AI & Machine Learning Ethics Policy

Last updated: July 9, 2026

At TerminalStreet LLC, we recognize the transformative power of artificial intelligence and machine learning technologies. We are committed to developing and deploying these technologies in ways that are ethical, transparent, and beneficial to society while mitigating potential harms.

1. Core Ethical Principles

1.1 Human-Centered Design

We design AI systems with human well-being as the primary consideration. Our AI solutions aim to augment human capabilities, not replace human judgment in critical decisions affecting people's rights, opportunities, or access to essential services without appropriate oversight.

1.2 Fairness and Non-Discrimination

We strive to develop AI systems that are fair and do not discriminate against individuals or groups based on protected characteristics such as race, gender, age, disability, sexual orientation, religion, or national origin. We actively work to identify and mitigate algorithmic bias in our systems.

Our approach includes:

• Diverse and representative training data
• Regular bias detection and mitigation processes
• Fairness metrics and testing across different demographic groups
• Ongoing evaluation and improvement of our systems

1.3 Transparency and Explainability

We commit to transparency in our AI systems by:

• Clearly communicating when AI is being used
• Providing appropriate explanations of how our AI systems make decisions
• Documenting the intended uses, limitations, and potential risks of our AI systems
• Making complex systems understandable to relevant stakeholders through appropriate documentation and interfaces

1.4 Privacy and Data Governance

We respect privacy and are committed to responsible data governance by:

• Collecting and using data in accordance with privacy laws and regulations
• Implementing data minimization principles
• Securing personal data with appropriate safeguards
• Providing clear information about how data is used in our AI systems
• Respecting individual rights regarding their personal data

1.5 Security and Safety

We prioritize the security and safety of our AI systems by:

• Conducting thorough security assessments
• Implementing robust safeguards against unauthorized access or manipulation
• Testing systems for potential harms or unintended consequences before deployment
• Establishing processes for monitoring and addressing safety issues post-deployment

1.6 Accountability

We take responsibility for our AI systems by:

• Establishing clear lines of responsibility for AI development and deployment
• Implementing governance structures for ethical oversight
• Conducting regular audits of our AI systems
• Maintaining appropriate documentation throughout the AI lifecycle
• Providing mechanisms for feedback, questions, and redress

2. AI Development and Deployment Practices

2.1 Risk Assessment

Before developing or deploying AI systems, we conduct risk assessments to:

• Identify potential harms and unintended consequences
• Assess impacts on different stakeholder groups, particularly vulnerable populations
• Evaluate alignment with legal and ethical requirements
• Determine appropriate risk mitigation strategies

2.2 Training Data Management

We are committed to responsible training data practices:

• Ensuring data quality, relevance, and representativeness
• Documenting data provenance, limitations, and potential biases
• Respecting intellectual property rights and obtaining proper permissions for data use
• Implementing appropriate data security and privacy protections
• Regularly reviewing and updating training data to address emerging biases or issues

2.3 Testing and Validation

We rigorously test our AI systems before deployment:

• Validating performance across diverse datasets and scenarios
• Testing for robustness against adversarial attacks and edge cases
• Evaluating fairness and bias across different demographic groups
• Assessing explainability and transparency
• Conducting human-in-the-loop evaluations where appropriate

2.4 Continuous Monitoring and Improvement

Our responsibility extends beyond initial deployment:

• Implementing systems to monitor performance and outcomes in production
• Regularly evaluating for drift, bias, or other quality issues
• Establishing feedback channels for users and affected stakeholders
• Applying lessons learned to improve future iterations
• Maintaining version control and documentation of system changes

3. Specific Applications and Use Cases

3.1 Automated Decision Systems

For AI systems used in decision-making processes that significantly affect individuals:

• We implement appropriate human oversight and review mechanisms
• We provide explanations for decisions where feasible and appropriate
• We ensure meaningful opportunities for human appeal or intervention
• We regularly audit outcomes for fairness and compliance with this policy

3.2 Retrieval-Augmented Generation & Large Language Models

For generative AI and large language models:

• We implement safeguards against generating harmful, illegal, or deliberately misleading content
• We clearly communicate the AI-generated nature of content when not obvious
• We respect copyright and intellectual property considerations
• We maintain human oversight of generated content in sensitive contexts
• We implement responsible citation and attribution practices

3.3 Computer Vision and Facial Recognition

For computer vision and facial recognition applications:

