unity修改飞行数据
Two and a half thousand years ago, the ancient Greeks used to visit a temple in Delphi to hear the Oracle of Apollo issue gnomic predictions about their futures.
两千半年前，古希腊人曾经拜访德尔斐(Delphi)的一座寺庙，以听取阿波罗神谕(Oracle)对其未来的预测。
In ancient Rome, soothsayers would sacrifice a sheep to the gods, cut open the body to extract the liver, dissect and examine it, and then tell the emperor whether or not they would win the next battle against the Goths.
在古罗马，占卜者会向众神献祭一只绵羊，将尸体切开以提取肝脏，进行解剖和检查，然后告诉皇帝他们是否会赢得与哥特人的下一场战斗。
In Renaissance Europe, travellers used to follow the tea routes and then read fortunes in the leaves at the bottom of the cup.
在欧洲文艺复兴时期，旅行者习惯于沿茶道行进，然后在杯子底部的叶子中阅读时运。
Today, hedge funds use sophisticated models with arcane mathematics to predict the vagaries of the market.
如今，对冲基金使用带有神秘数学的复杂模型来预测市场的变化。
Is one of these things unlike the others? Maybe. Maybe not.
这些事情之一不同于其他吗？ 也许。 也许不会。
In 2007, Warren Buffet made a million dollar bet with the hedge fund industry that the market would outperform a selection of handpicked, actively managed funds over a ten year period. In other words, the people who are paid to predict whether stocks would rise or fall would do worse than if you had just taken a cross section of stocks from across the market and stuck with them.
2007年，沃伦·巴菲特(Warren Buffet)向对冲基金行业押注了100万美元，称该市场在十年内将胜过精选的精选主动管理型基金。 换句话说，那些能够预测股票上涨或下跌的人会比只从整个市场拿出一部分股票并坚持下去的人做得更糟。
In 2017, Buffet won his bet. And yet hedge funds continue. As do horoscopes, fortune tellers and political analysts.
2017年，巴菲特赢得了赌注。 但是对冲基金仍在继续。 星座运势，算命先生和政治分析师也一样。
In June I gave a talk at a virtual conference about data science called Data, Prediction and Culture. Flying cars didn’t feature explicitly in the talk — nor do they feature in this article — but they’re a common trope used to illustrate what life may look like in the future, along with robot butlers, spaceflight and high-fidelity instant video communications. Commercial spaceflight is almost here. AI assistants are starting to become prevalent. And this talk was delivered via Zoom with participants attending from across Europe. William Gibson famously said that “The future is already here, it’s just not very evenly distributed”. Our ability to understand trends and outliers is not at the same level as the progress we make year-on-year in science and technology. And this has pervasive effects in the workplace but also in our lives.
在六月，我在一个名为数据，预测和文化的虚拟会议上发表了演讲。 谈话中并未明确提到飞行汽车-在本文中也未提及-但它们是常见的望远镜，用于说明未来的生活，以及机器人管家，太空飞行和高保真即时视频通讯。 商业太空飞行即将到来。 人工智能助手开始流行。 此次演讲是通过Zoom进行的，来自欧洲各地的参与者都参加了此次演讲。 威廉·吉布森(William Gibson)曾有句著名的话：“未来已经来临，分布不均”。 我们了解趋势和离群值的能力与我们在科学和技术上同比取得的进步水平不同。 这不仅在工作场所而且在我们的生活中都有普遍的影响。
This is a theme I’ve explored in previous talks but it feels more relevant given that the COVID-19 crisis is the starkest illustration of how the improbable can blow up all of our best laid plans.
这是我在之前的演讲中探讨过的主题，但鉴于COVID-19危机是最不可能发生的事情如何炸毁我们所有最佳计划的最明显例证，因此它具有更大的意义。
The following article will cover most of the content of that talk, as well as touching on some other points from previous talks around how we live, work and innovate in a world of noise and data.
