GLTaC & AI
Our Approach to AI
Navigating the AI Frontier: How GLTaC Balances Innovation with Compliance
At GLTaC, we're committed to leveraging cutting-edge technology while maintaining the highest standards of risk management and regulatory compliance.
Innovation with Responsibility
As AI translation tools transform our industry, we carefully evaluate each advancement for both its potential and its risks. Our approach? We employ only human translators for the actual translations, using AI solely as a supporting tool. This human-centered method ensures we maintain the high standards of accuracy and consistency that our clients have come to expect. We adopt technologies that enhance our services while ensuring human expertise remains at the core of our critical translation work.
Global Regulatory Navigation
Staying current with AI regulations isn't just good practice—it's essential for our global operations. We actively monitor developments across jurisdictions:
- U.S. frameworks from NIST and sector-specific guidelines
- EU AI Act compliance requirements
- China's evolving AI governance structure
- Japan's AI Ethics Guidelines
Why This Matters for Our Clients
When documentation crosses borders, it crosses regulatory environments. Our vigilance means your translated content meets compliance standards regardless of destination, which is especially crucial for technical and EHS documentation.
Our Commitment
We believe responsible innovation creates sustainable value. By balancing technological advancement with robust risk management, we deliver translations that are not just accurate and culturally appropriate, but also ethically sound and compliant.
The Hidden Costs of AI-Human Hybrid Translation for Technical Content
The False Economy of AI-Assisted Technical Translation
While AI translation tools promise cost savings, their application to technical documentation across industries—chemical, pharmaceutical, aerospace, automotive, and manufacturing—reveals a false economy that increases costs while compromising quality.
Increased Labor Costs and Inefficiencies
- Double Work Requirements: Professional translators must perform comprehensive source-to-target comparison, essentially re-translating the entire document while simultaneously checking AI output. This dual process requires significantly more time than direct human translation.
- Extended Timelines: Technical translation projects using AI-human hybrid workflows consistently experience longer completion times due to comprehensive review requirements and correction processes.
- Higher Effective Costs: Translators spend disproportionate time on error identification and correction rather than productive translation work, resulting in higher hourly rates for the same deliverable quality.
Compounded Risk and Quality Issues
- Multiple Failure Points: The review process introduces additional variables where translators must identify AI errors while ensuring they don't introduce new mistakes during correction, creating a more complex quality assurance challenge.
- Cognitive Load Burden: Reviewing and correcting AI translations requires more mental effort than translating from scratch, as professionals must constantly evaluate AI decisions while maintaining technical accuracy and regulatory compliance.
Critical Technical Translation Challenges
- Regulatory Compliance: One of the primary compliance risks associated with poor AI translations lies in the misinterpretation of critical information. In regulated industries, inaccuracies can lead to serious legal and financial repercussions.
- Specialized Terminology: AI systems struggle with domain-specific vocabulary where subtle differences can completely alter meaning, requiring precise technical knowledge spanning manufacturing processes, safety protocols, and international standards.
- Legal Framework Limitations: AI failed to use a comparative-law approach to properly identify the legal concepts involved, something that the new technology is not yet ready to do—particularly problematic for organizations operating across multiple regulatory jurisdictions.
The Irreplaceable Human Element
Professional technical translators provide integrated expertise that eliminates AI preprocessing needs: deep understanding of technical processes and regulatory requirements; contextual decision-making for terminology conflicts; error prevention through source document consistency recognition; integrated quality assurance with simultaneous linguistic accuracy and technical correctness verification; and critically, the ability to recognize when context is insufficient and seek clarification from subject matter experts or source document authors. This human capacity for inquiry—asking the right questions when ambiguity arises—ensures translation accuracy that AI systems cannot achieve, as they lack the judgment to identify when additional context is essential for correct translation.
Economic Reality and Conclusion
Organizations must consider total costs including extended timelines, increased review requirements, higher error correction rates, and potential regulatory liabilities. The hybrid approach consistently costs more than direct human translation while introducing additional operational and compliance risks. For technical content requiring regulatory compliance, safety accuracy, or specialized domain knowledge, direct human translation by qualified subject matter experts remains the most cost-effective solution. The economic reality reveals that supposed AI cost savings are consistently offset by increased review time, higher error rates, and extended project timelines.
AI Regulations
The overview presents a general snapshot of the regulatory environment to help contextualize our approach to balancing innovation with compliance in translation services. For the most current and detailed regulatory information, please consult official government resources or specialized legal counsel.
AI Regulation Effort in the U.S.
