前端自动化工作流
App developer. Social media manager. Personal trainer. No person on Earth could have predicted these jobs a few decades ago. These are but a few odd jobs that exist today, which have replaced jobs of the past. Throughout modern civilization, jobs have come and gone. Not too many decades ago, about ten perhaps, Americans and Europeans predominantly worked in agriculture. Today, however, mere percentages do. Yes, with the birth of new machinery that allowed one lone person to accomplish what previously required a plethora of coworkers, came the death of agricultural jobs in industrialized countries. In their stead came new jobs.
一PP开发商。 社交媒体经理。 私人教练。 几十年前，地球上没有人能预料到这些工作。 这些只是当今存在的一些零工，已经取代了过去的工作。 在整个现代文明中，工作已经过去了。 不到几十年前，大约有十个美国人和欧洲人主要从事农业工作。 但是，今天只有百分比了。 是的，随着新机械的诞生，使一个人可以完成以前需要大量同事的工作，工业化国家的农业工作就此死亡。 取而代之的是新工作。
This has been a consistent pattern throughout the history of modern civilization. As old jobs become obsolete to technology, new jobs appear to rise in their stead.
在整个现代文明的历史中，这一直是一种始终如一的模式。 随着旧工作对技术的淘汰，新工作似乎在增加。
Despite this historical trend, fears of jobs disappearing have nevertheless reemerged with the surge of popularity for machine learning. Indeed, does this pattern still exist? Are we still seeing a surplus of jobs? Yes, says many studies like this Gartner study and this Oxford paper.
尽管有这样的历史趋势，但是随着机器学习的普及，人们对工作消失的担忧重新燃起。 确实，这种模式仍然存在吗？ 我们仍然看到过剩的工作吗？ 是的，许多研究如Gartner研究和牛津论文都说。
For now. These studies mostly focus on the near future into consideration.
目前。 这些研究主要集中在考虑不久的将来。
What makes AI unique is its theoretical ability to automate any job, no matter how cognitively challenging. In whatever role that you can find clear routines and rules, a machine learning AI could more efficiently accomplish the work than a human. It should not be unfeasible to imagine a potential future wherein virtually every job, spare a few decision-making leadership roles, are automated.
AI的独特之处在于其理论上能够自动完成任何工作的能力，无论在认知上有多大挑战。 无论您能找到明确的例程和规则，机器学习的AI都比人类更有效地完成工作。 想象一个潜在的未来是可行的，其中几乎每项工作(除了少数决策领导角色)都是自动化的。
In this highly subjective and hypothetical article, I’d like to argue why and how we might reach that point, and what comes after. For that reason, I will be jumping over some of the dilemmas of the present day. If you’re curious about how value creation works in AI, you can read more about that here, and the severe ethical implications of these developments here.
在这篇高度主观和假设的文章中，我想争论为什么以及如何达到这一点，以及随后发生的事情。 因此，我将跳过当今的一些难题。 如果您对价值创造如何在AI中发挥作用感到好奇，可以在这里阅读更多有关它的信息，以及这些发展在伦理上的严重含义。
驾驶之死 (The Death of Driving)
From a process perspective, vehicular automation is what I would call the perfect case for automation. Autonomous AI thrives in environments with clearly defined rules, and there sure are plenty of rules in traffic. As there is a correct course of action for every conceivable scenario, machines are blatantly superior to humans when it comes to driving vehicles. Self-driving cars do not get tired. They do not drive over the speed limit. They drive energy-efficiently. They drive smoothly and comfortably for the passengers. And to top it all of, they don’t ask for a salary.