下一篇文章将涵盖该演讲的大部分内容，并涉及以前演讲中有关噪声和数据世界中我们如何生活，工作和创新的其他观点。
On Wednesday June 17th 2015, the headline of the sports pages in the Guardian read “Leicester sack three players over racist orgy on Thailand tour”. One of the sacked players was James Pearson, son of the manager. Two weeks later his father Nigel also parted ways with Leicester City making way for Claudio Ranieri, at that point a journeyman who had just failed spectacularly with the Greek national team. Eleven months later Leicester were crowned champions for the one and only time in their history, having been 1000–1 outsiders at the start of the season. Even late in the season Gary Lineker publicly declared he would present Match of the Day in his underwear should this improbable event occur. Occur it did.
2015年6月17日(星期三)，《卫报》体育版面的标题为“ 莱斯特在泰国巡回赛中因种族主义狂欢而解雇了三名球员 ”。 被解雇的球员之一是经理的儿子詹姆斯·皮尔森。 两周后，他的父亲奈杰尔(Nigel)也与莱斯特城(Leicester City)分道扬Cl，为克劳迪奥·拉涅里(Claudio Ranieri)铺路，那时候，一名旅行家刚刚在希腊国家队中惨败。 十一个月后，莱斯特队在历史上也是唯一一次加冕冠军，本赛季初他们是1000-1局外人。 甚至在赛季后期，加里·莱因克(Gary Lineker)公开宣布，如果发生这种不太可能发生的事件，他将在他的内衣中展示“今日比赛”。 做到了。
The following year, two more events occurred that beat the odds. In June, Brexit was voted for by the UK, with bookmakers up until the night before still favouring Remain. And in November, Donald Trump defied the polls to win the US election having started the primaries a year earlier as the rank outsider.
第二年，又发生了两次胜算不小的事件。 六月，英国脱欧被英国投票支持，直到深夜之前，博彩公司才继续支持Remain。 而且在11月，唐纳德·特朗普(Donald Trump)违背了民意测验以赢得美国大选，而该选举已于一年前作为高级局外人开始了初选。
And now, in 2020, a virus has made its way from animal to human and shut down normal life for weeks, months, perhaps years to come.
而现在，到了2020年，一种病毒已经从动物传播到人类，并关闭了数周，数月甚至数年的正常生命。
We have collected billions of data points on football, elections, and viruses. And yet, we have been unable to predict with any reliability either the likelihood, or the severity, of any of these and myriad other events which impact businesses, the economy, public consciousness and ultimately our lives.
我们已经收集了有关足球，选举和病毒的数十亿个数据点。 但是，我们无法可靠地预测影响企业，经济，公众意识并最终影响我们生活的所有这些以及其他众多事件的可能性或严重性。
And if you think I’m cherry picking specific events to prove a point, this is not to mention the Black Lives Matter movement, floods across the UK, fires engulfing Australia or any of the other multitude of unpredictable occurrences that have happened this year alone. I could also talk about a volcano erupting in Iceland or a tsunami off the coast of Japan or the financial crash of 2008 or Russia’s hostilities towards Crimea. And before that, the UK crashing out of the ERM, the miner’s strike, the oil crisis and the three day week, world wars, famines, depressions and on and on.
而且，如果您认为我正在挑选一些具体事件来证明观点，那就更不用说“黑人生命问题”运动，整个英国的洪水，席卷澳大利亚的大火或仅在今年发生的其他许多不可预测的事件。 我还可以谈一谈冰岛的火山爆发，日本沿海的海啸，2008年的金融危机或俄罗斯对克里米亚的敌对行动。 在此之前，英国因企业风险管理，矿工罢工，石油危机和为期三天的一周，世界大战，饥荒，萧条等持续崩溃而崩溃。
Nassim Nicholas Taleb wrote a book about these sort of events called The Black Swan. The things that you cannot predict because you cannot even comprehend them happening. Not all of the examples above are black swans, but all of them have unexpected impacts to human behaviour and create noise in complex systems. Is it possible to predict anything when the world is inherently so volatile?
纳西姆·尼古拉斯·塔勒布(Nassim Nicholas Taleb)写了一本关于此类事件的书，名为《黑天鹅》 。 您无法预测的事情，因为您甚至无法理解它们的发生。 并非以上所有示例都是黑天鹅，但它们都对人类行为产生了意想不到的影响，并在复杂的系统中产生了噪音。 当世界固有地如此动荡时，是否可以预测任何事情？
Usually in a talk I like to invite the audience to participate. This is difficult in a virtual talk with the current technology. Spontaneity is not supported, and as we all get to grips with the technology there are social protocols that we haven’t figured out yet. The raising of a hand, making eye contact, discreet coughs, adjusting the chair — cues that reveal something about the intent and the state-of-mind of the participants — are all difficult to replicate behind a screen.
