'AI Bias in Virtual Training Content Is an Ethical Challenge'

"AI bias and fairness are ethical challenges we must absolutely resolve." Inosimulation CEO Cho Jun-hee delivered a speech on ethical issues arising from virtual training content and AI technology advancement at the "2024 Global Metaverse Conference (GMC)" held at aT Center, Yangjae, Seoul on October 18. The conference discussed directions for Korea's metaverse ecosystem and strategies for building government and private sector regulation and ethical ecosystems. CEO Cho emphasized that virtual testing is no longer optional but essential for autonomous vehicle development, comparing it to military training: "Because we cannot conduct actual combat in real battlefields, simulator utilization through virtual reality is growing — autonomous vehicles are the same, and virtual training content must realistically represent all traffic situations that occur in the real world." He noted that autonomous vehicle development and verification through only real road testing cannot resolve legal/policy constraints, safety/reliability technical limitations, and consumer acceptance issues — virtual testing enables real-time traffic situation simulation in a virtual space similar to reality, ensuring safety. "To secure 95% reliability for autonomous vehicles, 600 million kilometers of driving distance is required — virtual testing is essential to achieve this goal." He added that multi-modal generative AI is expected to "revolutionarily reduce time and cost in content development." AI bias discussion: training data collected from specific demographics, geographies, or scenarios creates AI systems that perform poorly or unfairly for underrepresented groups; in virtual training for autonomous driving, biased training scenarios can embed dangerous assumptions about pedestrian behavior, road conditions, or edge cases that disproportionately harm vulnerable populations; addressing AI bias in virtual training content requires deliberate diversity in scenario design, regular bias auditing, and inclusive development teams.