GT Booster Responsible AI Principles
At GT Booster we are dedicated to developing cutting-edge networking technology for the benefit of people and society. While AI-based technologies hold limitless potential to advance how we live and work, we recognize that with great power comes great responsibility. These AI Principles describe our commitment to developing and deploying our AI systems responsibly, ethically, and sustainably.
CORE PRINCIPLES
1. Fairness and inclusiveness
Identifying and differentiating between fair and unfair biases is a complex challenge, and mathematical accuracy does not necessarily prevent bias. We are committed to ensuring that our AI systems operate fairly and in a non-discriminatory manner, and strive to deliver equitable results across diverse user populations. We seek to avoid unjust impacts on individuals or groups, particularly those related to sensitive characteristics such as gender, ethnicity, and other personal attributes. To prevent the creation or reinforcement of unfair bias, we take action such as implementing procedures, regular reviews, comprehensive testing, and creating and distributing more diverse datasets.
2. Transparency and explainability
We recognize the importance of transparency and explainability in fostering trust with our users and stakeholders. We enable users to make informed choices about their interactions with AI systems and are explicit about their intended purposes. We aim to provide an appropriate level of transparency by making explanations on how our AI systems function accessible and understandable to our users and stakeholders.
3. Privacy and data protection
We respect privacy and champion robust data protection. We integrate our privacy principles into the development and application of our AI technologies, and are committed to handling personal information in accordance with all applicable privacy laws and regulations. We strive to communicate clearly why, where, when, and how user and anonymized user data is collected and used in our solutions, and we provide opportunities for notice and consent. We adhere to strict data management protocols, such as minimizing data collection and retention and aggregating data whenever possible, among other security policies and procedures to resist attempts to compromise the system.
4. Safety and security
We continuously adapt and implement robust safety and security measures to ensure that our AI systems behave safely and as intended, and to minimize misuse and the impact of failure. Through rigorous testing, updates, model retraining, and evaluating performance, we strive to continually improve our solutions’ quality, reliability, safety, and security.
5. Accountability and governance
AI systems do not displace human responsibility and accountability. We implement reliable governance mechanisms, processes, and safeguards to ensure that our AI systems are developed, deployed and used ethically and responsibly. Apart from apply human oversight throughout the lifecycle of our solution to prevent misuse, we also provide appropriate opportunities for feedback to ensure the quality and appropriate performance of our solutions.
