World Congress 2024 Aug 20, 2024 Session details

Responsible AI in Practice: Real-World Examples and Challenges

Björn Bringmann , Mina Saidze , Ray Eitel-Porter , Steffen Bosse

Is your enterprise ready for the EU AI Act? Learn how to turn responsible AI from a philosophical debate into practical governance that protects your reputation.

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#1 about 4 min

Defining responsible AI and related terminology

The core components of AI ethics and how terminology differs between research and marketing.

#2 about 5 min

Assessing AI ethics adoption in the private sector

How regulatory mandates and public scrutiny force technology companies to elevate responsible AI policies.

#3 about 2 min

Establishing C-level accountability for AI orchestration

The necessity of a dedicated task force to balance regulatory compliance with technological innovation.

#4 about 3 min

Overcoming operational challenges in AI adoption

Why designing and implementing a comprehensive AI program requires significant time across organizational silos.

#5 about 3 min

Adapting AI governance to organization size

How enterprise, medium-sized, and startup companies allocate resources for AI compliance and risk management.

#6 about 4 min

Navigating AI disruption across regulated and unregulated industries

How diverse industries face unique technology challenges when establishing a corporate governance framework.

#7 about 4 min

Driving corporate AI accountability through public pressure

Why external awareness highlights algorithmic bias and demands transparency from software developers.

#8 about 2 min

Framing responsible AI as a core business driver

How implementing ethical AI controls mitigates financial risk and enhances client-facing product offerings.

#9 about 1 min

Mandating AI ethics training for employees

The importance of incorporating AI ethics into standard corporate compliance alongside fundamental cybersecurity policies.

#10 about 2 min

Mitigating algorithmic bias during AI model development

Providing developers with open-source toolkits and synthetic data strategies to identify bias within training datasets.

#11 about 2 min

Educating users and business teams on AI complexities

Aligning technical and non-technical stakeholders to effectively communicate AI concerns regarding transparency.

Matching moments

1:34 min

Introduction to responsible artificial intelligence and societal impact

Toju Duke · WWC 2022

1:31 min

Integrating regulatory policy into responsible artificial intelligence

Rebekka Weiss Rebekka Weiss +1 · WWC 2025

2:47 min

Core properties of responsible artificial intelligence

Jaap Kersten Jaap Kersten +1 · WWC 2024

1:39 min

Balancing value and risk for responsible artificial intelligence

Seppe Housen Seppe Housen · Europe 2026 Virtual

2:36 min

Structuring organizational governance for responsible AI initiatives

Rebekka Weiss Rebekka Weiss +1 · WWC 2025

4:23 min

Navigating the EU AI Act and regulatory landscape

Jaap Kersten Jaap Kersten +1 · WWC 2024

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