Solving Ethical AI with Digital Identity
Combined Session
Wednesday, May 07, 2025 14:30—15:30
Location: B 05-06
Wednesday, May 07, 2025 14:30—15:30
Location: B 05-06
The role of AI in protecting and managing digital identities has become of great importance. However, this rise in AI-driven solutions raises questions of ethic and accountability. This session will focus on the ethical implications of data consumption, transparency, privacy concerns and the possibility of bias in Identity Verification Systems.
We will explore the responsibilities of organization, policy makers and developers in ensuring that AI Technologies respects & upholds the value of fairness, transparency and accountability.
By tackling these challenges, we can promote trust and equity in AI applications and ensuring that individual identities are safe, and they can retain control over their personal information in AI-driven society.
Key takeaway from this session:
- Effective Data Stewardship
- Ethical implications of AI in digital Identity
- Shared responsibilities of Stakeholders in AI solution for digital identity
- Strategies for fairness and transparency: Strategies for designing AI systems that prioritize fairness, reduce bias and protect user privacy in digital identity applications.
Over the next few years, targeted advertising & personalization will see a quantum leap forward with GenAI, moving beyond simple suggestions to real-time simulations of our behaviours and preferences. When AI can predict and steer our choices, are we truly deciding for ourselves—or merely following an algorithmic nudge?
This talk dives into the ethical dilemmas of GenAI-powered hyper-personalization - highlighting how it can be weaponized for mass spear-phishing and disinformation. We’ll critique our outdated, “check-the-box” consent framework and propose new paradigms—like Self-Sovereign Identity (SSI) and transparent AI regulations—to restore data ownership and accountability.
Onboarding applications, whether on-premise or in the cloud, is a significant challenge for organizations. Translating business process activities into the necessary application changes is often complex and error prone. This difficulty stems from intricate access models and a lack of clarity around how provisioning and deprovisioning work within these systems.
An AI Agent, designed with a user-focused and interactive approach, transforms the onboarding process. Users can articulate their application details, desired operations, and integration objectives in simple, natural language. Leveraging Reinforcement Learning from Human Feedback (RLHF), the agent improves its understanding and recommendations iteratively, aligning closely with organizational requirements.
The agent does not act autonomously—it consistently seeks validation and adjusts its approach based on user feedback until the desired outcome is achieved.
Join us for a live demo to witness how this innovative solution simplifies the application onboarding experience!
