셀렉트스타 "AI 안전성, 빅테크도 못 다루는 로컬 리스크 해결이 핵심" - AI타임스
WIT — 언어권별 오해 가능성 탐지
inferred: 국내 AI 서비스 안전 담당자 — 한국어 실패 사례를 정리하고 모델 변경 때마다 회귀시험 및 승인 증빙 반복
Safety staff for Korean AI products manage Korean-specific failure cases—such as honorifics, regional context, and discriminatory language—in spreadsheets. When a model or prompt changes, the process of rerunning prior cases and documenting the results is fragmented, making regression risks easy to miss.
The service organizes an organization's input-output samples and policy criteria into versioned test suites, then records pre- and post-deployment differences and approval evidence in an audit trail. Repeated results and staff risk assessments accumulate into a more specific Korean-language risk baseline for each organization.
| N Novelty | 1-5 | How uncommon the service is in market context. |
| U Urgency | 1-5 | How urgently users need this problem solved now. |
| M Market | 1-5 | Market size and growth potential from proxy indicators. |
| R Realizability | 1-5 | Buildability for a small team with realistic constraints. |
| V Validation | 1-5 | Validation signal quality from competition and demand data. |
| Tech Complexity | / 40 | Difficulty of core implementation stack. |
| Data Availability | / 25 | Practical availability and cost of required data. |
| MVP Timeline | / 20 | Expected time to ship a usable MVP. |
| API Bonus | / 15 | Bonus for viable public API leverage. |
| Competition | / 20 | Signal quality from competitor landscape. |
| Market Demand | / 20 | Demand proxies from search and mention patterns. |
| Timing | / 20 | Fit with current shifts in tech, behavior, and regulation. |
| Revenue Signals | / 15 | Reference evidence for monetization viability. |
| Pick-Axe Fit | / 15 | How well the concept serves participants in a trend. |
| Solo Buildability | / 10 | Practicality for lean-team implementation. |