• We limit use to specific, well-defined purposes with clear benefits
• We obtain appropriate consent or legal basis for processing biometric data
• We implement strict accuracy and fairness requirements across demographic groups
• We respect privacy and implement appropriate data protections
• We do not deploy these technologies in contexts where they may enable mass surveillance or infringe on civil liberties

3.4 Autonomous Systems

For autonomous or semi-autonomous AI systems:

• We implement robust safety measures and fail-safe mechanisms
• We ensure appropriate human oversight and intervention capabilities
• We conduct extensive testing in diverse and challenging environments
• We clearly communicate system capabilities and limitations to operators and users

4. Governance and Implementation

4.1 Ethics Committee

We have established an AI Ethics Committee responsible for:

• Reviewing high-risk AI applications before deployment
• Providing guidance on ethical questions and dilemmas
• Updating this policy to address emerging issues and technologies
• Overseeing implementation of this policy across our organization

4.2 Training and Awareness

We promote an ethical AI culture through:

• Regular training for employees involved in AI development and deployment
• Resources and guidance for implementing this policy in practice
• Clear channels for raising concerns or ethical questions
• Recognition of ethical considerations in performance evaluations

4.3 Stakeholder Engagement

We engage with diverse stakeholders to inform our approach:

• Consulting with affected communities and user groups
• Participating in industry initiatives and standard-setting efforts
• Engaging with policymakers and regulators
• Collaborating with academic and civil society experts

4.4 Compliance with Laws and Regulations

We comply with applicable AI regulations and standards:

• Monitoring regulatory developments in relevant jurisdictions
• Implementing processes to ensure compliance
• Documenting our compliance efforts
• Engaging constructively with regulatory authorities

5. Client Responsibilities and Expectations

When we develop AI systems for clients, we expect and encourage clients to:

• Adhere to this policy and their own ethical guidelines
• Use our AI solutions for their intended purposes
• Implement appropriate governance and oversight mechanisms
• Provide feedback on any ethical concerns or unintended consequences
• Maintain transparency with their users about AI use

We reserve the right to decline or discontinue projects that conflict with this policy or present unacceptable ethical risks.

6. Responsibility Disclaimer

While we strive to develop ethical AI systems, we recognize that AI technologies involve inherent limitations and risks:

• AI systems may produce unexpected outputs or behave in unanticipated ways
• Perfect fairness, accuracy, or safety cannot be guaranteed across all possible contexts or use cases
• AI systems reflect the data they are trained on and may perpetuate existing societal biases
• Technological capabilities and ethical standards continue to evolve rapidly

We encourage ongoing dialogue about these challenges and are committed to continuous improvement of our AI ethical practices.

7. AI Services Limitation of Liability

Given the inherent limitations and evolving nature of AI technology:

• No Warranty: AI services are provided "as is" without warranties of accuracy, completeness, or fitness for any particular purpose
• Limitation of Damages: Our liability for AI-related claims is limited to the amount paid for the specific AI service in question
• No Consequential Damages: We shall not be liable for indirect, incidental, special, consequential, or punitive damages arising from AI service use
• User Responsibility: Users are responsible for validating AI outputs and implementing appropriate safeguards for their specific use cases
• Regulatory Changes: Liability limitations may be modified to comply with evolving AI regulations

8. AI Ethics Dispute Resolution

For disputes related to AI ethics, algorithmic bias, or AI service issues:

• Direct Resolution (5 business days): Contact our AI Ethics Committee at [email protected]
• Independent AI Ethics Review (10 business days): Complex cases may be referred to independent AI ethics experts
• Algorithmic Audit: Disputed AI systems may undergo independent algorithmic auditing by qualified third parties
• Mediation: Parties may request mediation through qualified AI ethics mediation services
• Arbitration: Any dispute not resolved through the steps above will be resolved by binding individual arbitration administered by JAMS, with a class-action waiver and a 30-day opt-out right, as set out in the "Dispute Resolution and Arbitration" section of our Terms of Service, which governs disputes under this document. Individual small-claims actions and claims for injunctive relief for intellectual-property violations are excepted, as provided there.

9. Force Majeure

AI services may be subject to delays, interruptions, or modifications due to Force Majeure events as defined in ourForce Majeure Policy. During such events, AI model performance, training schedules, and service availability may be impacted.

We will make commercially reasonable efforts to maintain AI service continuity and will notify affected users as soon as reasonably practicable of any Force Majeure events impacting AI services.

10. Contact Information

For questions, concerns, or feedback regarding this AI Ethics Policy, please contact:

[email protected]