International Conference on AI, Machine Learning, and Data Science Ethics

ICALDE

21st Aug – 22nd Aug 2026 Athens, Greece

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Registration Summary

Conference ICALDE

Date 21st Aug – 22nd Aug 2026

Location Athens, Greece

Participation Type Listener

Organizer Science Leagues

Registration Mode Standard / Physical

Registration Fee USD 0.00

Bank Convenience Charges (5.8%)i USD 0.00

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Conference Session Tracks

Aligned with UN Sustainable Development Goals

The conference's session tracks effectively support the following SDGs.

01 Ethical Frameworks in AI Development +

This track explores the various ethical frameworks that guide the development and deployment of artificial intelligence systems. Participants will discuss the implications of these frameworks on innovation and societal impact.

SDG 4 SDG 16

02 Transparency and Accountability in Machine Learning +

This session focuses on the importance of transparency and accountability in machine learning algorithms. It aims to address the challenges and solutions related to ensuring that AI systems can be audited and held accountable.

SDG 10

03 Bias Mitigation Strategies in Data Science +

This track examines the methodologies and practices for identifying and mitigating bias in data science projects. Discussions will include case studies and best practices for achieving fairness in AI.

SDG 5 SDG 10

04 Explainable AI: Bridging the Gap Between Models and Users +

This session delves into the significance of explainable AI in enhancing user trust and understanding of machine learning models. It will cover techniques for improving model interpretability and user engagement.

SDG 9

05 Governance of AI Systems: Policies and Regulations +

This track addresses the governance structures necessary for the ethical oversight of AI systems. Participants will explore current policies and propose frameworks for effective regulation.

SDG 16

06 Privacy-Preserving Machine Learning Techniques +

This session focuses on innovative approaches to ensure privacy in machine learning applications. Discussions will include differential privacy, federated learning, and other privacy-preserving methodologies.

SDG 16

07 Responsible AI: Balancing Innovation and Ethics +

This track examines the concept of responsible AI and its implications for technological advancement. Participants will discuss strategies for aligning AI innovation with ethical considerations.

SDG 9 SDG 16

08 Trust in Data Science: Building Credibility and Reliability +

This session explores the factors that contribute to trust in data science practices and outputs. It will address the role of data quality, transparency, and ethical considerations in building credibility.

SDG 16

09 Societal Impact of AI: Opportunities and Challenges +

This track investigates the broader societal implications of AI technologies. Participants will discuss both the potential benefits and the ethical dilemmas posed by AI in various sectors.

SDG 10 SDG 16

10 Ethical Decision Making in AI Systems +

This session focuses on the frameworks and methodologies for ethical decision making in AI applications. It will explore case studies that highlight the complexities of ethical dilemmas in AI.

SDG 16

11 Algorithmic Fairness: Theoretical Foundations and Practical Applications +

This track examines the theoretical underpinnings of algorithmic fairness and its practical implications in real-world applications. Discussions will include metrics for fairness and strategies for implementation.

SDG 10 SDG 16