从过程的角度来看，我将车辆自动化称为自动化的完美案例。 自主AI在具有明确定义的规则的环境中蓬勃发展，并且在流量中肯定有很多规则。 由于在每种可能的情况下都采取正确的措施，因此在驾驶车辆方面，机器明显优于人类。 自动驾驶汽车不累。 它们不会超速行驶。 他们以高能效驱动。 它们为乘客提供了平稳舒适的驾驶体验。 最重要的是，他们不要求薪水。
The technology for completely autonomous vehicles is almost complete. Elon Musk, CEO of Tesla, believes that their company will have fully autonomous cars by the end of this year, which would be 2020, in case you’ve arrived at this article from the future. After that, it will take a few years for the legal and judicial landscapes to pave the way for the technology, though inevitably, machines will be allowed to drive fully autonomously. I believe that machines will replace all jobs in industrialized countries that revolve around driving. This is a substantial amount of jobs. Truck drivers, bus drivers, taxi drivers, train conductors. AI is simply superior in these tasks.
全自动驾驶汽车技术几乎已经完成。 特斯拉(Tesla)首席执行官埃隆·马斯克(Elon Musk)相信，如果您从未来开始接触这篇文章，那么到今年年底，即2020年，他们的公司将拥有全自动驾驶汽车。 在那之后，法律和司法环境将花费几年的时间来铺平技术的道路，尽管不可避免地，机器将被允许完全自动驾驶。 我相信，机器将取代以驾驶为中心的工业化国家中的所有工作。 这是大量的工作。 卡车司机，公共汽车司机，出租车司机，火车售票员。 人工智能在这些任务上简直是上乘。
Again, what makes driving unique is that, while the processing of the data might be complex (i.e., the ability to observe and comprehend all manners of visual information such as road signs and other vehicles), from a process perspective, it’s rather straight forward. This is certainly not the case for many other tasks, however. Ask a banker, a programmer, or a doctor to explain in minute detail how they make every decision, every task, every objective of their day, and they will surely struggle to do so. Finding clear routines and rules for every job is challenging.
再次，使驾驶与众不同的是，尽管数据的处理可能很复杂(即能够观察和理解各种方式的视觉信息，例如路标和其他车辆的能力)，但从过程的角度来看，这很简单。 但是，许多其他任务肯定不是这种情况。 要求银行家，程序员或医生详细解释他们如何做出他们每天的每个决定，每个任务，每个目标，他们肯定会很难做到。 为每项工作找到清晰的例行程序和规则具有挑战性。
Alas, task by task, machine learning AI is slowly but surely automating even complex roles. The world’s best flu vaccine was created by an AI in 2019. When a jury was asked to vote for their favorite perfume, an overwhelming majority chose a perfume developed 100% autonomously by an AI. Music curation? Automated. Text editing? Automated. Stock investing? Automated. And all of this by 2020.
las，按任务进行，机器学习AI正在缓慢但确实可以自动化复杂的角色。 世界上最好的流感疫苗是由AI在2019年创造的。当陪审团被要求投票选出他们最喜欢的香水时，绝大多数人选择了AI自主开发的100％香水。 音乐策展？ 自动化的。 文字编辑？ 自动化的。 股票投资？ 自动化的。 到2020年，所有这些。
乔布斯之死 (The Death of Jobs)
If our planet had existed for a day, humanity would have existed for 10 minutes, the industrial era for two seconds, and machine learning for some mere millisecond. Imagine how far machine learning will have come in a decade, in two decades, in five, in ten, in a hundred decades.
如果我们的星球存在一天，那么人类将存在10分钟，工业时代将存在2秒钟，而机器学习将仅存在几毫秒。 想象一下，十年后，十年后，十年中，十年后，一百年后，机器学习将发展到何种程度。
All AI applications that exist today are examples of narrow AI, sometimes called modular AI. These are applications that have been built to accomplish one specific task. The AI that defeated the world’s best Go player cannot drive a car, and the AI that perfectly drives cars cannot play Go, while a human may be able to do an adequate job at both of those activities.
当前存在的所有AI应用都是狭窄AI(有时称为模块化AI)的示例。 这些是为完成一项特定任务而构建的应用程序。 击败了世界上最好的围棋运动员的AI不能驾驶汽车，而完美驾驶汽车的AI不能玩围棋，而人类可能在这两种活动中都能胜任。
Imagine how far machine learning will have come in a decade, in two decades, in five, in ten, in a hundred decades.
