Neural Vibe Ltd 

1. Introduction

Neural Vibe Ltd ("Neural Vibe," "we," "us," or "our") is dedicated to the ethical and responsible use of Artificial Intelligence (AI) technologies. This Ethical AI Policy outlines our commitment to transparency, fairness, and accountability in the development and deployment of AI systems, in alignment with the ISO 42001 and 38507 standards and TR 24368.

2. Principles of Ethical AI

2.1 Transparency
 

• Explainability and Understanding: We ensure that our AI systems are understandable and explainable. Stakeholders are informed about how AI decisions are made, the data sources used, and the algorithms applied.

• Documentation and Communication: We maintain clear and comprehensive documentation of AI models, data sources, decision-making processes, and any changes made over time. Regular communication with stakeholders about these aspects is prioritized to ensure transparency.

2.2 Fairness
 

• Bias Prevention and Mitigation: We are committed to preventing bias in AI systems. Regular audits, assessments, and bias detection mechanisms are in place to identify and mitigate potential biases in data and algorithms.

• Equitable Outcomes: Our AI systems are designed to provide equitable outcomes for all users, regardless of their background. We ensure that our systems do not disproportionately impact any particular group.
   

2.3 Accountability
 

• Role Clarity and Responsibility: Clear roles and responsibilities for AI management are assigned within our organization. Our AI governance structure includes designated AI providers, producers, and users, each with specific duties.

• Leadership and Ethical Oversight: Our leadership prioritizes ethical considerations in AI development. They ensure all AI initiatives align with our ethical standards and regulatory requirements, maintaining accountability for AI decisions and outcomes.

2.4 Risk Management
 

• Identification and Mitigation: Robust risk management practices are implemented to identify and mitigate ethical risks associated with AI technologies. We assess and address risks related to data security, privacy, bias, and potential impacts on stakeholders.

• Continuous Monitoring: Continuous monitoring and evaluation of AI systems are performed to ensure they remain effective, unbiased, and adaptable to new challenges. This includes regular updates and improvements to the systems based on new insights and feedback.

2.5 Data Privacy and Security
 

• Privacy Protection: We uphold stringent data privacy measures to protect personal data used in AI systems. Compliance with relevant data protection regulations, including GDPR, is ensured.

• Data Integrity and Confidentiality: Data used in AI training and operations is managed with the highest standards of integrity and confidentiality. We implement security measures to prevent unauthorized access, alteration, or disclosure of data.

3. Implementation and Compliance
 
3.1 Ethical AI System Development

• Incorporating Ethical Considerations: From design to deployment, ethical considerations are integrated into every stage of AI system development. This includes ethical design principles, responsible data collection, fair and unbiased model training, rigorous testing, and continuous monitoring.

• Stakeholder Engagement: Engaging with stakeholders, including end-users, regulators, and affected communities, to gather diverse perspectives and ensure the AI system meets ethical and societal standards.

• Ethical Design Principles: Adopting principles such as fairness, accountability, and transparency in the AI system’s design to prevent biases and ensure that the system aligns with ethical standards.

3.2 Data Management and Security
 

• Data Quality and Integrity: Ensuring the data used in AI systems is of high quality, accurate, and relevant. Implementing data cleaning and validation processes to maintain data integrity.

• Privacy by Design: Incorporating privacy considerations into the AI system design, ensuring compliance with data protection regulations like GDPR. Implementing measures such as data anonymization and encryption to protect personal data.
   

3.3 Continuous Improvement
 

• Regular Reviews and Updates: Conducting regular reviews and updates of AI systems and ethical practices to adapt to new insights, technological advancements, and regulatory changes.

• Feedback Mechanisms: Establishing robust feedback mechanisms to collect input from stakeholders, users, and affected parties. Using this feedback to refine and enhance AI systems continuously.

​3.4 Training and Awareness
 

• Employee Training: Providing ongoing training for employees on ethical AI practices, data privacy, and security. Ensuring all employees understand the ethical implications of AI and their roles in maintaining these standards.

• Awareness Programs: Conducting awareness programs to educate all stakeholders about their responsibilities in upholding ethical AI practices. Promoting a culture of ethical AI use throughout the organization.

4. Reporting and Accountability
 
4.1 Incident Reporting and Management
 

• Clear Reporting Channels: Establishing clear and accessible channels for reporting concerns or incidents related to the ethical use of AI. Ensuring stakeholders know how to report issues and feel confident that their reports will be taken seriously.

• Thorough Investigations: Conducting thorough investigations of all reported incidents. Ensuring that investigations are impartial and transparent, with appropriate corrective actions taken promptly.

​4.2 Regular Audits and Assessments
 

• Internal and External Audits: Conducting regular internal and external audits to ensure compliance with this policy and identify areas for improvement. Audits should be comprehensive and cover all aspects of AI system development, deployment, and use.

• Audit Documentation and Transparency: Documenting audit findings and corrective actions. Making audit results available to relevant stakeholders to maintain transparency and build trust.
   

4.3 Accountability Structures
 

• Designated Ethics Officer: Appointing a designated Ethics Officer responsible for overseeing the implementation of this policy and handling reports of ethical concerns. The Ethics Officer ensures that ethical considerations are integrated into all AI initiatives.

• Clear Roles and Responsibilities: Defining clear roles and responsibilities for AI management across the organization. Ensuring that accountability for ethical AI practices is assigned at all levels, from leadership to operational staff.

​4.4 Performance Metrics and Monitoring
 

• Ethical AI Performance Metrics: Developing and tracking performance metrics related to the ethical use of AI. These metrics can include bias detection rates, privacy incident reports, and stakeholder satisfaction levels.

• Continuous Monitoring: Implementing continuous monitoring of AI systems to ensure they remain compliant with ethical standards. Using advanced monitoring tools to detect and address potential issues in real-time.
   

4.5 Stakeholder Communication
 

• Regular Updates: Providing regular updates to stakeholders about the organization's AI practices, ethical considerations, and any changes to policies or procedures. Ensuring stakeholders are informed about how AI is being used and the measures in place to ensure its ethical use.

• Transparency Reports: Publishing transparency reports detailing the use of AI, ethical challenges encountered, and how they were addressed. Transparency reports build trust and demonstrate the organization’s commitment to ethical AI.

5. Contact Us

If you have any questions about this Ethical AI Policy or our AI practices, please contact us at:

Neural Vibe Ltd  
71-75 Shelton Street, Covent Garden, London, WC2H 9JQ, UNITED KINGDOM  
Email: info@neuralvibe.io