ai的智能发展不会超越人类

by George Krasadakis

通过乔治·克拉萨达基斯(George Krasadakis)

人工智能，超越炒作 (Artificial Intelligence, beyond the hype)

人工智能正在改变我们的世界，而随之而来的影响是巨大的：在我们的工作方式中，我们生活，协作，决定并充当一个社会。 但是有什么风险，我们如何做好准备？ (AI is changing our world and the impact to come is massive: on the way we work, we live, collaborate, decide and act as a society. But what are the risks and how can we get prepared?)

Artificial Intelligence. One of the most popular technology terms of our time— and very frequently, overused or even misused.

人工智能 。 我们时代最流行的技术术语之一，而且经常被滥用，甚至滥用。

The media loves both the success stories and ‘dystopias’ driven by Artificial Intelligence. Machines replacing human workers, AI exceeding human intelligence, robots taking control and so on.

媒体既喜欢成功故事，也喜欢人工智能驱动的“反乌托邦”。 机器代替人工，人工智能超越人类的智能，机器人掌控一切。

If you look beyond this hype, you will realize that there is a real revolution happening. To understand the potential of AI, just examine the recent advances in fields like Deep Learning and their applications in domains such as Computer Vision and Natural Language Processing.

如果您不仅仅关注这种炒作，您将意识到正在发生一场真正的革命。 要了解AI的潜力，只需查看深度学习等领域的最新进展及其在计算机视觉和自然语言处理等领域的应用。

There is a massive disruption in progress — powered by a combination of technologies, enabling machines to make sense of massive volumes of data and perform cognitive functions.

正在进行的大规模中断-由多种技术共同驱动，使机器能够理解大量数据并执行认知功能。

AI is changing our world and the impact to come is massive: on the way we work, we live, collaborate, decide and act as a society.

人工智能正在改变我们的世界，而随之而来的影响是巨大的：在我们的工作方式中，我们生活，协作，决定并充当一个社会。

1.人工智能，定义 (1. Artificial Intelligence, defined)

Artificial Intelligence can be defined as the technology enabling systems to encapsulate cognitive functions along with adaptive and learning capabilities — leading to self-improvement.

人工智能可以定义为使系统能够封装认知功能以及自适应和学习功能的技术，从而实现自我完善。

AI-powered systems can capture and ‘understand’ their environment and make optimal, real-time decisions towards specific objectives.

基于AI的系统可以捕获和“理解”其环境，并针对特定目标做出最佳的实时决策。

As a characteristic example of AI, ‘Computer Vision’ enables systems to ‘see’ via sophisticated algorithms. These are trained to identify a wide range of entities such as landscapes, persons and objects in a picture or video.

作为AI的典型示例，“计算机视觉”使系统能够通过复杂的算法“查看”。 这些经过训练可以识别各种各样的实体，例如图片或视频中的风景，人物和物体。

In another example of applied AI, ‘Natural Language Processing’ technologies enable interaction with a machine based on free-form, natural, speech.

在应用的AI的另一个示例中，“自然语言处理”技术支持与基于自由形式，自然语音的机器进行交互。

NLP and related technologies can ‘understand’ natural speech and respond in a meaningful way. As soon as the machine extracts the context of the ‘natural speech’ request, it synthesizes the right response which is also served back to the user as ‘natural speech’.

NLP和相关技术可以“理解”自然语言并以有意义的方式做出响应。 机器一提取“自然语音”请求的上下文，就会合成正确的响应，该响应也作为“自然语音”回馈给用户。

The rapid progress of AI is empowered by streams of data on major human activities. These include online communication, social interaction, device usage, searches, content consumption and IoT data streams — to name only a few.

重大人类活动的数据流推动了AI的快速发展。 其中包括在线交流，社交互动，设备使用，搜索，内容消耗和IoT数据流-仅举几例。

To make sense of these vast amounts of complex data, AI systems leverage the power of cloud computing and specialized machine learning algorithms. World-scale data centres, with huge, labelled data sets are being used for training AI algorithms in performing certain cognitive functions.

