018_具身人工智能的伦理与社会影响：从人机关系到全球治理的多维思考

# 具身AI隐私保护框架示例
class EmbodiedAIPrivacyFramework:
    def __init__(self, agent_id, privacy_policy):
        self.agent_id = agent_id
        self.privacy_policy = privacy_policy
        self.sensor_permissions = {}
        self.data_processing_rules = {}
        self.privacy_controls = {}
        self.compliance_logs = []
    
    def configure_sensor_privacy(self, sensor_config):
        """
        配置传感器隐私设置
        参数:
            sensor_config: 包含各传感器隐私设置的配置对象
        """
        for sensor_type, config in sensor_config.items():
            self.sensor_permissions[sensor_type] = {
                "recording_enabled": config.get("recording_enabled", False),
                "data_storage_duration": config.get("data_storage_duration", 0),
                "anonymization_level": config.get("anonymization_level", "high"),
                "user_consent_required": config.get("user_consent_required", True),
                "privacy_zones": config.get("privacy_zones", [])
            }
        
        self._log_compliance_event("sensor_privacy_configured", sensor_config)
    
    def set_data_processing_rules(self, processing_rules):
        """
        设置数据处理规则
        参数:
            processing_rules: 定义数据如何被处理的规则集合
        """
        self.data_processing_rules = processing_rules
        self._log_compliance_event("data_processing_rules_set", processing_rules)
    
    def enable_privacy_control(self, control_type, control_params):
        """
        启用特定的隐私控制机制
        参数:
            control_type: 控制类型（如 "privacy_mode", "consent_management" 等）
            control_params: 控制参数
        """
        self.privacy_controls[control_type] = {
            "enabled": True,
            "parameters": control_params,
            "last_updated": datetime.now().isoformat()
        }
        
        self._log_compliance_event("privacy_control_enabled", 
                                 {"control_type": control_type, "parameters": control_params})
    
    def process_sensor_data(self, sensor_type, raw_data, context):
        """
        处理传感器数据，应用隐私保护措施
        参数:
            sensor_type: 传感器类型
            raw_data: 原始传感器数据
            context: 采集数据的上下文信息
        返回:
            处理后的隐私保护数据
        """
        # 检查传感器权限
        if sensor_type not in self.sensor_permissions:
            raise ValueError(f"未知的传感器类型: {sensor_type}")
        
        permissions = self.sensor_permissions[sensor_type]
        
        # 检查是否在隐私区域
        if self._is_in_privacy_zone(context, permissions["privacy_zones"]):
            return self._apply_max_privacy(raw_data, sensor_type)
        
        # 检查是否需要用户同意
        if permissions["user_consent_required"] and not self._has_user_consent(context):
            return self._apply_max_privacy(raw_data, sensor_type)
        
        # 应用匿名化处理
        anonymized_data = self._apply_anonymization(raw_data, 
                                                  permissions["anonymization_level"])
        
        # 记录合规事件
        self._log_compliance_event("sensor_data_processed", {
            "sensor_type": sensor_type,
            "anonymization_level": permissions["anonymization_level"],
            "timestamp": datetime.now().isoformat()
        })
        
        return anonymized_data
    
    def _is_in_privacy_zone(self, context, privacy_zones):
        """检查是否在隐私区域内"""
        # 简化实现，实际应根据位置和环境信息确定
        location = context.get("location", {})
        for zone in privacy_zones:
            if self._check_location_in_zone(location, zone):
                return True
        return False
    
    def _check_location_in_zone(self, location, zone):
        """检查位置是否在指定区域内"""
        # 简化实现
        return False
    
    def _has_user_consent(self, context):
        """检查是否有用户同意"""
        return context.get("user_consent", False)
    
    def _apply_anonymization(self, data, level):
        """根据指定级别应用匿名化处理"""
        if level == "high":
            return self._high_level_anonymization(data)
        elif level == "medium":
            return self._medium_level_anonymization(data)
        else:  # low
            return self._low_level_anonymization(data)
    
    def _high_level_anonymization(self, data):
        """高级别匿名化处理"""
        # 实际实现中会进行深度数据脱敏
        return "[高度匿名化数据]"
    
    def _medium_level_anonymization(self, data):
        """中级别匿名化处理"""
        return "[中度匿名化数据]"
    
    def _low_level_anonymization(self, data):
        """低级别匿名化处理"""
        return "[低度匿名化数据]"
    
    def _apply_max_privacy(self, data, sensor_type):
        """应用最大隐私保护"""
        # 在隐私区域或无用户同意时，不收集或高度匿名化数据
        return "[隐私保护模式下的数据]"
    
    def _log_compliance_event(self, event_type, details):
        """记录合规事件"""
        event = {
            "timestamp": datetime.now().isoformat(),
            "agent_id": self.agent_id,
            "event_type": event_type,
            "details": details
        }
        self.compliance_logs.append(event)
    
    def generate_privacy_report(self, time_range=None):
        """
        生成隐私合规报告
        参数:
            time_range: 时间范围过滤器
        返回:
            隐私合规报告
        """
        # 生成报告
        report = {
            "agent_id": self.agent_id,
            "generated_at": datetime.now().isoformat(),
            "privacy_policy": self.privacy_policy,
            "sensor_configuration": self.sensor_permissions,
            "active_privacy_controls": [k for k, v in self.privacy_controls.items() 
                                      if v["enabled"]],
            "compliance_events_count": len(self.compliance_logs)
        }
        
        return report

# 使用示例（需要导入datetime模块）
from datetime import datetime

def example_privacy_framework():
    # 创建隐私框架实例
    privacy_policy = "遵循GDPR和CCPA等隐私法规，保护用户数据安全和隐私"
    privacy_framework = EmbodiedAIPrivacyFramework("robot_001", privacy_policy)
    
    # 配置传感器隐私设置
    sensor_config = {
        "camera": {
            "recording_enabled": True,
            "data_storage_duration": 72,  # 小时
            "anonymization_level": "high",
            "user_consent_required": True,
            "privacy_zones": ["卧室", "浴室"]
        },
        "microphone": {
            "recording_enabled": True,
            "data_storage_duration": 24,
            "anonymization_level": "medium",
            "user_consent_required": True,
            "privacy_zones": ["卧室"]
        },
        "motion_sensor": {
            "recording_enabled": True,
            "data_storage_duration": 48,
            "anonymization_level": "low",
            "user_consent_required": False,
            "privacy_zones": []
        }
    }
    privacy_framework.configure_sensor_privacy(sensor_config)
    
    # 启用隐私控制
    privacy_framework.enable_privacy_control("privacy_mode", {
        "manual_override": True,
        "schedule_based": False,
        "default_level": "high"
    })
    
    # 处理传感器数据
    context = {
        "location": {"room": "客厅"},
        "user_consent": True,
        "timestamp": datetime.now().isoformat()
    }
    
    processed_data = privacy_framework.process_sensor_data("camera", 
                                                          "原始图像数据", 
                                                          context)
    
    # 生成隐私报告
    report = privacy_framework.generate_privacy_report()
    
    print(f"摄像头数据处理结果: {processed_data}")
    print(f"隐私合规事件数量: {report['compliance_events_count']}")
    
    return report