【TED演讲稿】为什么人类和 AI 是业务好搭档

TED演讲者：Shervin Khodabandeh / 谢尔文·科达班德

演讲标题：Why people and AI make good business partners / 为什么人类和 AI 是业务好搭档

内容概要：What happens when the data-driven capabilities of AI are combined with human creativity and ingenuity? Shining a light on the opportunities this futuristic collaboration could bring to the workplace, AI expert Shervin Khodabandeh shares how to redesign companies so that people and machines can learn from each other.

如果 AI 的数据驱动技术可以与人类的创意和聪明才智结合，会怎么样？AI 专家谢尔文·科达班德（Shervin Khodabandeh）给我们展示了这种未来的职场合作方式，分享了如何将公司重新设计成人类可以和机器互相学习的形式。

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【1】I've been working in AI for most of my career, helping companies build artificial intelligence capabilities to improve their business, which is why I think what I'm about to tell you is quite shocking.

我大部分的职业生涯 都在研究 AI 领域, 帮助公司培养 人工智能（AI）的技术能力, 改进业务, 这就是为什么我认为 我接下来要告诉你的事 十分令人震惊。

【2】Every year, thousands of companies across the world spend collectively tens of billions of dollars to build AI capabilities.

每年,全球成千上万家公司 都会在培养 AI 的技术能力上 花费上亿美元。

【3】But according to research my colleagues and I have done, only about 10 percent of these companies get any meaningful financial impact from their investments.

但是根据我和我同事做的研究, 只有大约 10% 的企业 从这类投资中 收获了显着的财务改善。

【4】These 10 percent winners with AI have a secret.

这 10% 的 AI 赢家 有它们的秘诀。

【5】And their secret is not about fancy algorithms or sophisticated technology.

它们的秘诀与酷炫的算法 或者复杂的技术无关。

【6】It's something far more basic.

这个秘诀简单得很。

【7】It's how they get their people and AI to work together.

就是如何让人与 AI 协作。

【8】Together, not against each other, not instead of each other.

通力合作,而不是针锋相对, 也不是取而代之。

【9】Together in a mutually beneficial relationship.

是互利共赢。

【10】Unfortunately, when most people think about AI, they think about the most extreme cases.

不幸的是, 大多数人想到 AI 的时候, 会联想到最极端的例子。

【11】That AI is here only to replace us or overtake our intelligence and make us unnecessary.

AI 只会取代我们, 或者超越我们的智力, 让我们没有用武之地。

【12】But what I'm saying is that we don't seem to quite appreciate the huge opportunity that exists in the middle ground, where humans and AI come together to achieve outcomes that neither one could do alone on their own.

但是我要说的是 我们似乎并没有关注中间地带上 存在的丰富机会, 在这里,人类和 AI 可以携手 达到二者缺一不可 才能创造的成果。

【13】Consider the game of chess.

比如国际象棋。

【14】You probably knew that AI today can beat any human grandmaster.

你可能已经知道,现在的 AI 已经 可以赢过所有人类国际特级大师。

【15】But did you know that the combination of a human chess player and AI can beat not only any human but also any machine.

但是你知道 人类棋手和 AI 的组合 可以战胜的不仅是所有人类, 还有所有的机器吗？

【16】The combination is much more powerful than the sum of its parts.

这个组合比双方的总和 要厉害得多。

【17】In a perfect combination, AI will do what it does best, which is dealing with massive amounts of data and solving complex problems.

在一个完美的组合里, AI 会发挥所长 处理海量数据, 解决复杂问题。

【18】And humans do what we do best using our creativity, our judgment, our empathy, our ethics and our ability to compromise.

人类也发挥其所长, 充分利用我们的创造力、判断力、 同理心、道德感 和妥协的能力。

【19】For several years, my colleagues and I have studied and worked with hundreds of winning companies who are successfully building these human-AI relationships.

多年以来, 我和我的同事们学习 并与数百家成功利用 AI 获利的公司合作, 它们已经成功地建立了 这种人类与 AI 的关系。

【20】And what we've seen is quite interesting.