想象一下，十年后，十年后，十年中，十年后，一百年后，机器学习将发展到何种程度。
In contrast, artificial general intelligence (AGI) is a theoretical AI that can accomplish every task that a human can do just as well as a human. This is the kind of AI typically seen in sci-fi films. If humanity does discover AGI, then most jobs could, by definition of AGI, be replaced by computers.
相比之下，人工智能(AGI)是一种理论上的AI，可以完成人类可以完成的所有任务。 这是科幻电影中常见的一种AI。 如果人类确实发现了AGI，那么根据AGI的定义，大多数工作都可以由计算机代替。
However, whether or not researchers discover how to build AGI matters not, I would argue, as jobs could become replaced nevertheless. You don’t need AGI to replace even highly skilled positions. In time, modular AI applications could replace job after job.
但是，我认为，研究人员是否发现如何构建AGI无关紧要，因为尽管如此，工作仍可能被取代。 您甚至不需要AGI来替换技能高超的职位。 随着时间的流逝，模块化的AI应用程序可以一次又一次地替换工作。
There are plenty of obstacles to overcome, however. Besides technical challenges, there are ethical dilemmas such as overreliance in machines and algorithmic discrimination, judicial and legal difficulties, the need for human connections, and more. Mass automation of jobs will take a very long time. But I do believe it to be inevitable.
但是，有许多障碍需要克服。 除了技术挑战之外，还有道德困境，例如对机器的过度依赖和算法歧视，司法和法律困难，人际关系的需求等等。 工作的大规模自动化将花费很长时间。 但我确实认为这是不可避免的。
...的诞生...什么？ (The Birth of… What?)
With the death of jobs comes new jobs, or so I’ve been arguing all along. But what happens at this theoretical point where (almost) every job is automated? Where machines can do everything just as well as humans, and the few jobs that haven’t been replaced, such as those of political nature, instead use AI for decision-making support?
随着工作的死亡，出现了新的工作，或者一直以来，我一直在争论。 但是在(几乎)每项工作都自动化的理论点上会发生什么？ 在哪里机器可以像人类一样做所有事情，而没有被取代的少数工作(例如政治性工作)却使用AI来提供决策支持？
Erik Brynjolfsson of MIT coined the phrase “digital Athens”. Two millennia ago, Athenians enjoyed democracy, arts, philosophical debates, and Olympic games. They were free to fulfill their passions and made astonishing progress in science, arts, politics, philosophy, and rhetorics as a result. This was made possible primarily because Athenians had slaves do all the tedious work. Since then, nations around the world have agreed that slavery is horrifying and certainly not something we should be doing in 2020, but what about having machines as metaphorical slaves? Much like a self-driving car could be compared to having a personal slave driver, so too could AI slaves do all of your work.
麻省理工学院的Erik Brynjolfsson创造了“数字雅典”一词。 两千年前，雅典人享受民主，艺术，哲学辩论和奥林匹克运动会。 他们可以自由发挥自己的激情，结果在科学，艺术，政治，哲学和修辞学上取得了惊人的进步。 之所以能够做到这一点，主要是因为雅典人让奴隶从事所有繁琐的工作。 从那时起，世界各国都同意奴隶制令人恐惧，当然这不是我们在2020年应该做的事情，但是将机器作为隐喻的奴隶呢？ 就像将自动驾驶汽车与拥有个人奴隶司机相比，AI奴隶也可以完成您的所有工作。
The way we tend to look at life today is that it revolves around working. We are either employed or looking for work. We spend at least eight hours a day working. Our lives are built around having jobs. It might be hard to imagine a norm wherein most people do not have jobs and are, in fact, not looking for work either.
我们今天看待生活的方式是围绕工作。 我们要么被雇用，要么正在寻找工作。 我们每天至少要花八个小时工作。 我们的生活围绕着工作而建立。 很难想象一个规范，其中大多数人没有工作，实际上也不是找工作。
How would the economy work if (almost) every job is automated? Machines (both physical and digital) can do the job of humans significantly cheaper. If that weren’t true, there wouldn’t be much point in creating machines in the first place. This next sentence might upset some readers, but at this point in society, corporations can be taxed higher, and a basic universal income can be established. I know that many people today may be against the idea of having higher taxes and the idea of the government giving away free salaries to citizens for doing nothing, but bear with me.