为了理解这些大量的复杂数据，人工智能系统利用了云计算和专门的机器学习算法的功能。 具有大规模，标记数据集的世界级数据中心被用于训练AI算法执行某些认知功能。

2.最新技术 (2. The state of the art)

算法现在可以“看到” (Algorithms can now ‘see’)

The ability for a computer to ‘see’ is an astonishing achievement. AI-powered systems can ‘understand’ the context of an image or a video in impressive level of detail. They can identify an expanding set of entities — such as persons, named individuals, cars, houses, streets, trees and more — with increasing levels of success.

电脑“看到”的能力是一个了不起的成就。 基于AI的系统可以以令人印象深刻的细节“理解”图像或视频的上下文。 他们可以确定不断扩大的实体集，例如人物，已命名的人物，汽车，房屋，街道，树木等，它们的成功程度不断提高。

Given an image or video, algorithms can estimate additional properties such as the number of persons in the picture, their gender, age or even their emotional state.

给定图像或视频，算法可以估计其他属性，例如图片中的人数，性别，年龄甚至情绪状态。

You can simply submit a family photo to one of the commercially available cognitive services, and get in milliseconds a response with the persons identified, their gender, age and the dominant emotions. An object in a photo can also be identified. For example, AI can recognize a car and also its maker and model. It can then tag it for improved searching, grouping and discoverability.

您只需将全家福照片提交到一种可商购的认知服务，然后在几毫秒内得到所识别人员，其性别，年龄和主导情绪的回应。 照片中的物体也可以被识别。 例如，人工智能可以识别汽车及其制造商和型号。 然后，它可以标记它以改善搜索，分组和发现能力。

In the near future, algorithms will be able to infer even the situation implied — such as a kids party, a sports event, a business conference or a random arrangement of people in a park.

在不久的将来，算法将能够推断出所暗示的情况 ，例如孩子们的聚会 ， 体育赛事 ， 商务会议或公园里人们的随意安排。

The possible applications of computer vision are impressive. From autonomous cars which can ‘see’ in 360 and understand their environment and its dynamics in real-time, to special applications like the Seeing AI by Microsoft — a prototype system helping people who are visually impaired or blind to understand their environment!

计算机视觉的可能应用令人印象深刻。 从可以在360中“看到”并实时了解其环境及其动态的自动驾驶汽车，到特殊的应用程序，例如Microsoft的Seeing AI ，这是一个原型系统，可以帮助有视觉障碍或失明的人们了解他们的环境！

Computer vision is making huge steps, with massive applications in autonomous cars, navigation, robotics, pattern recognition, medical diagnosis and more. AI systems keep learning, and they learn fast.

计算机视觉正迈出巨大的步伐，在无人驾驶汽车，导航，机器人技术，模式识别，医学诊断等领域得到了广泛的应用。 人工智能系统不断学习，而且学习速度很快。

Check this article for more on the latest trends in AI.

查看本文以获取有关AI最新趋势的更多信息。

与“机器”的对话 (The dialogue with the ‘machine’)

A short interaction with Amazon Alexa, Cortana, Siri or Google Assistant is sufficient to realize the huge progress of Natural Language Processing technologies.

与Amazon Alexa，Cortana，Siri或Google Assistant的短暂交互足以实现自然语言处理技术的巨大进步。

Microsoft and IBM announced that their NLP technologies perform at the same level (or better) compared to professional transcribers in processing discussions ranging from sports to politics

微软和IBM宣布，他们的NLP技术在处理从体育到政治的各种讨论中，与专业转录员相比具有相同的水平(或更好)

Google recently demonstrated Duplex, its digital assistant technology, which is able to complete certain tasks via a natural conversational experience. For example, it can arrange a meeting or appointment via a free-form dialogue with a human.

Google最近展示了其数字助理技术Duplex ，该技术能够通过自然的对话体验来完成某些任务。 例如，它可以通过与人进行自由形式的对话来安排会议或约会。

Digital assistants will become more and more intelligent, contextual and proactive.

数字助理将变得越来越聪明，具有关联性和主动性。

At some point in the not so distant future, your digital assistant will respond naturally, in a conversational mode and possibly with a style, attitude and humor matching your personality and your current mood.

在不远的将来的某个时刻， 您的数字助理将以对话方式自然响应 ，并可能以与您的个性和当前情绪相匹配的风格，态度和幽默感进行响应 。

Digital assistants continuously learn using each single interaction with the user. They better match the user’s explicitly stated or implicitly identified preferences. At some point in time, DAs will become proactive and autonomous by seamlessly leveraging deep knowledge about the user, signals from user’s environment and global trends and dynamics.

