“The Age of AI Control Is Coming,” Says Think4BL CEO Park Ji-hwan
A Good AI Awards–Winning Company
“Future Competitiveness Lies in AI Reliability… Institutional Support Needed”
“AI Directors and Controllers Will Emerge as Key Roles”
“We need to cultivate professionals who understand the nature of artificial intelligence (AI) reliability. AI controllers will become one of the new jobs of the future.”
Park Ji-hwan, CEO of Think4BL, shared this outlook on the future of the AI industry in a written interview with THE AI. “The recent exponential development of AI technology has already led to layoffs of engineers in many organizations,” he said. “While securing manpower to build AI reliability is critical, companies remain largely uninterested in new roles that supervise and control AI, focusing only on performance competition.” He emphasized, “Future competitiveness lies in AI reliability, and this requires industry-wide and institutional support.”
Think4BL is a company specializing in AI reliability, supporting the safe and responsible use of AI across fields such as education, consulting, data analysis, and smart livestock. The company operates its own data bias analysis cloud service and RE:IN, a development tool designed to ensure AI reliability. RE:IN enhances model reliability by analyzing data duplication rates and bias, while Think4BL also provides AI reliability consulting and training programs.
Park has participated in the development of six industry-specific sectors of the Ministry of Science and ICT’s Guidelines for Trustworthy AI Development. More recently, he established the Transnational Research Alliance for Intelligent and Neutral AI (TRAIN). Last year, Think4BL received the Good AI Awards, which evaluate AI reliability. “The award reflects our systematic research across all dimensions of AI reliability and its application to real industries,” Park said. “We are the only organization in Korea that comprehensively studies the full spectrum of AI reliability, including impact analysis, risk management, governance frameworks, transparency, data bias analysis, and model robustness assessment.”
“Despite the limitations faced by small and medium-sized venture companies, we have continued investing over the past decade and steadily pioneered areas that few others addressed, such as AI reliability,” he said. “To overcome Korea’s shortage of specialized talent, we have formed a global research network spanning more than 20 countries and continue developing technologies at an international level.”
For Park, “Good AI” is not simply fast or highly accurate AI. “High performance can sometimes increase risk and make harmful outcomes more precise,” he said. “True Good AI is AI that can safely coexist with human values.” He added that ensuring safe operation within human and societal norms has become increasingly important.
◇ Growing Demand for AI Reliability
According to Park, market demand for AI reliability began accelerating in earnest this year, driving increased demand for tools that can guarantee reliability. “As AI expands into the real world, including physical AI, companies and institutions have realized that performance testing alone cannot ensure safety and trustworthiness.”
He also pointed to growing confusion in the AI certification market. “With the recent proliferation of AI certification systems in Korea, the term ‘reliability’ is often used inconsistently to refer to security, safety, basic testing, or red-team evaluations,” he said. “This creates significant confusion for both consumers and businesses.”
Park noted that some accredited testing bodies label simple performance evaluations based on ISO/IEC 4213 as “reliability certification.” “ISO/IEC 4213 measures classification accuracy within a given dataset,” he explained. “It does not verify whether test data reflect real-world conditions or adequately cover edge cases and extreme scenarios. It is an average performance metric, not a safety or reliability validation.”
◇ “AI Reliability in Korea Remains Largely Declarative”
Park criticized Korea’s AI reliability ecosystem, noting a lack of foundational infrastructure and policy support. “While other countries are making national-level investments in training reliability professionals—expanding graduate programs, mandating internships, and linking government procurement to reliability—Korea lacks specialized higher education programs, formal curricula, and textbooks in this field,” he said.
He added that current certification systems should not be mistaken for genuine corporate support. “This is similar to believing that English proficiency will improve simply by creating a TOEFL exam,” he said.
Park diagnosed that many companies are effectively operating without meaningful AI reliability solutions. “AI reliability remains a slogan unless we build a structural ecosystem—training professionals, establishing internal governance, and accumulating technological improvement capabilities,” he said, adding that a true AI reliability market has yet to form domestically.
In response, Think4BL is focusing on changing perceptions within Korea while supplying reliability-focused technologies to overseas markets where trust is more highly valued. “Over the past year, we have conducted nationwide seminars and training sessions for public-sector practitioners to raise awareness of AI reliability,” Park said.
◇ Education, Evaluation, and Data: The Roadmap Ahead
Park also outlined Think4BL’s business roadmap for next year, centered on three pillars: education, evaluation, and data.
First is the training of AI controller professionals. “Next year, we plan to further expand AI reliability, safety, and risk management education across universities, public institutions, and the National Human Resources Development Institute,” he said. “Countries such as Thailand, Uzbekistan, Vietnam, and Indonesia have also shown interest in adopting these educational programs.”
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