通常在演讲中，我喜欢邀请观众参加。 在与当前技术进行虚拟对话时，这很困难。 不支持自发性，并且由于我们都掌握了该技术，因此我们还没有发现一些社交协议。 举手，目光接触，谨慎的咳嗽，调整椅子(暗示参与者意图和思想状态的线索)都很难在屏幕后面复制。
What’s the solution to this? It’s still hard to say. Which is not to suggest virtual conferences don’t work, but perhaps they’re still missing the secret ingredient that makes them really valuable. Normal conferences have had years of refinement and practice to work out the kinks, and even then many of them may be boring or obvious (mea culpa!). Lots of the strength of them is in the networking or the random encounters or last minute decisions to visit this stall or listen to that talk. How do we make virtual conferences work like this? It’s difficult to predict.
有什么解决方案？ 仍然很难说。 这并不是说虚拟会议不起作用，但是也许它们仍然缺少使它们真正有价值的秘密成分。 普通会议已经进行了多年的完善和实践，以找出问题的根源，即使这样，许多会议也可能很无聊或很明显(Mea culpa！)。 他们的很多优势都来自于人脉，随机相遇或在最后一刻决定去逛这个摊位或听那个谈话。 我们如何使虚拟会议如此工作？ 很难预测。
What will the next ten years bring? As a start, may I humbly suggest some of the following possibilities: full home automation, wide-scale driverless cars, Michelin-starred lab-grown meat, microgrids, digital currency, the end of privacy, another great depression, applied quantum computing, new nation states appearing, war, the break-up of the UK, the break-up of the USA, the growth of the EU, nuclear fusion, humans on mars, general AI, nanotechnology and human genetic engineering. Many of these are already here, some in their infancy. Others are less likely to happen. But could you say for certain which? And what are the impacts of these events on the economy, on our social systems, on our lives?
未来十年会带来什么？ 首先，我谨谦虚地提出以下一些可能性：全面的家庭自动化，大规模的无人驾驶汽车，米其林星级的实验室种植的肉类，微电网，数字货币，隐私的终结，另一个大萧条，应用量子计算，新民族国家的出现，战争，英国的瓦解，美国的瓦解，欧盟的发展，核聚变，火星上的人类，通用人工智能，纳米技术和人类基因工程。 其中许多已经在这里，其中一些还处于婴儿期。 其他人则不太可能发生。 但是您可以肯定地说哪个吗？ 这些事件对经济，我们的社会制度和我们的生活有什么影响？
And what are the second or third order effects of these? The Andreessen Horowitz analyst Benedict Evans predicts a future where driverless cars are the death knell for smoking, given that most cigarettes are bought at gas stations, a potential casualty of the coming AI revolution (a driverless electric vehicle will charge itself when convenient). Going further, this would potentially affect tax income through lost cigarette sales, but also health spending due to reduced cases of lung cancer and emphysema. What effects do these have? It’s easy to see that single events have cascading impacts, each like it’s own mandelbrot set. Taken as a whole, realistically, any social prediction is unreliable at best and dishonest at worst.
这些的二阶或三阶效应是什么？ Andreessen Horowitz分析师本尼迪克特·埃文斯(Benedict Evans) 预测 ，无人驾驶汽车将成为吸烟的丧钟，鉴于大多数香烟都是在加油站购买的，这将是即将来临的AI革命的潜在伤亡(无人驾驶电动汽车会在方便时自行充电)。 更进一步说，这将通过减少卷烟销售而潜在地影响税收收入，但由于肺癌和肺气肿病例的减少，也会影响健康支出。 这些有什么作用？ 很容易看到单个事件具有级联影响，每个事件都像其自己的mandelbrot集。 总的来说，现实情况是，任何社会预测充其量都是不可靠的，最糟糕的是不诚实的。
And yet… the pace of technological change continues. Think back to television shows and films from the 70s, 80s, 90s. Star Trek’s instant communications and handheld tricorders. James Bond’s tech-filled watches and a car that could drive itself when needed. These technologies have not just landed, they have become indispensable and ubiquitous in no time at all. The modern web has only been with us for twenty years, smartphones for thirteen, social networks aren’t old enough to vote (even though they arguably hold a lot of sway over our politics). The pace of change is fast.
