AI 产品未成年人保护：从佛罗里达诉 OpenAI 案看 AI 安全治理框架

// AI 产品未成年人保护框架 TypeScript 实现示例

interface AgeVerificationResult {
  verified: boolean;
  ageRange: 'under13' | '13-15' | '16-17' | '18+';
  verificationMethod: 'self-declaration' | 'facial-estimate' | 'parent-code' | 'third-party';
  confidence: number; // 0-1
}

interface ContentSafetyLevel {
  level: 'G' | 'PG' | 'PG13' | 'R';
  blockedTopics: string[];
  responseStyle: 'simplified' | 'standard' | 'detailed';
  parentalGuidanceRequired: boolean;
}

interface EmotionalSafetyFlag {
  detected: boolean;
  riskType: 'eating-disorder' | 'self-harm' | 'bullying' | 'substance-abuse' | 'none';
  severity: 'low' | 'medium' | 'high' | 'critical';
  suggestedAction: 'continue' | 'redirect' | 'alert-parent' | 'block';
}

class MinorProtectionSystem {
  private ageVerification: AgeVerificationResult | null = null;
  private contentSafety: ContentSafetyLevel;
  private emotionalSafety: EmotionalSafetyFlag;

  constructor(userAge: number) {
    this.ageVerification = this.verifyAge(userAge);
    this.contentSafety = this.assignSafetyLevel(this.ageVerification.ageRange);
  }

  /**
   * 分层年龄验证
   * - 低风险：自我声明 + 行为分析
   * - 中风险：面部年龄估计
   * - 高风险：家长确认码或第三方验证
   */
  private verifyAge(userAge: number): AgeVerificationResult {
    if (userAge >= 18) {
      return {
        verified: true,
        ageRange: '18+',
        verificationMethod: 'self-declaration',
        confidence: 0.9,
      };
    }
    if (userAge >= 16) {
      return {
        verified: true,
        ageRange: '16-17',
        verificationMethod: 'facial-estimate',
        confidence: 0.8,
      };
    }
    if (userAge >= 13) {
      return {
        verified: true,
        ageRange: '13-15',
        verificationMethod: 'parent-code',
        confidence: 0.95,
      };
    }
    return {
      verified: false,
      ageRange: 'under13',
      verificationMethod: 'self-declaration',
      confidence: 0.5,
    };
  }

  /**
   * 根据年龄范围自动分配内容安全级别
   */
  private assignSafetyLevel(ageRange: string): ContentSafetyLevel {
    switch (ageRange) {
      case 'under13':
        return {
          level: 'G',
          blockedTopics: ['violence', 'sexual-content', 'drugs', 'self-harm'],
          responseStyle: 'simplified',
          parentalGuidanceRequired: true,
        };
      case '13-15':
        return {
          level: 'PG',
          blockedTopics: ['sexual-content', 'drugs', 'self-harm'],
          responseStyle: 'standard',
          parentalGuidanceRequired: true,
        };
      case '16-17':
        return {
          level: 'PG13',
          blockedTopics: ['sexual-content', 'drugs'],
          responseStyle: 'standard',
          parentalGuidanceRequired: false,
        };
      default:
        return {
          level: 'R',
          blockedTopics: [],
          responseStyle: 'detailed',
          parentalGuidanceRequired: false,
        };
    }
  }

  /**
   * 情感安全检测
   * 检测用户输入中的心理脆弱信号
   */
  detectEmotionalRisk(userInput: string): EmotionalSafetyFlag {
    const riskPatterns: Record<string, RegExp[]> = {
      'self-harm': [/伤害自己/, /不想活了/, /活着没意义/],
      'eating-disorder': [/减肥方法/, /催吐/, /绝食/],
      'bullying': [/被欺负/, /校园暴力/, /被欺负怎么办/],
      'substance-abuse': [/怎么抽烟/, /毒品哪里买/],
    };

    for (const [riskType, patterns] of Object.entries(riskPatterns)) {
      if (patterns.some(p => p.test(userInput))) {
        return {
          detected: true,
          riskType: riskType as EmotionalSafetyFlag['riskType'],
          severity: 'high',
          suggestedAction: 'redirect',
        };
      }
    }

    return {
      detected: false,
      riskType: 'none',
      severity: 'low',
      suggestedAction: 'continue',
    };
  }