如果(几乎)每项工作都是自动化的，经济将如何运作？ 机器(包括物理的和数字的)可以便宜得多地完成人类的工作。 如果那不是真的，那么首先创建机器就没有多大意义。 接下来的一句话可能会使一些读者感到不安，但在当今社会上，可以向公司征收更高的税，并可以建立基本的普遍收入。 我知道今天很多人可能反对提高税收的想法，反对政府无偿地向公民免费发放薪水的想法，但我要忍受。
Here’s why. Machines can do the work of humans significantly cheaper. Thus, governments can tax companies greater, and corporations would still make a healthy profit. This extra money can be spent on a basic income, eliminating the need to work. In this theoretical future, I argue that this is not only a suggestion but a requirement for societies to function.
这就是为什么。 机器可以便宜得多地完成人类的工作。 因此，政府可以向公司征税，而公司仍然可以赚取可观的利润。 这些额外的钱可以花在基本收入上，从而消除了工作的需要。 在这个理论上的未来中，我认为这不仅是一个建议，而且是社会运转的必要条件。
But if people don’t work, what will they do? This, I believe, is the most beautiful part. Humans would be free. Much like the Athenians were free to explore any creative arts they desired without monetary worries, so too would the modern humans be. Free to pursue happiness in any form they find fulfilling. No longer would they be a struggling artist, barely making enough to pay their bills. They would be an artist with no need to worry about making enough to pay their bills. People would be free to pursue their passions. And even if AI could also create art, songs, and films, humans would nonetheless be able to express creativity themselves. Our entire education system would be rebuilt, where creative arts would be at the top of the educational pyramid, rather than the bottom.
但是如果人们不工作，他们会怎么做？ 我相信，这是最美丽的部分。 人类将自由。 就像雅典人可以自由地探索他们想要的任何创意艺术而无须担心金钱，现代人也一样。 自由追求幸福，以他们发现的任何形式满足。 他们不再是一个挣扎的艺术家，几乎没有能力支付账单。 他们将是一名艺术家，无需担心足以支付账单。 人们可以自由追求自己的激情。 即使AI也可以创造艺术，歌曲和电影，人类仍然可以表达自己的创造力。 我们将重建整个教育体系，其中创意艺术将在教育金字塔的顶部，而不是底部。
But if people don’t work, what will they do? This, I believe, is the most beautiful part.
但是如果人们不工作，他们会怎么做？ 我相信，这是最美丽的部分。
All children are born creative. After their school years, their creativity has been systematically erased. In the schools of this hypothetical future, children would be taught to retain their creativity. Our way of looking at life would be altered from developing skills that will pay the bills, to developing skills that will lead to fulfillment in life.
所有的孩子都是天生的创造力。 在他们的学年以后，他们的创造力被系统地抹去了。 在这个假想未来的学校里，孩子们会被教导保持自己的创造力。 我们看待生活的方式将从发展将支付账单的技能转变为发展能够实现生活的技能。
听起来不错，雅各布，但要真实 (Sounds beautiful, Jacob, but get real)
Indeed, this is an optimistic view of what may happen when all jobs are automated, yet looking at societal trends in recent years will provide anything but an optimistic outlook. While the wealth of 99.9% of the population hasn’t increased much over the last decade, the wealth of the top 0.01% has exploded.
的确，这是对所有工作都自动化后可能发生的情况的乐观看法，但是对近几年的社会趋势的观察只能提供乐观的看法。 在过去的十年中，虽然99.9％的人口财富没有增加多少，但最高的0.01％的财富却激增了。
If one were to take a more cynical approach, one might ask themself why the 0.01% would care to give the other 99.9% a universal income. Yes, why even allow the majority of the population to continue to live? This idea comes from another MIT professor, this time the brilliant mind of Max Tegmark, who shared these ideas in his book Life 3.0 (2017, ISBN 978–91–88659–67–5). While discussing AGI, Tegmark argues that the wealthiest of society might simply opt to eliminate the redundant civilians who no longer contribute.
