Zobrazeno 1 - 10
of 314
pro vyhledávání: '"A, Prunkl"'
Autor:
Gala, Dalia, Phillips-Brown, Milo, Goel, Naman, Prunkl, Carinal, Jubete, Laura Alvarez, corcoran, medb, Eitel-Porter, Ray
Machine learning requires defining one's target variable for predictions or decisions, a process that can have profound implications on fairness: biases are often encoded in target variable definition itself, before any data collection or training. W
Externí odkaz:
http://arxiv.org/abs/2403.06031
Most group fairness notions detect unethical biases by computing statistical parity metrics on a model's output. However, this approach suffers from several shortcomings, such as philosophical disagreement, mutual incompatibility, and lack of interpr
Externí odkaz:
http://arxiv.org/abs/2307.15466
Autor:
Prunkl, Carina, author
Publikováno v:
AI Morality, 2024.
Externí odkaz:
https://doi.org/10.1093/oso/9780198876434.003.0013
AI systems can create, propagate, support, and automate bias in decision-making processes. To mitigate biased decisions, we both need to understand the origin of the bias and define what it means for an algorithm to make fair decisions. Most group fa
Externí odkaz:
http://arxiv.org/abs/2208.12786
Autor:
Lavin, Alexander, Krakauer, David, Zenil, Hector, Gottschlich, Justin, Mattson, Tim, Brehmer, Johann, Anandkumar, Anima, Choudry, Sanjay, Rocki, Kamil, Baydin, Atılım Güneş, Prunkl, Carina, Paige, Brooks, Isayev, Olexandr, Peterson, Erik, McMahon, Peter L., Macke, Jakob, Cranmer, Kyle, Zhang, Jiaxin, Wainwright, Haruko, Hanuka, Adi, Veloso, Manuela, Assefa, Samuel, Zheng, Stephan, Pfeffer, Avi
The original "Seven Motifs" set forth a roadmap of essential methods for the field of scientific computing, where a motif is an algorithmic method that captures a pattern of computation and data movement. We present the "Nine Motifs of Simulation Int
Externí odkaz:
http://arxiv.org/abs/2112.03235
Publikováno v:
Nature Machine Intelligence 3.2 (2021): 104-110
Turning principles into practice is one of the most pressing challenges of artificial intelligence (AI) governance. In this article, we reflect on a novel governance initiative by one of the world's largest AI conferences. In 2020, the Conference on
Externí odkaz:
http://arxiv.org/abs/2106.11039
Autor:
Brundage, Miles, Avin, Shahar, Wang, Jasmine, Belfield, Haydn, Krueger, Gretchen, Hadfield, Gillian, Khlaaf, Heidy, Yang, Jingying, Toner, Helen, Fong, Ruth, Maharaj, Tegan, Koh, Pang Wei, Hooker, Sara, Leung, Jade, Trask, Andrew, Bluemke, Emma, Lebensold, Jonathan, O'Keefe, Cullen, Koren, Mark, Ryffel, Théo, Rubinovitz, JB, Besiroglu, Tamay, Carugati, Federica, Clark, Jack, Eckersley, Peter, de Haas, Sarah, Johnson, Maritza, Laurie, Ben, Ingerman, Alex, Krawczuk, Igor, Askell, Amanda, Cammarota, Rosario, Lohn, Andrew, Krueger, David, Stix, Charlotte, Henderson, Peter, Graham, Logan, Prunkl, Carina, Martin, Bianca, Seger, Elizabeth, Zilberman, Noa, hÉigeartaigh, Seán Ó, Kroeger, Frens, Sastry, Girish, Kagan, Rebecca, Weller, Adrian, Tse, Brian, Barnes, Elizabeth, Dafoe, Allan, Scharre, Paul, Herbert-Voss, Ariel, Rasser, Martijn, Sodhani, Shagun, Flynn, Carrick, Gilbert, Thomas Krendl, Dyer, Lisa, Khan, Saif, Bengio, Yoshua, Anderljung, Markus
With the recent wave of progress in artificial intelligence (AI) has come a growing awareness of the large-scale impacts of AI systems, and recognition that existing regulations and norms in industry and academia are insufficient to ensure responsibl
Externí odkaz:
http://arxiv.org/abs/2004.07213
Autor:
Prunkl, Carina, Whittlestone, Jess
One way of carving up the broad "AI ethics and society" research space that has emerged in recent years is to distinguish between "near-term" and "long-term" research. While such ways of breaking down the research space can be useful, we put forward
Externí odkaz:
http://arxiv.org/abs/2001.04335
The comparison of geometrical properties of black holes with classical thermodynamic variables reveals surprising parallels between the laws of black hole mechanics and the laws of thermodynamics. Since Hawking's discovery that black holes when coupl
Externí odkaz:
http://arxiv.org/abs/1903.06276
Autor:
Abigail L. Cochran, Noreen C. McDonald, Lauren Prunkl, Emma Vinella-Brusher, Jueyu Wang, Lindsay Oluyede, Mary Wolfe
Publikováno v:
BMC Public Health, Vol 22, Iss 1, Pp 1-10 (2022)
Abstract Background Transportation problems are known barriers to health care and can result in late arrivals and delayed or missed care. Groups already prone to greater social and economic disadvantage, including low-income individuals and people wi
Externí odkaz:
https://doaj.org/article/9017e1e86bd94fee963be7c2ece20d95