数字助理通过与用户的每次交互不断学习。 它们更好地匹配用户的明确声明或隐式识别的首选项。 在某个时间点，DA将通过无缝地利用有关用户的深刻知识，来自用户环境以及全球趋势和动态的信号来变得主动和自治。

3.受人工智能影响的行业 (3. Industries to be impacted by Artificial Intelligence)

AI is already impacting our socioeconomic system in many ways. We have entered a phase of drastic transformation of markets, businesses, education, government, social welfare systems, companies, employment models and social structures. All will all be soon re-shaped as the result of intelligent technologies and automation.

人工智能已经在许多方面影响着我们的社会经济系统。 我们已经进入了市场，企业，教育，政府，社会福利系统，公司，就业模式和社会结构的急剧转变阶段。 智能技术和自动化的结果将很快改变所有人的命运。

The massive adoption of AI will fundamentally change all industries, as summarized below.

人工智能的大规模采用将从根本上改变所有行业，如下所述。

运输系统 (Transportation systems)

This sector is going through a radical transformation. Fully autonomous cars will soon be a reality. They will be safer, more efficient and more effective. Autonomous trucks, smart containers, driver-less taxis and smart cities are just some examples of the reality to come for the transportation industry.

这个部门正在经历根本性的转变。 全自动驾驶汽车将很快成为现实。 他们将更加安全，高效和高效。 无人驾驶卡车，智能集装箱，无人出租车和智能城市只是运输行业即将到来的现实例子。

AI in transportation will drive massive changes, not only to the vehicles, but also to the entire ecosystem — from taxi services to e-commerce and package delivery services.

运输业中的人工智能将推动巨大的变化，不仅是车辆，还将是整个生态系统-从出租车服务到电子商务和包裹递送服务。

Consumer habits will be severely impacted, with a shift from owning a car to consuming car services on demand.

消费者习惯将受到严重影响，从拥有汽车转变为按需消费汽车服务 。

The cost of a vehicle as a service will be significantly lower due to, among other factors, the capability of better utilization of the cars by the company operating the service.

由于其他因素，运营服务的公司能够更好地利用汽车，因此，汽车即服务的成本将大大降低。

Entire transportation networks consisting of fleets of autonomous cars will be orchestrated by AI algorithms to best adapt in real-time, to demand, traffic and other conditions. This will transform the way people commute along with the way cities expand and grow.

人工智能算法将对由无人驾驶汽车组成的整个运输网络进行编排，以最佳地实时适应需求，交通和其他条件。 这将改变人们的通勤方式，以及城市的扩张和发展方式。

For example, the new era of cheaper, faster and safer transportation with autonomous vehicles, might trigger a de-urbanization trend — especially if you consider that the time spent in autonomous vehicles can be fully productive with the capabilities of a modern office.

例如 ，使用自动驾驶汽车进行更便宜，更快速，更安全的运输的新时代可能会引发去城市化的趋势-特别是如果您考虑到在自动驾驶汽车上花费的时间可以充分利用现代化办公室的功能来提高生产力。

电子商务 (Electronic commerce)

Customer experience is becoming smarter with advanced, AI-powered personalization, dynamic pricing and offer generation.

通过先进的，人工智能支持的个性化，动态定价和优惠生成，客户体验变得越来越智能。

Fulfillment centers become more automated — with robots navigating the space to collect products and execute customer orders — in some cases, autonomously.

配送中心变得更加自动化-在某些情况下，机器人可以自动导航到收集产品和执行客户订单的空间。

Driver-less drones and cars could have a role in the last part of the delivery process. As centralized intelligence will orchestrate the entire processes, typical sales processes, channels, networks of physical stores are becoming less important — thus disrupting the industry.

无人驾驶无人机和汽车可能会在交付过程的最后阶段发挥作用。 由于集中式智能将统筹整个流程，因此实体店的典型销售流程，渠道，网络变得越来越不重要，从而扰乱了整个行业。

金融服务 ， 保险 (Financial services, insurance)

Any sector requiring significant amount of data processing and content handling will also benefit from AI.

