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You searched for subject:(Algorithmic Bias). Showing records 1 – 8 of 8 total matches.

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UCLA

1. Johnson, Gabbrielle Michelle. Cognition and the Structure of Bias.

Degree: Philosophy, 2019, UCLA

 Consider three structurally similar cases of social bias. Mary’s application for graduate school in mathematics is rejected by the traditionalist Mr. T, an evaluator who… (more)

Subjects/Keywords: Philosophy; Psychology; Cognitive psychology; Algorithmic Bias; Computational Theory of Mind; Implicit Bias; Social Bias; Social Cognition; Stereotypes

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Johnson, G. M. (2019). Cognition and the Structure of Bias. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/7hf582vz

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Johnson, Gabbrielle Michelle. “Cognition and the Structure of Bias.” 2019. Thesis, UCLA. Accessed October 30, 2020. http://www.escholarship.org/uc/item/7hf582vz.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Johnson, Gabbrielle Michelle. “Cognition and the Structure of Bias.” 2019. Web. 30 Oct 2020.

Vancouver:

Johnson GM. Cognition and the Structure of Bias. [Internet] [Thesis]. UCLA; 2019. [cited 2020 Oct 30]. Available from: http://www.escholarship.org/uc/item/7hf582vz.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Johnson GM. Cognition and the Structure of Bias. [Thesis]. UCLA; 2019. Available from: http://www.escholarship.org/uc/item/7hf582vz

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Louisville

2. Sun, Wenlong. Studying and handling iterated algorithmic biases in human and machine learning interaction.

Degree: PhD, 2019, University of Louisville

Algorithmic bias consists of biased predictions born from ingesting unchecked information, such as biased samples and biased labels. Furthermore, the interaction between people and… (more)

Subjects/Keywords: algorithmic bias; machine learning; interaction; iterated; Databases and Information Systems; Theory and Algorithms

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Sun, W. (2019). Studying and handling iterated algorithmic biases in human and machine learning interaction. (Doctoral Dissertation). University of Louisville. Retrieved from 10.18297/etd/3241 ; https://ir.library.louisville.edu/etd/3241

Chicago Manual of Style (16th Edition):

Sun, Wenlong. “Studying and handling iterated algorithmic biases in human and machine learning interaction.” 2019. Doctoral Dissertation, University of Louisville. Accessed October 30, 2020. 10.18297/etd/3241 ; https://ir.library.louisville.edu/etd/3241.

MLA Handbook (7th Edition):

Sun, Wenlong. “Studying and handling iterated algorithmic biases in human and machine learning interaction.” 2019. Web. 30 Oct 2020.

Vancouver:

Sun W. Studying and handling iterated algorithmic biases in human and machine learning interaction. [Internet] [Doctoral dissertation]. University of Louisville; 2019. [cited 2020 Oct 30]. Available from: 10.18297/etd/3241 ; https://ir.library.louisville.edu/etd/3241.

Council of Science Editors:

Sun W. Studying and handling iterated algorithmic biases in human and machine learning interaction. [Doctoral Dissertation]. University of Louisville; 2019. Available from: 10.18297/etd/3241 ; https://ir.library.louisville.edu/etd/3241


University of Arkansas

3. Wu, Yongkai. Achieving Causal Fairness in Machine Learning.

Degree: PhD, 2020, University of Arkansas

  Fairness is a social norm and a legal requirement in today's society. Many laws and regulations (e.g., the Equal Credit Opportunity Act of 1974)… (more)

Subjects/Keywords: Algorithmic Bias; Causal Inference; Fairness; Machine Learning; Artificial Intelligence and Robotics; Theory and Algorithms

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Wu, Y. (2020). Achieving Causal Fairness in Machine Learning. (Doctoral Dissertation). University of Arkansas. Retrieved from https://scholarworks.uark.edu/etd/3632

Chicago Manual of Style (16th Edition):

Wu, Yongkai. “Achieving Causal Fairness in Machine Learning.” 2020. Doctoral Dissertation, University of Arkansas. Accessed October 30, 2020. https://scholarworks.uark.edu/etd/3632.

MLA Handbook (7th Edition):

Wu, Yongkai. “Achieving Causal Fairness in Machine Learning.” 2020. Web. 30 Oct 2020.

Vancouver:

Wu Y. Achieving Causal Fairness in Machine Learning. [Internet] [Doctoral dissertation]. University of Arkansas; 2020. [cited 2020 Oct 30]. Available from: https://scholarworks.uark.edu/etd/3632.