但是……技术变革的步伐仍在继续。 回想70年代，80年代，90年代的电视节目和电影。 星际迷航的即时通讯和手持三阶仪。 詹姆斯·邦德(James Bond)充满技术的手表和可以在需要时自行驾驶的汽车。 这些技术不仅落地，而且已经成为不可或缺的技术。 现代网络已经存在了20年，智能手机已经使用了13年，社交网络还不够老，无法投票(尽管可以说它们在我们的政治上拥有很大的影响力)。 变化的步伐很快。
Working in data science, then, presents a strange dichotomy. Expectations from our customers and colleagues are high, having seen the accelerating technological changes of the last couple of decades. And yet, we are asked to build models to predict an uncertain future, to make sense of a random world. How do we manage the contrast between these competing factors?
因此，从事数据科学工作提出了一个奇怪的二分法。 在过去的几十年中，技术进步日新月异，我们的客户和同事对此寄予厚望。 然而，我们被要求建立模型来预测不确定的未来，以使世界变得随机。 我们如何处理这些竞争因素之间的对比？
The virtual conference is a good case in point — we have incredible technology, the ability to make instantaneous high definition video available across multiple time zones with very little friction. And yet think about every video conference you’ve ever been a part of. “Can you hear me?”. “Am I on mute?”. “Video is lagging, I’m going to audio to preserve bandwidth”. “Sorry, that was my dog / the kids / the postman…”.
虚拟会议就是一个很好的例子-我们拥有令人难以置信的技术，能够在多个时区之间以很小的摩擦提供即时高清视频。 但是，请考虑一下您曾经参加过的每个视频会议。 “你能听到我吗？”。 “我要静音吗？”。 “视频滞后，我要使用音频以保留带宽”。 “对不起，那是我的狗/孩子/邮递员……”。
Nobody ever had to contend with a WiFi outage or wandering family members in Star Trek or James Bond or The Avengers or Star Wars or Back to the Future. The reality is different from the cultural image that has been burned into our subconscious, over and over in TV and Film.
在《星际迷航》，《詹姆斯·邦德》，《复仇者联盟》，《星球大战》或《回到未来》中，没有人遇到过WiFi中断或流浪的家庭成员的问题。 现实不同于在电视和电影中一遍遍地潜入我们的潜意识的文化形象。
In fact, this problem of expectation versus reality is really just scratching the surface. The deeper concern that permeates our lives is how far removed we are from understanding the technology and the data presented all around us. The current Coronavirus crisis is a case in point: each day we are treated to statistics, graphs, facts. Many people will have seen log-scale graphs for the first time when looking at relative cases across countries (this is a chart where one of the axes increases in different magnitudes, for example 1, 10, 100, 1000…). Or been asked to understand second-order derivatives when looking at the speed at which the death rate is falling or rising. And then have to understand the issues concerning the efficacy of masks, two-metre distancing versus one-metre distancing, whether vitamin supplements help and whether obesity or race are a factor in the severity of symptoms. Each of these is debated by experts, analysed by pundits, and put into action entirely differently across countries.
实际上，这个期望与现实的问题实际上只是在摸索。 贯穿我们生活的更深层次的担忧是，我们与了解周围呈现的技术和数据相距甚远。 当前的冠状病毒危机就是一个很好的例子：每天我们都会得到统计数据，图表和事实。 在查看国家/地区的相对情况时，许多人会第一次看到对数刻度图 (此图是其中一个轴以不同的幅度增加，例如1、10、100、1000…)的图表。 或者被要求在查看死亡率下降或上升的速度时理解二阶导数。 然后必须了解有关口罩功效，两米距离与一米距离的距离问题，维生素补充剂是否有帮助以及肥胖或种族是否是症状严重程度的因素。 所有这些都由专家进行辩论，由专家进行分析，然后在不同国家采取完全不同的行动。
What do we do? Give up on statistics and prediction entirely? Throw our hands up in the air and shout “what’s the point?”. Clearly not. Perhaps I was disingenuous above when suggesting we can’t reliably predict anything. After all, the odds at a bookmaker just reflect the market (at 1000–1, the 1 is still going to happen once every thousand times). Polling gives a percentage estimate that a particular candidate will be elected and 48% isn’t zero. Some hedge funds do actually make money for their clients (Buffet’s Berkshire-Hathaway fund continues to outperform the market).
