Generative artificial intelligence has become one of the defining technologies of the decade. It supports content creation, powers conversation systems, guides recommendation engines, enhances education, and accelerates business operations across industries. Organizations see generative AI as an accelerator for innovation. However, they also recognize the risks associated with large scale deployment, such as misinformation, biased outputs, misunderstanding of cultural context, unsafe queries, and unpredictable emergent behaviors. Because of these risks, trust has emerged as a foundational requirement for AI adoption.
ByteDance, the global technology company behind multiple international content and social platforms, exemplifies both the promise and the responsibility associated with generative AI. The company serves one of the most diverse user bases in the world, hosting multilingual interactions, cultural exchange, real time commentary, and complex video and content based communication across its product ecosystem. Over the past few years, ByteDance has introduced a growing suite of generative AI features, ranging from creative enhancement tools to multimedia content generation assistants, allowing millions of users to express themselves through AI powered experiences.
With this expansion, ByteDance must maintain one of the most robust AI safety ecosystems in the industry. While generative models enable highly diverse and open ended user experiences, they can also introduce risks related to misuse, bias, hallucination, privacy exposure, and user harm. These risks must be carefully governed at scale, especially for a global platform operating across jurisdictions and languages.
Since 2023, Chong Lam Cheong has played a central role in this ecosystem as a Generative AI Safety Product Manager at ByteDance’s San Jose office. He is responsible for ensuring that users can safely engage with ByteDance’s generative features and that the company’s underlying model capabilities operate within strict safety, compliance, and quality guardrails. Cheong collaborates closely with engineering teams, trust and safety groups, policy leaders, machine learning researchers, legal advisors, and international operations teams to build governance systems that scale with ByteDance’s global footprint.
One of Cheong’s major contributions is the design of risk evaluation pipelines for generative models. These pipelines simulate diverse user scenarios across languages, cultures, and content categories. They include safety relevant prompts, adversarial queries, borderline content, and everyday user behavior. The pipeline measures hallucination rates, harmful content generation, guideline compliance, robustness to manipulation, and sensitivity to cultural context. This systematic evaluation helps determine whether a model is safe enough for deployment across ByteDance’s global platforms.
Cheong also supports the development of governance tools integrated into ByteDance’s product release process. These tools allow teams to run automated compliance checks before launching new generative features. The system identifies safety gaps, verifies whether required tests have been completed, and generates documentation for internal audits and regulatory reviews. This infrastructure is essential for a company that operates in markets with different regulations, including the United States, the European Union, and regions in Asia and the Middle East.
Another important component of Cheong’s work is the development of safety observability dashboards. These dashboards track model performance after deployment and collect signals related to user reports, policy violations, model drift, and unusual patterns. Because ByteDance’s environment changes rapidly, real time visibility is critical. Dashboards help teams detect new risks and make appropriate interventions, such as adjusting settings, adding guardrails, or retraining components.
Training data governance also plays a major role in ensuring trustworthy AI. Generative models require diverse data sources, and the quality of this data influences model behavior. Cheong has helped build workflows that identify high risk data, classify sensitive categories, document data origins, and maintain compliance with privacy standards. These processes reduce the likelihood of harmful content being reproduced in model outputs.
Cheong also collaborates on the development of real time mitigation systems. These systems prevent generative models from producing unsafe outputs. They may reroute sensitive prompts to human moderators, apply automated filters, generate safe alternative responses, or decline requests that violate platform policy. This ensures that generative features remain aligned with the expectations of regulators and ByteDance’s global trust and safety organization.
Analysts point out that ByteDance operates at a scale where even small model errors can have large consequences. The company must protect young users, respond to global regulatory pressures, and maintain community trust. As generative AI becomes more powerful, ByteDance faces new challenges in preventing misinformation, harassment, harmful stereotypes, and unintended influence on public discourse. Cheong’s work helps address these challenges by providing structured methods for testing, monitoring, and improving generative models.
Cheong’s multidisciplinary background makes him effective in this role. His engineering experience supports structured risk analysis, and his work in generative AI governance helps him anticipate new safety concerns. He integrates technical knowledge with policy understanding and cross cultural awareness. This combination allows him to design safety systems that reflect the realities of global platforms.
Cheong sees responsible AI as a shared responsibility across the entire organization. Engineers must build safe architectures. Policy teams must define clear rules. Trust and safety teams must enforce guidelines. Legal teams must understand emerging regulations. Operations teams must respond quickly when issues arise. By aligning these roles, ByteDance can maintain a governance system that scales with rapid technological development.
Looking ahead, Cheong believes the next stage of AI governance will require standardized industry benchmarks, greater public transparency, and stronger global coordination. As governments introduce new regulations, companies will need to demonstrate testing coverage, monitoring processes, and mitigation strategies. Users will expect more communication about how AI systems work and how safety risks are addressed.
For Cheong, trustworthy AI is a continuous process rooted in measurement, infrastructure, and collaboration. He believes that generative AI can serve as a positive force when deployed responsibly. His work at ByteDance demonstrates how major technology companies can innovate while maintaining commitments to user safety, regulatory compliance, and public trust. As generative AI continues to shape global digital ecosystems, the systems built by professionals like Cheong will become essential to the future of safe and sustainable AI.
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Company Name: Chonglam (Lam) CHEONG
Contact Person: Chonglam (Lam) CHEONG
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City: San Jose
State: California
Country: United States
Website: https://www.linkedin.com/in/clcheong/
