Partner

Partner &
Cooperation

Research and peer-reviewed work applied as bottom-up approach directly to your organization by a collaborative team and strong academic partners. By addressing AI ethics, we support organizations proactively identify and mitigate ethical issues throughout the AI development process, ensuring greater consistency in ethical AI systems.

Join the Force

Exploring the core principles that guide trustworthy AI system development.

Interdisciplinary team designs and drafts future social tech concepts & studies for companies in order to generate human-centered experience and sustainable social impact.

Partnership

We welcome new partners from academia and industry. This could lead to research projects or consulting tools (e.g., the TAII Framework) for your business success in developing trustworthy AI systems. Please feel free to contact us and share your ideas to express your interest.

Team Member

We are always open to volunteer research participants from Europe who are curious, self-organized, experienced in research, and interested in technology, humanity, and culture. Please feel free to contact us and share your ideas and previous research findings with us.

Partner & Cooperations

Partner and cooperations

AI Literacy

To be compliant with Article 4 of the EU AI Act, companies need to take measures of increading AI literacy.

The following points are outcomes of using the TAII Framework for trustworthy AI system development. By taking these steps, companies can ensure they meet the AI literacy requirements set out in Article 4 of the EU AI Act.

Assessment of current AI literacy levels: Companies evaluate the existing AI literacy within their organisation, including the technical knowledge, experience, education, and training of their staff.

Implementation of training programs: Develop and provide regular training programs that cover both the technical aspects of AI and the ethical considerations. This training should be tailored to address the specific roles and responsibilities of employees.

Development of internal guidelines and standards: Establish clear guidelines and standards for AI use within the company. These should outline best practices, ethical principles, and compliance requirements.

Continuous improvement: The TAII Framework is iterative and refers to the whole AI system’s life cycle, allowing for ongoing refinement and improvement of ethical considerations.

Encouragement of interdisciplinary communication: Foster communication and collaboration between different departments such as IT, ethics, and legal. This helps in developing a comprehensive understanding of trustworthy AI systems.

Documentation of compliance efforts: Keep detailed records of all AI literacy measures implemented, including training programs, guidelines, and any other initiatives. This documentation will be crucial for demonstrating compliance during regulatory inquiries.

Stay updated with evolving standards: Regularly review updates from regulatory bodies and industry best practices to ensure ongoing compliance.

Embed AI literacy across the organisation: Ensure that AI literacy is not limited to technical teams but is integrated across all relevant aspects of the business.