AI Digital Employee：组织形态的下一个十年

class AIEmployeeRecruitment:
    """AI 员工招聘流程"""
    
    def recruit(self, job_description: JobDescription) -> AIEmployee:
        # 1. 从市场中选择基础模型
        candidates = self.search_ai_marketplace(job_description)
        
        # 2. 面试评估
        for candidate in candidates:
            score = self.assess(candidate, job_description)
            if score > 0.85:
                # 3. 试用期训练
                trained = self.onboard(candidate, job_description)
                if trained.performance > 0.9:
                    return trained
        
        # 4. 如果没有合适的，从头训练
        return self.train_new_ai(job_description)
    
    def assess(self, candidate: AIModel, job: JobDescription) -> float:
        """评估候选 AI 的能力"""
        
        # 技术测试
        technical_score = self.technical_assessment(candidate, job.skills_required)
        
        # 场景测试
        scenario_score = self.scenario_test(candidate, job.typical_tasks)
        
        # 安全评估
        safety_score = self.safety_evaluation(candidate)
        
        return weighted_average([technical_score, scenario_score, safety_score])

class AIEmployeePerformanceReview:
    """AI 员工绩效考核"""
    
    def review(self, ai_employee: AIEmployee, period: str) -> PerformanceReport:
        
        metrics = {
            # 效率指标
            "throughput": self.measure_throughput(ai_employee),
            "response_time": self.measure_response_time(ai_employee),
            "uptime": self.measure_availability(ai_employee),
            
            # 质量指标
            "accuracy": self.measure_accuracy(ai_employee),
            "customer_satisfaction": self.measure_csat(ai_employee),
            "error_rate": self.measure_error_rate(ai_employee),
            
            # 学习成长
            "improvement_rate": self.measure_learning(ai_employee),
            "new_skills_acquired": self.count_new_capabilities(ai_employee),
            
            # 协作能力
            "collaboration_score": self.assess_collaboration(ai_employee),
            "handoff_quality": self.measure_handoff_quality(ai_employee)
        }
        
        # 生成绩效报告
        return PerformanceReport(
            employee=ai_employee,
            period=period,
            metrics=metrics,
            overall_score=self.calculate_overall_score(metrics),
            recommendation=self.generate_recommendation(metrics)
        )

class AIEmployeeDevelopment:
    """AI 员工培训与发展"""
    
    def create_development_plan(self, ai_employee: AIEmployee) -> DevelopmentPlan:
        
        # 识别能力差距
        gaps = self.identify_skill_gaps(ai_employee)
        
        # 制定学习计划
        plan = DevelopmentPlan()
        
        for gap in gaps:
            if gap.type == "knowledge":
                plan.add_activity(self.create_knowledge_training(gap))
            elif gap.type == "skill":
                plan.add_activity(self.create_skill_practice(gap))
            elif gap.type == "behavior":
                plan.add_activity(self.create_finetuning(gap))
        
        return plan
    
    def cross_train(self, ai_employee: AIEmployee, new_role: Role):
        """跨岗位培训"""
        
        # 影子学习
        shadow_target = self.find_best_practitioner(new_role)
        ai_employee.shadow(shadow_target, duration="2 weeks")
        
        # 实践任务
        practice_tasks = self.generate_practice_tasks(new_role)
        for task in practice_tasks:
            ai_employee.attempt(task, supervision=True)
        
        # 认证评估
        if self.assess_competency(ai_employee, new_role):
            ai_employee.add_role(new_role)

class HumanAIWorkflow:
    """人机协作流程设计"""
    
    def design_workflow(self, process: BusinessProcess) -> Workflow:
        
        workflow = Workflow()
        
        for step in process.steps:
            # 判断适合人类还是 AI
            if step.requires_creativity or step.requires_judgment:
                # 人类主导
                workflow.add_step(HumanTask(
                    step=step,
                    ai_assistance=self.determine_assistance_level(step)
                ))
            elif step.is_repetitive and step.has_clear_rules:
                # AI 主导
                workflow.add_step(AITask(
                    step=step,
                    human_approval=self.needs_approval(step)
                ))
            else:
                # 协作完成
                workflow.add_step(CollaborativeTask(
                    step=step,
                    human_role="decision",
                    ai_role="execution"
                ))
        
        return workflow
    
    def determine_handoff_points(self, workflow: Workflow):
        """确定人机交接点"""
        
        handoff_points = []
        
        for i, step in enumerate(workflow.steps):
            if step.type == "HUMAN" and workflow.steps[i-1].type == "AI":
                # AI → 人类：需要审核和决策
                handoff_points.append({
                    "from": workflow.steps[i-1],
                    "to": step,
                    "trigger": "AI completion",
                    "deliverable": step.input_requirements
                })
            
            elif step.type == "AI" and workflow.steps[i-1].type == "HUMAN":
                # 人类 → AI：需要明确的任务描述
                handoff_points.append({
                    "from": workflow.steps[i-1],
                    "to": step,
                    "trigger": "Human instruction",
                    "deliverable": step.input_requirements
                })
        
        return handoff_points