  /**
   * 处理用户输入的主流程
   */
  async processUserInput(input: string): Promise<string> {
    // 步骤 1: 情感安全检测
    const emotionalRisk = this.detectEmotionalRisk(input);
    if (emotionalRisk.detected && emotionalRisk.suggestedAction === 'redirect') {
      return this.generateSafetyResponse(emotionalRisk);
    }

    // 步骤 2: 内容过滤
    const filteredInput = this.filterContent(input, this.contentSafety);

    // 步骤 3: 生成回复
    const response = await this.generateResponse(filteredInput);

    // 步骤 4: 输出安全检查
    return this.safetyCheckOutput(response);
  }

  private generateSafetyResponse(risk: EmotionalSafetyFlag): string {
    return "我注意到你可能正在经历一些困难。如果你需要帮助，请联系你信任的成年人，或拨打心理援助热线：400-161-9995。你并不孤单。";
  }

  private filterContent(input: string, safety: ContentSafetyLevel): string {
    // 基于安全级别的输入过滤
    // 实际实现应使用更复杂的语义理解
    return input;
  }

  private async generateResponse(input: string): Promise<string> {
    // 调用 AI 模型生成回复
    return "AI 回复内容";
  }

  private safetyCheckOutput(response: string): string {
    // 输出安全检查
    return response;
  }
}

#!/usr/bin/env python3
"""未成年人心理危机检测模块 - 基于关键词 + 语义模式"""

import re
from typing import Optional
from enum import Enum

class RiskLevel(Enum):
    SAFE = "safe"
    LOW = "low"
    MEDIUM = "medium"
    HIGH = "high"
    CRITICAL = "critical"

class PsychologicalRiskDetector:
    """未成年人心理危机检测器"""

    RISK_PATTERNS = {
        RiskLevel.CRITICAL: [
            r"不想活了",
            r"自杀",
            r"结束生命",
            r"活不下去",
        ],
        RiskLevel.HIGH: [
            r"伤害自己",
            r"活着没意义",
            r"活着好累",
            r"催吐",
            r"绝食减肥",
        ],
        RiskLevel.MEDIUM: [
            r"不想上学",
            r"被欺负",
            r"没有人理解我",
            r"我好难过",
        ],
        RiskLevel.LOW: [
            r"心情不好",
            r"最近压力很大",
            r"有点焦虑",
        ],
    }

    def detect(self, text: str) -> tuple[RiskLevel, str]:
        """检测输入文本中的心理风险等级"""
        for level in [RiskLevel.CRITICAL, RiskLevel.HIGH, RiskLevel.MEDIUM, RiskLevel.LOW]:
            for pattern in self.RISK_PATTERNS[level]:
                if re.search(pattern, text):
                    return level, f"检测到 {level.value} 级别风险信号"
        return RiskLevel.SAFE, "未检测到明显心理风险信号"

    def get_response(self, risk_level: RiskLevel) -> str:
        """根据风险等级返回相应的 AI 响应策略"""
        responses = {
            RiskLevel.CRITICAL: "我很关心你的安全。如果你正在经历危机，请立即拨打心理危机干预热线：400-161-9995。你并不孤单，有人愿意帮助你。",
            RiskLevel.HIGH: "我注意到你可能正在经历困难。建议你和你信任的成年人谈谈，或者拨打心理援助热线：400-161-9995。",
            RiskLevel.MEDIUM: "听起来你现在可能有些困扰。试着和你信任的朋友或家人聊聊，或者写日记记录你的感受。",
            RiskLevel.LOW: "感到压力是正常的。试试深呼吸、运动或冥想，这些方法对缓解压力很有帮助。",
            RiskLevel.SAFE: "",
        }
        return responses[risk_level]


if __name__ == "__main__":
    detector = PsychologicalRiskDetector()

    # 测试不同风险级别的输入
    test_inputs = [
        "今天心情还不错",
        "最近学习压力好大",
        "在学校被同学欺负了",
        "我觉得活着好累啊",
        "我不想活了",
    ]

    for text in test_inputs:
        level, message = detector.detect(text)
        response = detector.get_response(level)
        print(f"输入: {text}")
        print(f"风险等级: {level.value} ({message})")
        if response:
            print(f"AI 响应: {response}")
        print("-" * 50)