任何需要大量数据处理和内容处理的行业也将从AI中受益。

Financial institutions will automate significant processes regarding transaction validation, fraud identification, stock trading, recommendation and advisory services.

金融机构将使有关交易验证，欺诈识别，股票交易，推荐和咨询服务的重要流程实现自动化。

Insurance companies will leverage the vast amounts of data available and predictive and machine learning technologies, to get better risk estimations. As a result, they will be in position to offer better products, matching the exact needs of a certain customer.

保险公司将利用可用的大量数据以及预测和机器学习技术来获得更好的风险估计。 结果，他们将能够提供更好的产品，满足特定客户的确切需求。

Car insurance companies will also be significantly impacted by the adoption of smart, driver-less cars.

汽车保险公司还将因采用智能无人驾驶汽车而受到重大影响。

国家和公民服务 (The State and Citizen Services)

AI can have a great impact in eliminating bureaucracy, improving citizen services, governance and social programmes.

人工智能可以在消除官僚主义，改善公民服务，治理和社会计划方面产生巨大影响。

法律服务 (Legal services)

Even more traditional professions which are built on top of strong relationships, such as legal professions, will be re-defined by AI. Typical support services in a legal context, deal with document handling, classification, discovery, summarization, comparison and knowledge management — tasks where AI agents already excel.

AI将重新定义建立在牢固关系之上的更多传统专业，例如法律专业。 在法律背景下的典型支持服务涉及文件处理，分类，发现，摘要，比较和知识管理，这是AI代理已经擅长的任务。

产品开发 (Product development)

AI introduces new capabilities changing the typical product development process — for digital or physical products. With the general availability of advanced cognitive technologies (cloud-based commercial AI offerings via easy-to-consume APIs) and the low-cost integration scenarios, the AI-powered opportunities for innovation increase exponentially.

人工智能引入了新功能，改变了典型的产品开发流程-数字或物理产品。 随着高级认知技术的普遍普及(通过易用的API提供基于云的商业AI产品)和低成本的集成方案，以AI为动力的创新机会呈指数增长。

Commercial cognitive APIs and the cloud make it easy for software developers to build cognitive apps, powered by advanced AI capabilities. Physical product manufacturing processes can also benefit from AI-powered production lines, quality control systems and continuous improvement processes. Products will soon be built in totally different ways; and they will be connected and intelligent.

商业认知API和云使软件开发人员能够轻松构建由高级AI功能提供支持的认知应用。 物理产品制造流程也可以从AI驱动的生产线，质量控制系统和持续改进流程中受益。 产品很快将以完全不同的方式制造； 他们将被连接和智能化。

教育 (Education)

The overall education system will be dramatically improved by AI on top of world-scale digitized content, data and scientific and general knowledge.

AI将在世界规模的数字化内容，数据以及科学和常识的基础上极大地改善整个教育系统。

Intelligent education agents will be capturing the needs of the student to synthesize optimal personalized educational programs — matching the intent of the student, the right level, pace, preferred types of content and other parameters.

聪明的教育代理人将抓住学生的需求， 以综合最佳的个性化教育计划 -匹配学生的意图，正确的水平，速度，内容的偏好类型和其他参数。

In another scenario, AI-powered apps will be able to recommend education opportunities and personalized educational content, proactively — depending on the current state of user’s career, education level and previous experiences.

在另一种情况下，基于AI的应用程序将能够主动推荐教育机会和个性化的教育内容，具体取决于用户职业的当前状态，教育水平和以前的经验。

This could take the form of an always-on, intelligent ‘education adviser’, discovering the right learning opportunities for each user.

这可以采取永远在线，智能的“教育顾问”的形式，为每个用户发现正确的学习机会。

4.关注点 (4. The concerns)

There are serious concerns and unanswered questions regarding the social, political and ethical implications of massive adoption of AI.

对于大规模采用人工智能的社会，政治和道德影响，存在严重的关切和未解决的问题。

For instance, the ‘intelligent automation’ which can be achieved at scale by using Artificial Intelligence, is expected to transform the way we work and the skills in demand. Certain roles will become obsolete and some professions will eventually disappear.

