Ai在设备风控场景的落地

11A pro-innovation approach to AI regulationcreates a range of new security risks to individuals,organisations,and critical infrastructure.43 Without government action,AI could cause and amplify discrimination that results in,for example,unfairness in the justice system.44 Similarly,without regulatory oversight,AI technologies could pose risks to our privacy and human dignity,potentially harming our fundamental liberties.45 Our regulatory intervention will ensure that AI does not cause harm at a societal level,threatening democracy46 or UK values.Box 1.2:Illustrative AI risksThe patchwork of legal frameworks that currently regulate some uses of AI may not sufficiently address the risks that AI can pose.The following examples are hypothetical scenarios designed to illustrate AI’s potential to create harm.Risks to human rightsGenerative AI is used to generate deepfake pornographic video content,potentially damaging the reputation,relationships and dignity of the subject.Risks to safetyAn AI assistant based on LLM technology recommends a dangerous activity that it has found on the internet,without understanding or communicating the context of the website where the activity was described.The user undertakes this activity causing physical harm.Risks to fairness47An AI tool assessing credit-worthiness of loan applicants is trained on incomplete or biased data,leading the company to offer loans to individuals on different terms based on characteristics like race or gender.Risks to privacy and agencyConnected devices in the home may constantly gather data,including conversations,potentially creating a near-complete portrait of an individual's home life.Privacy risks are compounded the more parties can access this data.Risks to societal wellbeing

Indeed,the pace of change itself can be unsettling.Some fear a future in which AI replaces or displaces jobs,for example.Our white paper and our vision for a future AI-enabled country is one in which our ways of working are complemented by AI rather than disrupted by it.In the modern world,too much of our professional lives are taken up by monotonous tasks–inputting data,filling out paperwork,scanning through documents for one piece of information and so on.AI in the workplace has the potential to free us up from these tasks,allowing us to spend more time doing the things we trained for–teachers with more time to teach,clinicians with more time to spend with patients,police officers with more time on the beat rather than behind a desk–the list goes on.Indeed,since AI is already in our day-to-day lives,there are numerous examples that can help to illustrate the real,tangible benefits that AI can bring once any risks are mitigated.Streaming services already use advanced AI to recommend TV shows and films to us.Our satnav uses AI to plot the fastest routes for our journeys,or helps us avoid traffic by intelligently predicting where congestion will be on our journey.And of course,almost all of us carry a smartphone in our pockets that uses advanced AI in all sorts of ways.These common devices all carried risks at one time or another,but today they benefit us enormously.That is why our white paper details how we intend to support innovation while providing a framework to ensure risks are identified and addressed.However,a heavy-handed and rigid approach can stifle innovation and slow AI adoption.That is why we set out a proportionate and pro-innovation regulatory framework.Rather than target specific technologies,it focuses on the context in which AI is deployed.This enables us to take a balanced approach to weighing up the benefits versus the potential risks.

制造业正向智能化、无人化迈进，AI Agent在此可充当工业智能体，用于生产决策、设备维护、供应链协调等。一个重要应用是工业设备监控与预防性维护Agent。工厂机器装满传感器，Agent可连续监测震动、电流、温度等，通过模型识别异常模式，在设备故障前发出检修通知。这将大幅减少停机损失和维修成本。比如，一个化工厂AI监听管道压力和阀门声音，发现异常震颤频率预示阀门将失效，提前安排更换避免事故。这就是自动演化的自愈工厂初步形态。在生产计划上，Agent可实时根据订单和库存调整排产顺序，优化机器调度以最小化切换时间和能耗。供应链管理Agent能追踪原材料运输情况，预测延迟并自动调整采购或替代来源。质量控制中，视觉AI检测产品瑕疵已应用（如相机+AI筛选食品、零件）。未来Agent会综合生产参数和检验结果，追溯缺陷原因并优化工艺参数。协作机器人领域，Agent可以让多台机器人和人工组成弹性生产线。Agent基于订单优先级指挥机器人配置工站、人机协同，达到最优产出。这类似多智能体系统调度。仓储物流里，Agent可以管理AGV(搬运机器人)和机械臂拣货，规划路径避免碰撞，24小时不停运转。产品设计也能引入AI助理，帮工程师快速检索设计规范、推荐材料和结构方案，甚至自动生成CAD草图。建筑工程上，Agent可调度工人、机械、材料进场顺序，优化建筑工期。能源管理方面，Agent在工厂调控空调照明，结合电价预测降低能耗成本。总的来说，工业Agent将实现生产无人化、决策数据化、响应实时化，以前需人盯或周期手动调整的环节将自动、智能地运转起来。