Lisbon, Centre Pompidou Paris, Gray Area Festival San Francisco, Manifesta 13, and Tokyo Wonder Site. She has received numerous prizes, including the Kunsthalle Wien Prize (2008), the Outstanding Artist Award of the Federal Chancellery (2016), and the Austrian Art Award (2023). Currently, she is a resident of the ARTTEC program at the Austrian Institute of Technology.
Claudia Larcher (AT) is an artist, filmmaker, and AI researcher. Her work spans video animation, collage, photography, and installation, with a focus on the impacts and uses of artificial intelligence. Together with Eva Fischer, she explores Feminine AI, integrating gender perspectives in AI development to promote inclusivity and diversity. Larcher has exhibited globally, including at Anthology Film Archives NYC, Calouste Gulbenkian Foundation Lisbon, Centre Pompidou Paris, Gray Area Festival San Francisco, Manifesta 13, and Tokyo Wonder Site. She has received numerous prizes, including the Kunsthalle Wien Prize (2008), the Outstanding Artist Award of the Federal Chancellery (2016), and the Austrian Art Award (2023). Currently, she is a resident of the ARTTEC program at the Austrian Institute of Technology.
AI and the Art of Historical Reinterpretation – Filling Gender Bias Gap is a groundbreaking project aimed at eliminating gender-specific biases in historical datasets used by AI. Recognizing the heavy reliance of AI models on historical data, the project critically examines the ethical implications of using AI to predict societal changes and proposes innovative methods to complement, rewrite, and reinterpret historical data. By employing AI-generated "historical images," the project seeks to fill gaps in historical records and provide a more inclusive understanding of the past.
The project highlights the exclusion of LGBTQ+ individuals from official historical narratives, bringing their overlooked contributions to the forefront. Through meticulous examination of archives and historical texts, the project has created a fictional image archive that reinterprets history with a focus on inclusivity and diversity. Until now, the project has generated a dataset of over 140 images, with 80 specifically addressing gender biases in art history.
AI and the Art of Historical Reinterpretation exemplifies the award's vision by addressing social, cultural, and humanitarian issues through innovative use of technology. This project stands as a powerful example of how AI can be harnessed to empower marginalized groups and reshape our understanding of history. The jury was impressed by the project's commitment to diversity, inclusion, and ethical considerations, as it depicts a future that celebrates digital humanism and inclusivity.
AI and the Art of Historical Reinterpretation – Filling Gender Bias Gap is a groundbreaking project aimed at eliminating gender-specific biases in historical datasets used by AI. Recognizing the heavy reliance of AI models on historical data, the project critically examines the ethical implications of using AI to predict societal changes and proposes innovative methods to complement, rewrite, and reinterpret historical data. By employing AI-generated "historical images," the project seeks to fill gaps in historical records and provide a more inclusive understanding of the past.
The project highlights the exclusion of LGBTQ+ individuals from official historical narratives, bringing their overlooked contributions to the forefront. Through meticulous examination of archives and historical texts, the project has created a fictional image archive that reinterprets history with a focus on inclusivity and diversity. Until now, the project has generated a dataset of over 140 images, with 80 specifically addressing gender biases in art history.
AI and the Art of Historical Reinterpretation exemplifies the award's vision by addressing social, cultural, and humanitarian issues through innovative use of technology. This project stands as a powerful example of how AI can be harnessed to empower marginalized groups and reshape our understanding of history. The jury was impressed by the project's commitment to diversity, inclusion, and ethical considerations, as it depicts a future that celebrates digital humanism and inclusivity.