我们做什么？ 完全放弃统计和预测？ 将我们的手举到空中，高喊“这是什么意思？”。 显然不是。 在暗示我们无法可靠地预测任何事情时，也许我在上面有些不屑一顾。 毕竟，博彩公司的赔率仅反映了市场(在1000–1时，赔率仍然每千次发生一次)。 投票给出了一个百分比估计值，即特定候选人将当选，而48％的人数不为零。 一些对冲基金确实为他们的客户赚钱(Buffet的Berkshire-Hathaway基金继续跑赢大盘)。
But the point is that certainty, or even near-certainty, is difficult. And certainty in the future, when looking at the social sphere, is impossible. There is still snake-oil being sold and marketed as “AI”, the opinion that “you can prove anything with statistics” is still prevalent and unhelpful, both in a business and social context, and there is still the expectation that some magic technology solution will solve the world’s ills, from cancer to climate change.
但是关键是确定性，甚至接近确定性是困难的。 从社会角度来看，将来不可能确定。 仍然有以“ AI”形式出售和销售的蛇油 ，在商业和社会环境中，“可以用统计数据证明一切”的观点仍然普遍存在并且无济于事，而且人们仍然期望某些神奇的技术解决方案将解决从癌症到气候变化的世界疾病。
While there isn’t a magic remedy to the problem of expectations versus reality, there are some actions we can take as individuals, as organisations and as a society, that can help us to better face the challenges.
尽管没有一种对预期与现实的问题有不可思议的补救措施，但是作为个人，组织和社会，我们可以采取一些行动来帮助我们更好地应对挑战。
Without wishing to propose widespread policy recommendations, or structural changes to the way our society is organised, perhaps I could humbly offer some simple and relatively easy suggestions that may help, at least a little.
在不希望提出广泛的政策建议或不改变我们的社会组织方式的情况下，也许我可以谦虚地提出一些简单而相对容易的建议，这些建议至少可以有所帮助。
Education. This has been emphasised personally to me given that I am now the primary teacher to three young children while lockdown continues. And while I think education in basic statistics and critical thinking is valuable for school children, it is also essential for adults. One of the things I’m most proud of at is that the data science team I run have produced courses to teach basic programming, data science fundamentals and statistics.
教育 。 我个人已经强调了这一点，因为我现在是三个小孩的主要老师，而封锁仍在继续。 虽然我认为基础统计和批判性思维的教育对学龄儿童很有价值，但对成年人也很重要。 我最引以为傲的事情之一是，我所管理的数据科学团队制作了一些课程，以教授基础编程，数据科学基础知识和统计学。
Understanding confidence intervals, p-values, the aforementioned log scale and other core concepts, is vital for decision makers in businesses. Do you know that the result of the A/B test you’re running is statistically significant? Are you sure the time series forecast will be accurate three years into the future? Are you certain the correlation between sales and zodiac sign of the customer is meaningful? Statistical literacy prevents these mistakes. Education has the effect of inoculating a person against the misuse and misinterpretation of data.
了解置信区间，p值，上述对数标度和其他核心概念对于企业决策者至关重要。 您是否知道所运行的A / B测试的结果具有统计意义？ 您确定时间序列预测在未来三年内将是准确的吗？ 您确定销售量与客户的十二生肖之间的相关性有意义吗？ 统计素养可以防止这些错误。 教育具有使人免于滥用和误解数据的作用。
Honesty. A known problem in science is the lack of papers published which show negative results. Only the flashy, attention-grabbing papers with positive outcomes get into the top journals. And as such the millions of hours of cumulative drudge-work resulting in non-significant results, never see the light of day. This gives the impression that science is a steady progression forwards and scientists, engineers and technologists are all alchemists in ivory towers, able to bend the world to their will. This is dangerous and exclusionary, and only deepens the apprehension many have about science and data and technology.