例如，通过使用人工智能可以实现大规模的“智能自动化”，有望改变我们的工作方式和所需的技能。 某些角色将过时，某些职业最终将消失。

致命的自主武器 (Lethal Autonomous Weapons)

The concept of an autonomous machine is impressive. Think of an autonomous car, which can capture its environment and dynamics and make real-time decisions, to achieve a predefined objective — move from point A to B — under certain constraints.

自主机器的概念令人印象深刻。 考虑一下自动驾驶汽车，它可以捕获其环境和动态并做出实时决策，以实现预定义的目标-在某些约束下从A点移动到B点。

In a military context though, this autonomy in decision-making is frightening: the so called Lethal Autonomous Weapons, refer to futuristic robotic systems, which could hit targets without human intervention or approval.

不过，在军事环境中，这种决策自主权令人恐惧：所谓的“致命自主武器”指的是未来派机器人系统，无需人工干预或批准，即可袭击目标。

But, who is controlling the design, operation and target assignment to such ‘killer robots’? How such a robot will be able to understand the nuances regarding a complex situation and make life-threatening decisions? And many more.

但是，谁来控制此类“杀手机器人”的设计，操作和目标分配？ 这样的机器人将如何理解复杂情况下的细微差别并做出危及生命的决策？ 还有很多。

偏见的风险和透明度的需求 (The risk of bias and the need for transparency)

AI systems learn by analyzing huge volumes of data and they keep adapting through continuous modelling of interaction data and user-feedback.

人工智能系统通过分析大量数据来学习，并且它们通过对交互数据和用户反馈进行连续建模来保持适应性。

How can we ensure that the initial training of the AI algorithms is unbiased? What if a company introduces bias via the training data set (intentionally or not) in favor of particular classes of customers or users?

我们如何确保AI算法的初始训练没有偏见？ 如果公司通过培训数据集(有意或无意)引入偏向特定客户或用户类别的偏见怎么办？

For instance, what if the algorithm responsible for identifying talented candidates from a pool of CVs, has inherited known or unknown biases, leading, for example, to diversity-related issues?

例如，如果负责从简历集中识别有才能的候选人的算法继承了已知或未知的偏见，例如导致了与多样性相关的问题？

We must ensure that such systems are transparent regarding their decision-making processes. This is key to allow better handling of edge cases, while supporting the general understanding and acceptance by the wider audience and the society.

我们必须确保此类系统的决策过程透明。 这是在更好地处理边缘案件的同时支持更广泛的受众和社会的普遍理解和接受的关键。

获取数据，知识，技术。 (Access to data, knowledge, technology.)

In our interconnected world, a relatively small number of companies are collecting vast amounts of data. Access to this data would allow an accurate replay of our day-to-day life in terms of activities, interactions and explicitly stated or implicitly identified interests. Somebody with access to this data would ‘know’ our mobility history, our online search and social media activity, chats, emails and other online micro-behaviors and interactions.

在我们这个互联的世界中，相对少数的公司正在收集大量数据。 访问这些数据将使我们能够根据活动，互动和明确陈述或隐含的兴趣来准确重述我们的日常生活。 有权访问此数据的人会“知道”我们的出行历史，我们的在线搜索和社交媒体活动，聊天，电子邮件以及其他在线微行为和互动。

An AI system will be able to ‘understand’ any online user — in terms of interests, daily habits and future needs; it could derive impressive estimations and predictions, ranging from purchasing interests to user’s emotional state.

一个AI系统将能够“了解”任何在线用户-的兴趣 ， 日常习惯和未来需求 ； 它可以得出令人印象深刻的估计和预测，从购买兴趣到用户的情绪状态 。

If you think of this AI output at scale — analyzing data at the population level — these predictions and insights could describe the synthesis, state and dynamics of an entire population.

如果您大规模地考虑一下AI的输出-在人口水平上分析数据-这些预测和见解可以描述整个人口的综合，状态和动态。

This would obviously provide extreme power to those controlling such systems over this wealth of data. Just recall the Cambridge Analytica case. The data for a given individual user might be of low value, but when analysed at scale — for a sufficiently large group of users, with advanced analytical and inference models — it could drive massive socio-political influence.