While there isn't a single, comprehensive federal law governing AI in the US, there's a growing body of regulations and initiatives at both the federal and state levels. Here's a breakdown of the key aspects:
Federal Level:
- Executive Order 14110 (October 2023) on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence: This executive order directs federal agencies to develop AI safety and security, protect privacy and civil liberties, address algorithmic discrimination, and promote responsible innovation. It directs various federal agencies to develop guidelines and regulations related to AI.
- National Artificial Intelligence Initiative Act of 2020 (NAII): This act, while primarily focused on promoting AI research and development, also directs the National Institute of Standards and Technology (NIST) to develop standards for AI systems.
- NIST AI Risk Management Framework: Voluntary guidelines for responsible AI development.
- Federal Trade Commission (FTC): The FTC has been active in enforcing existing laws, such as those related to consumer protection, in the context of AI. They have taken action against companies for deceptive or unfair practices involving AI.
- EEOC: Providing guidance addressing AI discrimination in employment.
- FDA: Focusing on oversight of AI medical devices.
- Consumer Financial Protection Bureau (CFPB): Exploring how existing laws apply to AI and may issue further guidance or regulations.
State Level:
- Colorado AI Act: AI legislation requiring regular testing and risk management. This is one of the most comprehensive state-level AI laws, focusing on regulating the use of AI in insurance.
- California: Requires businesses to assess the impact of automated decision tools.
- New York City Local Law 144: Regulates AI in employment decisions.
- Other State Laws: Several other states have passed or are considering legislation related to specific aspects of AI, such as its use in hiring, facial recognition, and automated decision-making.
Industry-Specific:
- Financial services: Banking regulators are examining AI use in lending and risk assessment.
- Healthcare: FDA regulation of AI medical devices through the Software as a Medical Device framework.
AI Regulation Beyond the U.S.
AI regulation is a hot topic worldwide, and different countries are taking varied approaches. Here's a glimpse at some key regions and their strategies:
Europe:
- European Union (EU): The EU is leading the charge with its AI Act (March 2024). The world's first comprehensive AI law, which is a landmark piece of legislation using a risk-based approach. It classifies AI systems based on risk levels and imposes corresponding obligations. This act is expected to set a global precedent for AI regulation. This takes effect in phases between 2024 and 2026. The various risk levels include the following:
- Banned: Unacceptable risk AI systems (social scoring, emotion recognition in workplaces)
- High-risk systems: Requires extensive documentation, testing, and oversight
- General purpose AI: Subject to transparency requirements
- United Kingdom (UK): The UK is taking a more innovation-friendly approach, focusing on principles and guidance rather than hard law. They are emphasizing collaboration with industry and international cooperation on AI safety. The key factors are as follows:
- Pro-innovation approach with voluntary principles
- AI Safety Institute established in 2023
- Regulatory framework focused on existing regulators applying AI principles
Asia:
- China: Generative AI regulations (August 2023) require content moderation and data protection. China has a comprehensive AI regulatory regime, focusing on algorithmic systems with respect to transparency and preventing algorithmic discrimination, deep synthesis information services, and generative AI. China has sectoral regulations for autonomous vehicles and financial services. Their regulations emphasize upholding Chinese values and state stability.
- Singapore: Singapore is a leader in AI governance, with a Model AI Governance Framework and a focus on sector-specific oversight and ethical testing requirements. They have also been quick to adapt their regulations to new developments like generative AI.
- Japan: Japan has a "human-centered" approach to AI, emphasizing ethical principles and social responsibility. They are currently taking a "soft law" approach, with guidelines rather than strict regulations, pursuing voluntary guidelines and international cooperation.
Other Regions:
- Canada: Canada is developing its own AI strategy, with the Artificial Intelligence & Data Act (AIDA) currently under consideration, which would regulate high-impact AI systems. It includes an Algorithmic Impact Assessment tool for government AI use. They are aiming to balance innovation with responsible AI adoption.
- Australia: Australia is taking a similar approach to Canada, with proposed guardrails for high-risk AI and a voluntary standard for AI safety.
- Brazil: Currently has a draft legislation based on EU model under consideration.
- India: Is working on a risk-based approach similar to EU AI Act.
Regulatory Disclaimer: The information provided regarding AI regulations in the US and globally is shared for informational purposes only and reflects our understanding as of October 2024. GLTaC is not a legal authority on AI regulations. This content should not be considered legal advice. Regulatory landscapes are evolving rapidly, and specific requirements may vary by jurisdiction, industry, and application. We recommend consulting with legal experts specializing in AI compliance for guidance on your specific situation.