诚实。 科学中的一个已知问题是缺乏发表负面结果的论文。 只有华而不实，引人注目的论文取得了积极成果，才进入顶级期刊。 因此，数百万小时的累积繁琐工作导致了不重要的结果，所以从来没有白日可待。 这给人的印象是科学是稳步向前发展的，科学家，工程师和技术人员都是象牙塔中的炼金术士，能够将世界屈服于自己的意愿。 这是危险的和排他性的，只会加深许多人对科学，数据和技术的忧虑。
In my Data Science team, we have a monthly show-and-tell of projects we have been working on. Importantly, we try to show all the projects we work on in all the various stages of development, including those that never make it — because they ran out of funding or just didn’t work. Demystifying the process invites more people in. Failure is normal and accepted, particularly when it’s learnt from. The biggest benefit though is cultural — it helps set expectations, removes the veil, and rather than encouraging our customers and colleagues to ask for flying cars, encourages reasoned inquiry, intelligent questioning and potential products that are realistic and impactful.
在我的数据科学团队中，我们每月进行一次正在进行的项目展示。 重要的是，我们试图显示我们在开发的各个阶段所从事的所有项目，包括那些从未实现的项目-因为它们用光了资金或只是没有用。 对过程进行神秘化邀请更多的人参与。失败是正常的并且可以接受的，尤其是从中吸取教训时。 虽然最大的好处是文化-它有助于树立期望，消除面纱，而不是鼓励我们的客户和同事要求乘飞机，而是鼓励进行理性的询问，明智的提问以及具有现实意义和影响力的潜在产品。
Collaboration. This probably isn’t the best descriptor. Diversity of opinions while remaining understanding and welcoming of new ideas and approaches? (There may be a German word for this). Working in a diverse group, whether that’s regarding politics, race, gender or sexual orientation — this gives us superpowers. They allow us to create things that work across the spectrum, let us test our assumptions safely and cheaply, and prevent echo chambers which lead to stagnation. A mix of opinions and beliefs is also stronger than the individual in prediction, estimation and thinking — The Wisdom of Crowds by James Surowiecki describes this with dozens of examples. But as well as helping us cognitively, collaboration and diversity lets us cope with whatever the future throws at us, predicted or not.
合作。 这可能不是最好的描述符。 在保持对新思想和方法的理解和欢迎的同时，意见是否多样化？ (为此可能会有一个德语单词)。 无论是政治，种族，性别还是性取向，都要在一个多元化的团队中工作-这赋予了我们超能力。 它们使我们能够创建适用于整个频谱的事物，让我们安全，便宜地测试我们的假设，并防止回声腔导致停滞。 在预测，估计和思考方面，意见和信念的混合也比个人强。JamesSurowiecki 的《人群的智慧》通过数十个示例对此进行了描述。 但是，除了在认知上帮助我们之外，协作和多样性还使我们能够应对未来可能发生的一切事情，无论预测与否。
In a business context, collaboration means working across departments and breaking down barriers. Fiefdoms and empire-building is common in large companies, and these are the enemies of rational, science-based thinking. Product teams comprising elements from across different functions are able to build things together with the same set of beliefs and expectations.
在业务环境中，协作意味着跨部门合作并打破障碍。 在大公司中，建立领地和建立帝国很常见，而这些都是理性的，基于科学的思维的敌人。 由来自不同职能部门的要素组成的产品团队能够以相同的信念和期望来构建事物。
My final point on collaboration is best stated by a slide I’ve started including in recent presentations: “You don’t need a business case for kindness”. This should be the default position. It’s possible to hold differing opinions while remaining respectful. Everybody is dealing with something, particularly in the current crisis, and kindness to our colleagues and customers will help us far more than flying cars or predicting the future.
我最近开始发表的一张幻灯片就很好地表达了我关于协作的最终观点，其中包括最近的演讲：“您不需要出于商业目的的善意”。 这应该是默认位置。 在保持尊重的同时，可以持有不同的意见。 每个人都在应对某些事情，尤其是在当前的危机中，对我们的同事和客户的友善将给我们带来的好处远远超过了驾驶汽车或预测未来。
When I finish a talk, I usually give some book recommendations that inspired the talk as well as some tongue-in-cheek predictions, mostly to give a satisfying conclusion to the event, but also to highlight the absurdity of making predictions in public.