显然，这将为控制此类系统的用户提供如此强大的功能。 只要回想一下剑桥分析案。 给定单个用户的数据可能价值不高，但是如果对大量用户(具有先进的分析和推理模型)进行大规模分析，则可能会产生巨大的社会政治影响力。

隐私权 (The right to privacy)

When you consider the possibility of unauthorized access to one’s online history (or other) data, the right to privacy is obviously at risk. But even in the case of an offline user — somebody who has deliberately decided to stay ‘disconnected’ — the right to privacy is still under threat.

当您考虑到未经授权访问某人的在线历史(或其他)数据的可能性时，隐私权显然受到威胁。 但是，即使是离线用户(有人故意决定保持“断开连接”)，隐私权仍然受到威胁。

Imagine a disconnected user (no smartphones or other devices aware of user’s location) moving through the ‘smart city’ of the future. A walk through a couple of major streets would be enough for the network of security cameras to capture user’s trails and possibly identify them via reliable facial recognition, against a centralized data store. There are obvious big questions on who has access to this information and under what conditions.

想象一下，一个断开连接的用户(没有智能手机或其他知道用户位置的设备)正在穿越未来的“智能城市”。 穿过几条主要街道就足以使安全摄像机网络捕获用户的踪迹，并有可能通过可靠的面部识别来针对集中式数据存储区进行识别。 关于谁有权访问此信息以及在什么条件下存在明显的重大问题。

未经授权的访问和控制 (Unauthorized access and control)

Security and access control is a critical aspect. If somebody compromises a smart system (for instance, an autonomous car) the consequences can be disastrous. Security of intelligent, connected systems and machines against unauthorized access is a top priority.

安全和访问控制是至关重要的方面。 如果有人破坏了智能系统(例如自动驾驶汽车)，后果可能是灾难性的。 安全，智能的互联系统和机器免受未经授权的访问是当务之急。

技术失业 (Technological unemployment)

This is defined as the unemployment ‘explained’ by the application of new technologies — in the AI era it refers to the jobs replaced by intelligent automation.

这被定义为通过应用新技术“解释”的失业-在AI时代，它指的是被智能自动化取代的工作。

In the years to come, we will witness significant changes in the workforce and the markets. Roles and jobs will become obsolete, industries will be radically transformed, employment models and relationships will be redefined.

在未来的几年中 ，我们将见证劳动力和市场的重大变化。 角色和工作将变得过时，行业将发生根本性转变，就业模式和关系将被重新定义。

For instance, tasks and activities related to customer care/call centres, document management, content moderation are increasingly based on technology and intelligent systems.

例如，与客户服务/呼叫中心，文档管理，内容审核相关的任务和活动越来越多地基于技术和智能系统。

The same is true for roles related to operation and support of production lines and factories. Humans are being replaced by smart robots which can safely navigate the space, find and move objects (such as products, parts or tools) and perform complex assembling operations.

与生产线和工厂的运营和支持相关的角色也是如此。 智能机器人正在取代人类，这些机器人可以安全地导航空间，查找和移动物体(例如产品，零件或工具)并执行复杂的组装操作。

But AI proves to be very effective in handling even more complex activities — those requiring processing of multiple signals, data streams and accumulated knowledge in real time. A characteristic case is the autonomous vehicles which can capture and ‘understand’ their environment and its dynamics — they can ‘see’, decide and act in real-time. Professional drivers (taxi, trucks and more) will see the demand for their skill-set dropping rapidly.

但是事实证明，人工智能在处理更复杂的活动方面非常有效，这些活动需要实时处理多个信号，数据流和积累的知识。 一个典型的例子是自动驾驶汽车，它们可以捕获和“了解”其环境及其动态变化-他们可以“看到”，实时做出决定并采取行动。 专业驾驶员(出租车，卡车等)将看到他们对技能的需求Swift下降。

道德，社会责任和艰难的决定 (Ethics, social responsibility and difficult decisions)

AI enables optimal decisions in a real-time mode. Although in most of the cases the optimal decision is objectively determined and generally accepted, there are several examples raising ethical and moral issues.

AI可在实时模式下实现最佳决策。 尽管在大多数情况下，最佳决策是客观地确定并被普遍接受的，但还是有一些例子提出了道德和道德问题。

For instance, an autonomous car which knows that it is about to hit a pedestrian, must decide if it will try to avoid the sensitive pedestrian via a risky (to its passengers) manoeuvre. And this needs to be decided in milliseconds.

