Zobrazeno 1 - 10
of 551
pro vyhledávání: '"Rismani A"'
Autor:
Rismani, Shalaleh, Shelby, Renee, Smart, Andrew, Santos, Renelito Delos, Moon, AJung, Rostamzadeh, Negar
Identifying potential social and ethical risks in emerging machine learning (ML) models and their applications remains challenging. In this work, we applied two well-established safety engineering frameworks (FMEA, STPA) to a case study involving tex
Externí odkaz:
http://arxiv.org/abs/2307.10312
Autor:
Chan, Alan, Salganik, Rebecca, Markelius, Alva, Pang, Chris, Rajkumar, Nitarshan, Krasheninnikov, Dmitrii, Langosco, Lauro, He, Zhonghao, Duan, Yawen, Carroll, Micah, Lin, Michelle, Mayhew, Alex, Collins, Katherine, Molamohammadi, Maryam, Burden, John, Zhao, Wanru, Rismani, Shalaleh, Voudouris, Konstantinos, Bhatt, Umang, Weller, Adrian, Krueger, David, Maharaj, Tegan
Research in Fairness, Accountability, Transparency, and Ethics (FATE) has established many sources and forms of algorithmic harm, in domains as diverse as health care, finance, policing, and recommendations. Much work remains to be done to mitigate t
Externí odkaz:
http://arxiv.org/abs/2302.10329
Autor:
Jatho III, Edgar W., Mailloux, Logan O., Rismani, Shalaleh, Williams, Eugene D., Kroll, Joshua A.
Governments, industry, and academia have undertaken efforts to identify and mitigate harms in ML-driven systems, with a particular focus on social and ethical risks of ML components in complex sociotechnical systems. However, existing approaches are
Externí odkaz:
http://arxiv.org/abs/2211.04602
Autor:
Shelby, Renee, Rismani, Shalaleh, Henne, Kathryn, Moon, AJung, Rostamzadeh, Negar, Nicholas, Paul, Yilla, N'Mah, Gallegos, Jess, Smart, Andrew, Garcia, Emilio, Virk, Gurleen
Understanding the landscape of potential harms from algorithmic systems enables practitioners to better anticipate consequences of the systems they build. It also supports the prospect of incorporating controls to help minimize harms that emerge from
Externí odkaz:
http://arxiv.org/abs/2210.05791
Autor:
Rismani, Shalaleh, Shelby, Renee, Smart, Andrew, Jatho, Edgar, Kroll, Joshua, Moon, AJung, Rostamzadeh, Negar
Inappropriate design and deployment of machine learning (ML) systems leads to negative downstream social and ethical impact -- described here as social and ethical risks -- for users, society and the environment. Despite the growing need to regulate
Externí odkaz:
http://arxiv.org/abs/2210.03535
Autor:
Parmida Malekzadeh, Seyed Hossein Hosseini, Mahsa Shahbakhsh, Parviz Shayan, Mohammad Zibaei, Shahram Jamshidi, Elham Rismani, Abdorreza Naser Moghadasi, Mohammad Akrami, Fateme Jalousian
Publikováno v:
Journal of Zoonotic Diseases, Vol 8, Iss 1, Pp 422-435 (2024)
The protein C-type lectin is secreted by the secondary-stage larve of Toxocara canis (T. canis). Its antigenic characteristics have been the subject of research. The recombinant pET-32a (+) plasmid containing the 660 bp sequence of T. canis C-type
Externí odkaz:
https://doaj.org/article/1b4b1ab8ce924abe9d5ad42093b9bdd0
Autor:
Rismani, Shalaleh, Moon, AJung
With the growing need to regulate AI systems across a wide variety of application domains, a new set of occupations has emerged in the industry. The so-called responsible AI practitioners or AI ethicists are generally tasked with interpreting and ope
Externí odkaz:
http://arxiv.org/abs/2205.03946
Publikováno v:
In Archives of Biochemistry and Biophysics September 2024 759
Autor:
Nasim Rismani, Hossein Afzalimehr, Seyed-Amin Asghari-Pari, Mohammad Nazari-Sharabian, Moses Karakouzian
Publikováno v:
Water, Vol 16, Iss 15, p 2162 (2024)
River meanders and channel curvatures play a significant role in sediment motion, making it crucial to predict incipient sediment motion for effective river restoration projects. This study utilized an artificial intelligence method, multiple linear
Externí odkaz:
https://doaj.org/article/4fa20015900b48aa8456b65051256141
Autor:
Zahra Rashno, Elham Rismani, Jahan B. Ghasemi, Mehdi Mansouri, Mohammad Shabani, Ali Afgar, Shahriar Dabiri, Farahnaz Rezaei Makhouri, Abbas Hatami, Majid Fasihi Harandi
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-18 (2023)
Abstract Over-expression of K+ channels has been reported in human cancers and is associated with the poor prognosis of several malignancies. EAG1, a particular potassium ion channel, is widely expressed in the brain but poorly expressed in other nor
Externí odkaz:
https://doaj.org/article/abcba3457e0c40dd9e74d7790ec2441c