如果一个人采取更愤世嫉俗的态度，那么他们可能会问自己，为什么0.01％的人愿意给另外99.9％的人以全民收入。 是的，为什么还要让大多数人口继续生活呢？ 这个想法来自另一位麻省理工学院的教授，这次是Max Tegmark的聪明才智，他在他的《生活3.0》(2017，ISBN 978–91–88659–67–5)中分享了这些想法。 在讨论AGI时，Tegmark认为，社会上最富有的人可能只是选择消灭不再捐款的多余平民。
I agree; it’s a possible future. If virtually every job becomes automated, humans become unnecessary. With a twisted enough mindset, one might even argue that the mass elimination of humanity is for the good of Earth, as climate change and overpopulation would be issues no longer. The elite could wipe out the world with ease. If an AI could create the world’s best flu vaccine in 2019, there is surely a future wherein an AI can create the perfect virus. A virus that spreads incredibly fast, shows no symptoms to the bearer for the first thirty days, and then kills its bearer instantly. Naturally, the wealthiest will be genetically engineered to be immune to the virus.
我同意; 这是一个可能的未来。 如果几乎所有工作都变得自动化，那么人类就变得不必要了。 有足够的思维定势，甚至有人可能会认为，大规模消除人类是为了地球的利益，因为气候变化和人口过剩将不再是问题。 精英们可以轻松地消灭世界。 如果AI能够在2019年创造出世界上最好的流感疫苗，那么AI肯定会创造出完美的病毒。 一种病毒以极快的速度传播，在最初的三十天内对承载者没有任何症状，然后立即杀死了其承载者。 自然，最富有的人将经过基因工程改造以对病毒免疫。
This way, the 0.01% of the population could enjoy a perfect world wherein they never have to work, never have to worry about climate change, and never have to worry about another revolution sparked by unemployment.
这样，0.01％的人口可以享受一个完美的世界，他们无需工作，不必担心气候变化，也不必担心失业引发的另一场革命。
死亡还是出生？ (Death or Birth?)
Whether or not AGI is discovered, I believe that there will be a point of time in the future where a majority of jobs will have been automated, and not enough new jobs will have been invented. I also believe that the most likely scenario in this event is that universal basic income will become commonplace, but there are naturally plenty of other possibilities, and I wanted to provide an example of a cynical such.
不管是否发现了AGI，我相信在将来的某个时间点，大多数工作将被自动化，并且将不会创造出足够的新工作。 我也相信，在这种情况下，最有可能发生的情况是普遍基本收入将变得司空见惯，但是自然地还有许多其他可能性，我想举一个愤世嫉俗的例子。
Before I end this argumentative piece, I want to stress that what I have described is a potential future that likely will not exist for many decades, probably not for many centuries. I do not believe that we are anywhere close to mass automation. However, I also want to point out that technological progress is unpredictable and has proven to be generally faster than one would imagine. A single breakthrough in a single field can be a game-changer that disrupts life as we know it. Inventions such as the internet and the smartphone are mere decades old and have, in such a short time-span, fundamentally reshaped our lives and disrupted countless industries.
在结束这篇辩论性文章之前，我想强调，我所描述的是一个潜在的未来，它可能不会存在数十年，可能不会存在多个世纪。 我不认为我们可以接近大规模自动化。 但是，我还想指出，技术进步是不可预测的，并且事实证明，它比人们想象的要快得多。 在一个领域中的一个突破可以是改变我们生活的改变游戏规则的人。 互联网和智能手机等发明只有几十年的历史，并且在如此短的时间内，从根本上改变了我们的生活，并扰乱了无数行业。
Whether it turns out to be a utopia or a dystopia: mass automation of jobs is coming.
无论结果是乌托邦还是反乌托邦：工作的大规模自动化即将到来。
翻译自: https://medium.com/swlh/when-every-job-is-automated-444d5e9a249e
前端自动化工作流