UnBias: emancipating users against algorithmic biases for a trusted digital economy

UnBias: emancipating users against algorithmic biases for a trusted digital economy

UnBias is a collaboration between the Horizon Digital Economy Research Institute at the University of Nottingham, the Human Centred Computing group at the University of Oxford and the Centre for Intelligent Systems and their Applications (CISA) at the University of Edinburgh, with creative studio Pr...

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Bibliografiske detaljer
Main Authors:	Koene, A, Dowthwaite, L, Lane, G, Webb, H, Portillo, V, Jirotka, M
Format:	Conference item
Udgivet:	2018

Lignende værker

TrustScapes: a visualisation tool to capture stakeholders’ concerns and recommendations about data protection, algorithmic bias, and online safety
af: Ito-Jaeger, S, et al.
Udgivet: (2023)

TrustScapes: A Visualisation Tool to Capture Stakeholders’ Concerns and Recommendations About Data Protection, Algorithmic Bias, and Online Safety
af: Sachiyo Ito-Jaeger, et al.
Udgivet: (2023-06-01)

“It would be pretty immoral to choose a random algorithm”: Opening up algorithmic interpretability and transparency
af: Webb, HM, et al.
Udgivet: (2018)

“It would be pretty immoral to choose a random algorithm”: opening up algorithmic interpretability and transparency
af: Webb, H, et al.
Udgivet: (2019)

Judgments in the Sharing Economy: The Effect of User-Generated Trust and Reputation Information on Decision-Making Accuracy and Bias
af: Mircea Zloteanu, et al.
Udgivet: (2021-11-01)

Rational and biased trust.
af: Barr, A
Udgivet: (2004)

Rational and biased trust
af: Barr, A
Udgivet: (2004)

Developing a measure of online wellbeing and user trust
af: Dowthwaite, L, et al.
Udgivet: (2020)

Navigating algorithm bias in AI: ensuring fairness and trust in Africa
af: Notice Pasipamire, et al.
Udgivet: (2024-10-01)

The impact of algorithmic decision-making processes on young people’s well-being
af: Perez, E, et al.
Udgivet: (2021)

Ethics of artificial intelligence in global health: Explainability, algorithmic bias and trust
af: Kerasidou, A
Udgivet: (2021)

Ethics of artificial intelligence in global health: Explainability, algorithmic bias and trust
af: Angeliki Kerasidou
Udgivet: (2021-10-01)

A framework of algorithms: computing the bias and prestige of nodes in trust networks.
af: Rong-Hua Li, et al.
Udgivet: (2012-01-01)

TRUST, AUTOMATION BIAS AND AVERSION: ALGORITHMIC DECISION-MAKING IN THE CONTEXT OF CREDIT SCORING
af: Rita Gsenger, et al.
Udgivet: (2021-12-01)

Correction: A Framework of Algorithms: Computing the Bias and Prestige of Nodes in Trust Networks
Udgivet: (2013-01-01)

Correction: A Framework of Algorithms: Computing the Bias and Prestige of Nodes in Trust Networks.
af: Rong-Hua Li, et al.
Udgivet: (2013-01-01)

In Code, We Trust? Regulation and Emancipation in Cyberspace
af: Zhu Chenwei
Udgivet: (2004-12-01)

Against Time Bias
af: Greene, Preston, et al.
Udgivet: (2016)

Ethnic discrimination unlearned: experience in the repeated Trust Game reduces trust bias
af: Caitlin Duncan, et al.
Udgivet: (2023-05-01)

Bias does not equal bias: a socio-technical typology of bias in data-based algorithmic systems
af: Paola Lopez
Udgivet: (2021-12-01)

Attentional bias in snus users: an experimental study.
af: Rune Aune Mentzoni, et al.
Udgivet: (2014-01-01)

On Western Bias Against Cuba
af: Denise Baden
Udgivet: (2017-03-01)

Understanding user perceptions of trustworthiness in e-recruitment systems
af: Ogunniye, G, et al.
Udgivet: (2021)

Trust aftereffect: adaptation to own or other race faces biases subsequent trust judgements
af: Ong, Tulip Yu Lay
Udgivet: (2024)

Bias, bullshit and lies: audience perspectives on low trust in the media
af: Newman, N, et al.
Udgivet: (2017)

Trusting the experts: The domain-specificity of prestige-biased social learning
af: Charlotte O. Brand, et al.
Udgivet: (2021-01-01)

Trusting the experts: The domain-specificity of prestige-biased social learning.
af: Charlotte O Brand, et al.
Udgivet: (2021-01-01)

"It's your private information. it's your life.": young people's views of personal data use by online technologies
af: Dowthwaite, L, et al.
Udgivet: (2020)

Algorithmic fairness in online information mediating systems.
af: Koene, A, et al.
Udgivet: (2017)

Digital Identity: The effect of trust and reputation information on user judgement in the Sharing Economy.
af: Mircea Zloteanu, et al.
Udgivet: (2018-01-01)

Catalogue of bias: allocation bias
af: Nunan, D, et al.
Udgivet: (2018)

Catalogue of bias: publication bias
af: Goldacre, B, et al.
Udgivet: (2018)

Catalogue of bias: Attrition bias
af: Nunan, D, et al.
Udgivet: (2018)

Catalogue of bias: observer bias.
af: Mahtani, K, et al.
Udgivet: (2018)

Catalogue of bias: novelty bias
af: Luo, Y, et al.
Udgivet: (2023)

Social bias, not time bias
af: Greene, Preston
Udgivet: (2023)

Bias does not equal bias
af: Renate Baumgartner, et al.
Udgivet: (2021-07-01)

A call to action: Designing a more transparent online world for children and young people
af: Virginia Portillo, et al.
Udgivet: (2024-09-01)

The rule against bias and the doctrine of waiver
af: Goudkamp, J
Udgivet: (2007)

Are nurses biased against obese patients?
af: Meryem Türkan Işık, et al.
Udgivet: (2019-10-01)