Council of Science Editors:

Wu Y. Achieving Causal Fairness in Machine Learning. [Doctoral Dissertation]. University of Arkansas; 2020. Available from: https://scholarworks.uark.edu/etd/3632


Uppsala University

4. Fyrvald, Johanna. Mitigating algorithmic bias in Artificial Intelligence systems.

Degree: Mathematics, 2019, Uppsala University

  Artificial Intelligence (AI) systems are increasingly used in society to make decisions that can have direct implications on human lives; credit risk assessments, employment… (more)

Subjects/Keywords: Artificial Intelligence; AI; algorithmic bias; disruptive technology; Engineering and Technology; Teknik och teknologier

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Fyrvald, J. (2019). Mitigating algorithmic bias in Artificial Intelligence systems. (Thesis). Uppsala University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-388627

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Fyrvald, Johanna. “Mitigating algorithmic bias in Artificial Intelligence systems.” 2019. Thesis, Uppsala University. Accessed October 30, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-388627.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Fyrvald, Johanna. “Mitigating algorithmic bias in Artificial Intelligence systems.” 2019. Web. 30 Oct 2020.

Vancouver:

Fyrvald J. Mitigating algorithmic bias in Artificial Intelligence systems. [Internet] [Thesis]. Uppsala University; 2019. [cited 2020 Oct 30]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-388627.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Fyrvald J. Mitigating algorithmic bias in Artificial Intelligence systems. [Thesis]. Uppsala University; 2019. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-388627

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Delft University of Technology

5. Lazo, C.B. (author). Towards Engineering AI Software for Fairness: A framework to help design fair, accountable and transparent algorithmic decision-making systems.

Degree: 2020, Delft University of Technology

Algorithmic decision-making (ADM) is becoming increasingly prevalent in society, due to the rapid technological developments in Artificial Intelligence. ADM make substantially impactful decisions about people:… (more)

Subjects/Keywords: fairness; discrimination; bias; algorithmic decision-making; machine learning; software engineering; requirements engineering; Design for values; AI ethics

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Lazo, C. B. (. (2020). Towards Engineering AI Software for Fairness: A framework to help design fair, accountable and transparent algorithmic decision-making systems. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:c7dc661e-c3f9-4986-bc54-c903aaddbc68

Chicago Manual of Style (16th Edition):

Lazo, C B (author). “Towards Engineering AI Software for Fairness: A framework to help design fair, accountable and transparent algorithmic decision-making systems.” 2020. Masters Thesis, Delft University of Technology. Accessed October 30, 2020. http://resolver.tudelft.nl/uuid:c7dc661e-c3f9-4986-bc54-c903aaddbc68.

MLA Handbook (7th Edition):

Lazo, C B (author). “Towards Engineering AI Software for Fairness: A framework to help design fair, accountable and transparent algorithmic decision-making systems.” 2020. Web. 30 Oct 2020.

Vancouver:

Lazo CB(. Towards Engineering AI Software for Fairness: A framework to help design fair, accountable and transparent algorithmic decision-making systems. [Internet] [Masters thesis]. Delft University of Technology; 2020. [cited 2020 Oct 30]. Available from: http://resolver.tudelft.nl/uuid:c7dc661e-c3f9-4986-bc54-c903aaddbc68.

Council of Science Editors:

Lazo CB(. Towards Engineering AI Software for Fairness: A framework to help design fair, accountable and transparent algorithmic decision-making systems. [Masters Thesis]. Delft University of Technology; 2020. Available from: http://resolver.tudelft.nl/uuid:c7dc661e-c3f9-4986-bc54-c903aaddbc68


KTH

6. Jansson, Daniel. Operationalizing FAccT : A Case Study at the Swedish Tax Agency.

Degree: Industrial Engineering and Management (ITM), 2020, KTH

Fairness, accountability and transparency (FAccT) in machine learning is an interdisciplinary area that concerns the design, development, deployment and maintenance of ethical AI and ML. Examples… (more)

Subjects/Keywords: Fairness; Accountability; Transparency; Algorithmic accountability; Bias; Framework; Machine learning; Case study; Rättvisa; Ansvarsskyldighet; Transparens; Algoritmisk ansvarsskyldighet; Ramverk; Maskininlärning; Engineering and Technology; Teknik och teknologier

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Jansson, D. (2020). Operationalizing FAccT : A Case Study at the Swedish Tax Agency. (Thesis). KTH. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-276408

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Jansson, Daniel. “Operationalizing FAccT : A Case Study at the Swedish Tax Agency.” 2020. Thesis, KTH. Accessed October 30, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-276408.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Jansson, Daniel. “Operationalizing FAccT : A Case Study at the Swedish Tax Agency.” 2020. Web. 30 Oct 2020.