当我结束演讲时，我通常会给出一些启发演讲的书本建议以及一些tongue舌的预测，主要是为了使活动取得令人满意的结论，同时也强调在公共场合进行预测的荒谬性。
First the book recommendations: three related books, (related mostly by the fact that the authors have complicated relationships with each other). The Black Swan by Nassim Nicholas Taleb is packed full of examples, like those above, as well as the impacts they have in a wider context. The Signal and the Noise by Nate Silver is a foray through the world of statistics via political polls, weather forecasting and sports betting, and is very readable. And finally, Superforcasting by Philip Tetlock, who tries to understand why some people actually can make accurate predictions.
首先，推荐这本书：三本相关的书籍(主要是由于作者之间存在复杂的关系而引起的)。 纳西姆·尼古拉斯·塔勒布(Nassim Nicholas Taleb ) 创作的《黑天鹅》(Black Swan )挤满了上面的例子，以及它们在更广泛的背景下产生的影响。 Nate Silver 撰写的 《信号与噪声》 是通过政治民意调查，天气预报和体育博彩在统计领域中的一次尝试，并且可读性强。 最后， 菲利普·泰特洛克(Philip Tetlock)的超级预测 ，他试图理解为什么有些人实际上可以做出准确的预测。
Regarding my predictions — I don’t have a great record at the end of these talks. In 2017 I predicted that Donald Trump would be impeached by Christmas. It actually took a couple of years longer. I’ve also predicted that the next US president would be a woman. This wasn’t based on anything other than wish fulfilment. However, I feel like that particular wish has been vindicated based on the performance of women leaders of nations reacting to COVID.
关于我的预测-在这些谈话结束时，我的成绩并不理想。 在2017年，我预测唐纳德·特朗普将在圣诞节被弹imp。 实际上花了几年时间。 我还预言，下一届美国总统将是一名女性。 除了实现愿望，这不是基于其他任何东西。 但是，我觉得这个愿望已经根据各国对COVID做出React的女性领导人的表现而得到了证明。
So on a related note, here’s my first prediction: In my lifetime, the CEOs of FTSE 100 companies will remain resolutely male (let’s say 70%). This is gloomy and I hope it is proved wrong. But when you try to predict the weather tomorrow, the most reliable way is to look at the weather today. Perhaps we’ll learn something from the handling of Coronavirus? Perhaps a new social movement will usher in fifth-wave feminism?
因此，在相关的注释上，这是我的第一个预测：在我的一生中，富时100强公司的首席执行官将绝对是男性(比如说70％)。 这是令人沮丧的，我希望事实证明这是错误的。 但是，当您尝试预测明天的天气时，最可靠的方法是查看今天的天气。 也许我们将从冠状病毒的处理中学到一些东西？ 也许新的社会运动会迎来第五波女权主义？
My second prediction: the effects of the pandemic will be with us for a long time (1–2 years) and then will be forgotten almost immediately as we return straight back to the world as we left it. The promises of societal upheaval, reduction in carbon, universal basic income — none of them will come to pass as a result of the current pandemic. The world is already rushing to continue business as usual even while at the time of writing there are hundreds of new cases every day.
我的第二个预测：大流行的影响将持续很长时间(1-2年)，然后在我们离开世界直接返回世界时几乎立即被遗忘。 社会动荡，减少碳排放，普及基本收入的承诺-由于当前的大流行而没有一个兑现。 即使在撰写本文时，全世界每天都在急于继续照常营业，尽管每天有成百上千的新案件发生。
My final prediction: that something none of us have predicted will come out of the blue in the next ten years and change everything all over again.
我的最终预测：在接下来的十年中，我们谁也无法预测到什么，并且会再次改变一切。
I hope it’s something positive.
我希望这是积极的。
Cardiff, June 2020
2020年6月，加的夫
翻译自: https://medium.com/the-innovation/data-prediction-and-culture-or-how-i-learned-to-live-without-my-flying-car-389f4ea72d4
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