我们所见的非常有趣。

【21】First of all, these companies get five times more financial value than companies who use AI only to replace people.

首先,这些公司 比那些仅仅只为了取代人类而 利用 AI 的公司多获取了 五倍的经济价值。

【22】Most importantly, they have a happier workforce.

最重要的是, 它们的员工更快乐。

【23】Their employees are more proud, more fulfilled, they collaborate better with each other, and they're more effective.

它们的员工更自豪、 更有满足感, 他们更有效地合作,更加高效。

【24】Five times more value and a happier workforce.

多五倍的价值, 更快乐的员工。

【25】So the question is, how do these companies do it?

问题是,这些公司是怎么做到的？

【26】How do they achieve these symbiotic human-AI relationships?

它们是如何达到这种 人类与 AI 的共生关系的？

【27】I have some answers.

我有几个答案。

【28】First of all, they don't think of AI in the most extreme case only to replace humans.

首先,它们不会用极端的情况 取代人类,来看待 AI 。

【29】Instead, they look deep inside their organizations and at the various roles their people play.

相反,它们深入研究组织内部, 研究员工扮演的不同角色。

【30】And they ask: How can AI make our people more fulfilled, more effective, more amplified?

它们会问: “AI 如何让我们的员工 更满足、更高效、 价值最大化？”

【31】Let me give you an example.

我来举个例子。

【32】Humana is a health care company here in the US.

休曼纳公司（Humana） 是美国的一家医疗服务公司。

【33】It has pharmacy call centers where pharmacists work with patients over the phone.

它有药房呼叫中心, 药剂师通过电话 与患者交流。

【34】It's a job that requires a fair amount of empathy and humanity.

这个岗位需要相当的同理心 和人道主义精神。

【35】Humana has developed an AI system that listens to the pharmacists' conversation and picks up emotional and tone signals and then gives real-time suggestions to the pharmacists on how to improve the quality of that conversation.

休曼纳研发了一个 AI 系统, 收录药剂师与患者的对话内容, 监测情感和语调的信号, 给药剂师提供实时建议, 告诉他们如何提高对话的质量。

【36】For example, it might say "Slow down" or "Pause"

比如,它会提示 “慢一点”或者“停一下”,

【37】or "Hey, consider how the other person is feeling right now."

或者“嘿,想想对方 现在是什么感受。”

【38】All to improve the quality of that conversation.

这些提示都是为了提高对话的质量。

【39】I'm pretty sure my wife would buy me one of these if she could, just to help me in some of my conversations with her.

我很确定如果 我太太买得到这个系统, 让我更好地和她对话。

【40】Turns out the pharmacists like it quite a lot, too.

结果是药剂师们 也很喜欢这个系统。

【41】They're more effective in their jobs, but they also learn something about themselves, their own behaviors and biases.

他们工作更高效, 同时也更了解自己, 了解自己的行为和偏见。

【42】The result has been more effective pharmacists and much higher customer satisfaction scores.

这个系统带来了 更高效的药剂师、 更高的客户满意度。

【43】Now, this is just one example of many possibilities where human AI collaborate.

这只是人类和 AI 合作的 众多例子中的一个。

【44】In this example, AI was a recommender.

在这个例子中, AI 是一个建议者。

【45】It didn't replace the human or make any decisions of its own.

它没有取代人类, 或者自主做任何决定。

【46】It simply made suggestions, and it was up to the person to decide and act.

它只是提建议, 由人类决定如何 做出决定,采取行动。

【47】And at the heart of it is a feedback loop, which, by the way, is very critical for any human-AI relationship.

它的核心是一个反馈回路, 对人类与 AI 的关系至关重要。

【48】By that I mean that in this example, first AI had to learn from humans the qualities that would make up a good or not so good conversation.

我的意思是,在这个例子中, AI 首先需要向人类学习 优秀和不怎么样的对话 有什么样的特质。

【49】And then over time, as AI built more intelligence, it would be able to make suggestions, but it would be up to the person to decide and act.