Vancouver:

Jansson D. Operationalizing FAccT : A Case Study at the Swedish Tax Agency. [Internet] [Thesis]. KTH; 2020. [cited 2020 Oct 30]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-276408.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Jansson D. Operationalizing FAccT : A Case Study at the Swedish Tax Agency. [Thesis]. KTH; 2020. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-276408

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

7. Engman, Clara. Ramverk för att motverka algoritmisk snedvridning.

Degree: Division of Visual Information and Interaction, 2019, Uppsala University

Användningen av artificiell intelligens (AI) har tredubblats på ett år och och anses av vissa vara det viktigaste paradigmskiftet i teknikhistorien. Den rådande AI-kapplöpningen… (more)

Subjects/Keywords: algorithmic bias; artificial intelligence; framework; cognitive bias; automation; algoritmisk snedvridning; artificiell intelligens; ramverk; kognitiv snedvridning; automatisering; Computer Vision and Robotics (Autonomous Systems); Datorseende och robotik (autonoma system)

…Uppkomsten av så kallad algoritmisk snedvridning (algorithmic bias) är en sådan risk som… …snedvridningar Snedvridning, eller bias, berör systematiska missuppfattningar och/eller okunskap… …snedvridningar - såväl mänskliga som algoritmiska. 3.1.1 Konfirmeringssnedvridning - Confirmation Bias… …Attributionssnedvridning - Attribution Bias Attributionssnedvridning beskriver fel som uppstår på grund av… 

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Engman, C. (2019). Ramverk för att motverka algoritmisk snedvridning. (Thesis). Uppsala University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-385348

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Engman, Clara. “Ramverk för att motverka algoritmisk snedvridning.” 2019. Thesis, Uppsala University. Accessed October 30, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-385348.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Engman, Clara. “Ramverk för att motverka algoritmisk snedvridning.” 2019. Web. 30 Oct 2020.

Vancouver:

Engman C. Ramverk för att motverka algoritmisk snedvridning. [Internet] [Thesis]. Uppsala University; 2019. [cited 2020 Oct 30]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-385348.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Engman C. Ramverk för att motverka algoritmisk snedvridning. [Thesis]. Uppsala University; 2019. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-385348

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

8. Lycken, Hanna. Artificiell intelligens och gender bias : En studie av samband mellan artificiell intelligens, gender bias och könsdiskriminering.

Degree: Division of Visual Information and Interaction, 2019, Uppsala University

AI spås få lika stor påverkan på samhället som elektricitet haft och avancemangen inom till exempel maskininlärning och neurala nätverk har tagit AI in… (more)

Subjects/Keywords: algorithmic bias; artificial intelligence; AI-system; automation; cognitive bias; gender analysis; gender bias; gender discrimination; fairness; algoritmisk snedvridning; artificiell intelligens; AI-system; automatisering; genusanalys; könsdiskriminering; kognitiv snedvridning; rättvisa; Computer Vision and Robotics (Autonomous Systems); Datorseende och robotik (autonoma system); Gender Studies; Genusstudier

…fördomar implementeras i teknik kallas algoritmisk snedvridning (algorithmic bias)… …50 6.11 AI som katalysator för debatt kring gender bias… …bias och AI-system 2 ser ut. Studiens andra syfte är att undersöka hur ett företag som… …arbetar med utveckling av AI resonerar kring relationen mellan gender bias och AI. För att… …uppfylla syftet har följande frågeställningar undersökts: § § § Hur kan gender bias eller… 

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Lycken, H. (2019). Artificiell intelligens och gender bias : En studie av samband mellan artificiell intelligens, gender bias och könsdiskriminering. (Thesis). Uppsala University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-398282

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Lycken, Hanna. “Artificiell intelligens och gender bias : En studie av samband mellan artificiell intelligens, gender bias och könsdiskriminering.” 2019. Thesis, Uppsala University. Accessed October 30, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-398282.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Lycken, Hanna. “Artificiell intelligens och gender bias : En studie av samband mellan artificiell intelligens, gender bias och könsdiskriminering.” 2019. Web. 30 Oct 2020.

Vancouver:

Lycken H. Artificiell intelligens och gender bias : En studie av samband mellan artificiell intelligens, gender bias och könsdiskriminering. [Internet] [Thesis]. Uppsala University; 2019. [cited 2020 Oct 30]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-398282.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Lycken H. Artificiell intelligens och gender bias : En studie av samband mellan artificiell intelligens, gender bias och könsdiskriminering. [Thesis]. Uppsala University; 2019. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-398282

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

.