例如，知道将要撞到行人的自动驾驶汽车，必须决定是否将通过有风险的(对其乘客)操纵来避开敏感的行人。 这需要以毫秒为单位确定。

The logic behind these critical decisions, must be predefined, well-understood and accepted. At the same time, the detailed history of activity and decisions of the autonomous car must be accessible and available for analysis — under certain data protection rules.

这些关键决策背后的逻辑必须预先定义，充分理解并接受。 同时，在某些数据保护规则下，自动驾驶汽车的详细活动历史和决策必须可访问并可供分析。

力量不平衡和数据控制 (Disproportional power and control over data)

Technology companies are investing heavily in artificial intelligence, both at the scientific/engineering and also at the commercial and product development level.

科技公司在科学/工程学以及商业和产品开发级别都在人工智能方面进行了大量投资。

These corporations have an unmatched advantage when compared to any ambitious competitor out there. The massive datasets describing a wide range of human activity (searches, communication, content creation, social interaction and more), in many different formats (text, images, audio, video).

与其他雄心勃勃的竞争对手相比，这些公司具有无与伦比的优势。 大量的数据集以许多不同的格式(文本，图像，音频，视频)描述了各种各样的人类活动(搜索，交流，内容创建，社交互动等)。

In an effort to retain their leading market positions, tech corporations tend to acquire those promising tech/AI startups disrupting the market. This could lead to super-powers, with a unique setup of AI technologies over massive amounts of accumulated user and machine data.

为了保持其市场领先地位，技术公司倾向于收购那些有前途的技术/人工智能创业公司，以扰乱市场。 通过独特的AI技术设置，可以积累大量的用户和机器数据，从而带来超能力。

5.诺言 (5. The promise)

In the context of Internet of Things (IoT), billions of connected devices continuously send events, operation and other data, which are then processed by advanced Big Data, Machine Learning and Artificial Intelligence technologies.

在物联网(IoT)的背景下，数十亿个互联设备不断发送事件，操作和其他数据，然后由高级大数据，机器学习和人工智能技术对其进行处理。

This wealth of data, combined with the increasing ability to make sense of massive, complex data sets, is creating unprecedented opportunities for improvement across health, lifestyle, transportation, education and practically every human activity. Under certain assumptions, this technological revolution, will lead to a new era of prosperity, creativeness and well-being.

如此丰富的数据 ，再加上对海量复杂数据集的理解能力的增强，为健康，生活方式，交通，教育和几乎所有人类活动的改善创造了前所未有的机会。 在某些假设下，这场技术革命将引领繁荣，创新和福祉的新时代。

And yes, technological unemployment is a risk.

是的，技术失业是一种风险。

But in most of cases, Artificial Intelligence will play a supportive role to humans — empowering the human factor to perform better in handling complex and critical situations which require judgement and creative thinking.

但是在大多数情况下， 人工智能将对人类起到辅助作用 -赋予人类因素以更好地处理需要判断和创造性思维的复杂和关键情况的能力。

In the future, humans will no more need to perform routine, limited-value, jobs. The workforce and the underlying employment models, will move from long-term, full-time employment agreements, to flexible, selective offering of services.

将来，人类将不再需要执行常规的，有限价值的工作。 劳动力和基本的雇佣模式将从长期的全职雇佣协议转变为灵活的，有选择的服务。

There will be a stream of new business opportunities empowering the culture of entrepreneurship, creativeness and innovation.

将会出现一系列新的商机，赋予企业家精神，创造力和创新文化。

In parallel, numerous new roles and specializations will be created — focusing on technology and science, allowing people to free-up time from monotonous, low-value work, towards more creative activities.

同时，还将创建许多新的角色和专业化-专注于技术和科学，使人们将时间从单调的低价值工作中解放出来，投入更多的创造性活动。

Education systems will evolve to personalized programs and a life-learning mode. Innovation and creative thinking will be empowered by intelligent access of world’s accumulated knowledge, ideas and creative energy.

教育系统将演变为个性化的课程和生活学习模式 。 通过智能地访问世界上积累的知识，思想和创造力，将能够实现创新和创造性思维。

With the applications of AI in the Transportation industry, we will witness a significant reduction of accidents and fatalities on the roads. Moreover, people will benefit from lower transportation costs and increased level of service.