随着时间流逝, AI 积累了更多智能, 它就能够提出建议, 但是由人类决定 如何做决定和执行。

【50】And if they didn't agree with the recommendation because it might have not made sense to them, they didn't have to.

如果人类无法赞同这个建议, 也许这个建议没什么道理, 这个人就可以选择不采纳。

【51】In which case AI might learn something and adapt for the future.

无论如何选择,AI 都可以 学到一些东西并为以后调整。

【52】It's basically open, frequent, two-way communication, like any couples therapist will tell you, is very important for any good relationship.

这种公开、频繁、双向的交流, 婚姻治疗师也会这么告诉你, 对任何良好的关系都非常重要。

【53】Now the key word here is relationship.

此处的关键词是“关系”。

【54】Think about your own personal relationships with other people.

想想你和其他人的私人关系。

【55】You don't have the same kind of relationship with your accountant or your boss or your spouse, do you?

你和你的会计师、 你的老板或者配偶 都不会有同样的关系吧？

【56】Well, I certainly hope not.

希望没有。

【57】And just like that, the right relationship between human and AI in a company is not a one-size-fits-all.

就像这样, 公司里 人类和 AI 之间的正确关系 并没有“均码”。

【58】So in the case of Humana, AI was a recommender and a human was decision-maker and actor.

以休曼纳为例, AI 是一个建议者, 人类是决策者和执行者。

【59】In some other examples, AI might be an evaluator where a human comes up with ideas or scenarios, and AI evaluates the complex implications and tradeoffs of those ideas and makes it easy for humans to decide the best course of action.

在其他的例子中, AI 可以是一个评审员, 人类提出想法或者场景, AI 评估这些想法的 复杂影响和优劣, 让人类更容易做出最佳决定。

【60】In some other examples, AI might take a more creative role.

还有别的例子, AI 扮演了更有创意的角色。

【61】It could be an illuminator where it can take a complex problem and come up with potential solutions to that problem and illuminate some options that might have been impossible for humans to see.

它可以指点迷津, 针对复杂的问题 提出可能的解决方案, 指出一些人类可能 无法察觉的选项。

【62】Let me give you another example.

我再举一个例子。

【63】During the COVID pandemic, if you walked into a retail or grocery store, you saw that many retailers were struggling.

新冠疫情期间, 如果你走进一家 零售商店或者超市, 你会发现很多零售商都处境艰难。

【64】Their shelves were empty, their suppliers were not able to fulfill the orders, and with all the uncertainties of the pandemic, they simply had no idea how many people would be walking into what stores, demanding what products.

他们的货架空空, 供应商无法完成订单, 疫情带来的不确定性 让他们对有多少人会前来购物、 购买什么商品毫无头绪。

【65】Now, to put this in perspective, this is a problem that's already quite hard when things are normal.

我们来仔细看一下这个问题, 就算一切正常的时候, 这都是一个很难的问题。

【66】Retailers have to predict demand for tens of thousands of products across thousands of locations and thousands of suppliers every day to manage and optimize their inventory.

零售商每天都需要预测 来自成千上万的地点和供应商的 数以万计的商品需求, 管理并优化仓储。

【67】Add to that the uncertainties of COVID and the global supply chain disruptions, and this became 100 times more difficult.

加上新冠带来的不确定性 和全球供应链冲击, 难度增加了百倍。

【68】And many retailers were simply paralyzed.

许多零售商直接瘫痪。

【69】But there were a few who had built strong foundations with AI and the human-AI feedback loop that we talked about.

但是有些零售商之前 就打下了 AI 的坚实基础, 建立了我之前谈到的 人类与 AI 之间的反馈回路。

【70】And these guys were able to navigate all this uncertainty much better than others.

这些公司比其他公司更好地 在不确定性中站稳脚跟。

【71】They used AI to analyze tens of billions of data points on consumer behavior and global supply chain disruptions and local government closures and mandates and traffic on highways

它们利用 AI 分析数亿数据点, 分析消费者行为、 全球供应链冲击、 当地政府关闭情况和指令、 高速公路交通、

【72】and ocean freight lanes and many, many other factors and get a pretty good handle on what consumers in each unique area wanted the most, what would have been feasible, and for items that were not available, what substitutions could be made.

