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Integrating AI Into Arbitration: Balancing Efficiency With Fairness and Legal Compliance
6 references·0 citing·23 second hop
Integrating AI Into Arbitration: Balancing Efficiency With Fairness and Legal Compliance (2025)Integrating AI Into Arbitration: Balancin…Three pathways for standardisation and ethical disclosure by default under the European union artificial intelligence act (2024)Three pathways for standardis…Policy advice and best practices on bias and fairness in AI (2024)Policy advice and best practi…Navigating and reviewing ethical dilemmas in AI development: Strategies for transparency, fairness, and accountability (2024)Navigating and reviewing ethi…Exploring Deep Learning Methods for Audio Speech Emotion Detection: An Ensemble MFCCs, CNNs and LSTM (2024)Exploring Deep Learning Metho…Developing Green Marketing Strategies: A Comprehensive Analysis of Consumer Behaviour and Business Practices (2024)Developing Green Marketing St…Digitally Transforming Electronic Governments into Smart Governments: SMARTGOV, an Extended Maturity Model (2021)Digitally Transforming Electr…Developing fully functional E-government: A four stage model (2001)The Evolution of E‐Government among Municipalities: Rhetoric or Reality? (2002)The Delphi technique: myths and realities (2003)Examining the antecedents and outcomes of smart government usage: An integrated model (2022)A methodology for assessing supply-demand matching of smart government services from citizens’ perspective: A case study in Nanjing, China (2023)Artificial intelligence capabilities, dynamic capabilities and organizational creativity: contributing factors to the United Arab Emirates Government’s organizational performance (2024)AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias (2018)Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims (2020)AI-Based Modeling: Techniques, Applications and Research Issues Towards Automation, Intelligent and Smart Systems (2022)Accountability and Transparency Ensuring Responsible AI Development (2024)Navigating the Ethical Terrain of AI-Generated Text Tools: A Review (2024)Artificial Intelligence-Driven Recommendations and Functional Food Purchases: Understanding Consumer Decision-Making (2025)Equality of Opportunity in Supervised Learning (2016)Model Cards for Model Reporting (2019)The global landscape of AI ethics guidelines (2019)Democratising AI: Multiple Meanings, Goals, and Methods (2023)Mitigating the adverse effects of AI with the European Union's artificial intelligence act: Hype or hope? (2023)Comparing the value of perceived human versus AI-generated empathy (2025)Stanford Encyclopedia of Philosophy (2015)A Survey on Bias and Fairness in Machine Learning (2021)Bias and Fairness Addressing Discrimination in AI Systems (2024)Ethics, transparency, and explainability in generative ai decision-making systems: a comprehensive bibliometric study (2024)Navigating algorithm bias in AI: ensuring fairness and trust in Africa (2024)
this work references cited by second hop

References

  • 2024Navigating and reviewing ethical dilemmas in AI development: Strategies for transparency, fairness, and accountability204 cited
  • 2024Three pathways for standardisation and ethical disclosure by default under the European union artificial intelligence act112 cited
  • 2021Digitally Transforming Electronic Governments into Smart Governments: SMARTGOV, an Extended Maturity Model110 cited
  • 2024Policy advice and best practices on bias and fairness in AI109 cited
  • 2024Exploring Deep Learning Methods for Audio Speech Emotion Detection: An Ensemble MFCCs, CNNs and LSTM67 cited
  • 2024Developing Green Marketing Strategies: A Comprehensive Analysis of Consumer Behaviour and Business Practices32 cited

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