Experiential AI
| Autor: | Ewa Luger, Frank Broz, Ruth Aylett, Jane Hillston, Drew Hemment, Michael Rovatsos, Dave Murray-Rust, Vaishak Belle |
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| Rok vydání: | 2019 |
| Předmět: |
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Computer science media_common.quotation_subject 05 social sciences 050801 communication & media studies 02 engineering and technology General Medicine Transparency (behavior) Experiential learning GeneralLiterature_MISCELLANEOUS Field (computer science) Comprehension 0508 media and communications Human–computer interaction 020204 information systems 0202 electrical engineering electronic engineering information engineering media_common Ai systems |
| Zdroj: | AI Matters. 5:25-31 |
| ISSN: | 2372-3483 |
| Popis: | Experiential AI is proposed as a new research agenda in which artists and scientists come together to dispel the mystery of algorithms and make their mechanisms vividly apparent. It addresses the challenge of finding novel ways of opening up the field of artificial intelligence to greater transparency and collaboration between human and machine. The hypothesis is that art can mediate between computer code and human comprehension to overcome the limitations of explanations in and for AI systems. Artists can make the boundaries of systems visible and offer novel ways to make the reasoning of AI transparent and decipherable. Beyond this, artistic practice can explore new configurations of humans and algorithms, mapping the terrain of inter-agencies between people and machines. This helps to viscerally understand the complex causal chains in environments with AI components, including questions about what data to collect or who to collect it about, how the algorithms are chosen, commissioned and configured or how humans are conditioned by their participation in algorithmic processes. |
| Databáze: | OpenAIRE |
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