海运航线和许多别的因素, 很好地掌握了 每一个领域的消费者 最想要什么, 怎么样最可行, 缺货的商品 有什么替代品。

【73】But AI alone without the human touch wouldn't work either.

但是,单单靠 AI, 没有人类的影响也无法成功。

【74】There were ethical and economic tradeoffs that had to be considered.

还需要考虑道德和经济影响。

【75】For example, deciding to bring in a product that didn't have a good margin for the retailer but would really help support the local community at their time of need.

比如,决定要不要引进一款 对零售商没有什么利润, 但是可以为本地的社区 在它们需要的时候 提供支持的产品。

【76】After all, AI couldn't quite understand the uniquely human behavior of panic-buying toilet paper or tens of gallons of liquor, only to be used as hand sanitizer.

AI 毕竟并不能完全理解 人类疯抢厕纸或者 只是用作洗手液的大量酒水 这样的独特行为。

【77】It was the combination that was the key.

组合在一起才是关键。

【78】And the winning companies know this.

那些获胜的公司懂得这点。

【79】They also know that inside their companies, there's literally hundreds of these opportunities for human-AI combination, and they actively identify and pursue them.

它们也知道在公司内部, 存在着成百上千 留给人类与 AI 组合的机会, 它们主动地发掘并追寻这些机会。

【80】They think of AI as much more broadly a means to replace people.

它们不会把 AI 看作取代人类的 方式,而是思维更加开阔。

【81】They look inside their organizations and re-imagine how the biggest challenges and opportunities of their company can be addressed by the combination of human and AI.

它们观察企业内部, 重新考虑公司最大的挑战和机遇 应该如何利用 人类与 AI 的组合解决。

【82】And they put in place the right combination for each unique situation.

它们会为每一种具体的情况 采取最佳的组合。

【83】Whether it's the recommender or the evaluator or the illuminator or optimizer or many, many other ones.

无论是建议者、评审员、 引路人、优化器还是其他角色。

【84】They build and evolve the feedback loops that we talked about.

它们建立并改进了 我们之前谈到的反馈回路。

【85】And finally and most importantly, they don't just throw technology at it.

最后一点,也是最重要的一点, 它们不会一门心思只搞技术。

【86】In fact, this has been the biggest pitfall of companies who don't get their return from their AI investments.

实际上有很多公司都遭遇了危机, 它们在 AI 上的投资 没有得到回报。

【87】If they overinvest in technology expecting a piece of tech to solve all their problems.

它们过度投资技术, 指望一项技术可以解决所有问题。

【88】But there is no silver bullet.

并没有什么一招鲜。

【89】Technology and automation can only go so far, and for every one automation opportunity inside a company, there's literally ten for collaboration.

科技和自动化止步于此, 但是公司里每一个自动化的机会, 都对应着十个合作的机会。

【90】But collaboration's hard.

但是合作很难。

【91】It requires a new mindset and doing things differently than how we've always done it.

这需要一种崭新的思维, 抛开传统的方式, 采取与众不同的行动。

【92】And the winning companies know this, too, which is why they don't just invest in technology, but so much more on human factors, on their people, on training and reskilling and reimagining how their people and AI work together in new ways.

获胜的公司也懂这些, 这就是为什么 它们不会只投资于技术, 还会投资于人力, 于员工,于培训和技能提升, 于重新考虑人类和 AI 协作的全新方式。

【93】Inside these companies, it's not just machines replacing humans.

在这些公司里, 机器没有要取代人类。

【94】It's machines and humans working together, learning from each other.

机器会和人类一起工作, 互相学习。

【95】And when that happens, the organization's overall rate of learning increases, which in turn makes the company much more agile, much more resilient, ready to adapt and take on any challenge.

这时, 这个公司的总体学习率提升了, 从而让公司变得更加敏捷、 更加能屈能伸, 适应性更强, 应对各种挑战。

【96】It is the human touch that will bring the best out of AI.

人类的介入能让 AI 物尽其用。

【97】Thank you.

谢谢。