随着AI在交通运输行业的应用，我们将目睹道路上事故和死亡人数的显着减少 。 此外，人们将受益于较低的运输成本和更高的服务水平。

People will have better access to world’s digitized knowledge, with intelligent discovery tools. The ‘Fake news’ problem, along with content quality, security and safety online will all be improved by intelligent components and AI-powered services.

人们将通过智能发现工具更好地访问世界数字化知识 。 “假新闻”问题以及在线内容质量，安全性和安全性都将通过智能组件和AI驱动的服务得到改善。

Artificial Intelligence is also improving our health systems: more accurate medical diagnoses, personalized medicine, shorter drug development cycles will significantly improve the overall effectiveness, level of service to patients and the general access to health services.

人工智能还改善了我们的卫生系统 ：更准确的医学诊断，个性化药物，更短的药物开发周期将显着提高整体有效性，为患者提供的服务水平以及获得卫生服务的总体途径。

6.准备 (6. Getting ready)

But how can we ensure proper use of Artificial Intelligence — in the interest of the individual and the society? How can we best adapt to the technological transformation which is already happening?

但是，为了个人和社会的利益，我们如何确保正确使用人工智能？ 我们如何最好地适应已经发生的技术改造？

People need to achieve a general awareness and understanding of the technology, its potential, benefits and associated risks. Societies need to adapt to the new technology landscape and embrace Artificial Intelligence as a ‘smart tool’ helping people to achieve more. We all need to realize the value for humanity, but also see the treats from bad use of AI.

人们需要对技术，其潜力，收益和相关风险有一个普遍的认识 。 社会需要适应新技术形势，并将人工智能作为帮助人们实现更多目标的“智能工具”。 我们每个人都需要实现人类的价值，但同时也要看到因错误使用AI而产生的待遇。

States need to adapt by modernizing laws, frameworks, social programmes and their education systems. New strategies are needed — to focus on education — along with new frameworks for the markets, businesses and social systems; they need to rethink how markets, companies and employment agreements should work in the new era of intelligent automation; they need to redesign the social mechanisms to cover a range of new scenarios and situations

各国需要通过使法律，框架，社会计划及其教育系统现代化来适应 。 需要采取新的战略(以教育为重点)以及针对市场，企业和社会系统的新框架； 他们需要重新考虑市场，公司和雇佣协议在智能自动化新时代应如何运作； 他们需要重新设计社交机制，以涵盖一系列新情况和新情况

People need to switch to a life-learning mode — learn to acquire new skills and explore new talents which are more relevant to the new order of things.

人们需要切换到生活学习模式 -学习获得新技能并探索与新事物更相关的新才能。

Thought leaders need to drive the right rules, frameworks and global agreements to mitigate the risk of centralization of power and control over data and technology.

思想领袖需要制定正确的规则，框架和全球协议，以减轻权力集中以及控制数据和技术的风险。

This technological revolution brings great opportunities for prosperity and growth. We just need to somehow ensure that the technology will be applied and used in the right direction. We need a framework to guide the development of AI-powered applications with basic rules and those specifications that guarantee reliability, transparency and ethical alignment.

这场技术革命为繁荣和发展带来了巨大的机会 。 我们只需要以某种方式确保以正确的方向应用和使用该技术。 我们需要一个框架来指导具有基本规则和保证可靠性，透明性和道德一致性的规范的AI驱动的应用程序的开发。

Key steps in the right direction are already happening. For example, there’s already discussion for banning ALWs. There’s also movement towards explainable AI (XAI) and the ‘right to explanation’. These allow understanding the models used for artificial intelligence (and how they make particular decisions — which is also required by the European Union GDPR — General Data Protection Regulation).

正确方向上的关键步骤已经在发生。 例如，已经有关于禁止ALW的讨论。 也有向可解释的 AI ( XAI )和“ 解释权 ”的方向发展。 这些使您能够了解用于人工智能的模型(以及它们如何做出特定决策，这也是欧盟GDPR(通用数据保护条例)的要求)。

翻译自: https://www.freecodecamp.org/news/ai-beyond-the-hype-3fd6b4b16c3c/

ai的智能发展不会超越人类