生成式人工智能：人类雄心壮志的力量倍增器
德勤首席未来学家迈克·贝克特尔（Mike Bechtel）在《技术趋势》宏观技术力量的背景下，对当前围绕生成式人工智能的兴奋点进行了展望。
去年，我们的未来学家和研究人员团队决定使用生成式人工智能 （AI） 来创作封面和章节艺术 2023 年技术趋势。结果简直令人叹为观止。然而，我们严格的设计标准需要大量的人工协作和干预。在那次成功的实验和随后的 ChatGPT 推出以及随之而来的生成式 AI 狂热之后，我们决定探索使用 AI 生成的文本来帮助撰写今年的技术趋势介绍。与去年的艺术作品一样，需要大量的人为干预，这支持了我们的观点，即在人工智能机器时代，人类比以往任何时候都更加重要。
迈克·贝克特尔
美国
作为一个在我眼球上花了四分之一个世纪时间研究所有新奇事物的人，我想为当前围绕生成式人工智能的兴奋提供一些额外的视角，并在我们经久不衰的宏观技术力量的背景下构建这项突破性技术。
比尔·布里格斯
美国
技术演进，商业革命
首先，虽然生成式人工智能给人的感觉是前所未有的和革命性的，但该技术本身实际上是机器智能能力的令人惊讶的直接演变，自Tech Trends成立以来，我们一直在跟踪和记录这种能力。近 70 年来，组织一直在使用机械肌肉（工业机器人），在过去 25 年中一直使用机械思维（机器学习系统）。我们的无机同事现在可以画一幅画，写一个产品描述，或者吊索Python，这既不是随机的，也不是出乎意料的——它们是一本书的下一页，未来的计算机科学家有朝一日可能会称之为《认知自动化：早期》。事实上，至少在过去15年里，最好的公司一直在寻求降低决策成本（图1）。
从技术上讲，生成式人工智能只是正在进行的信息历史的下一个篇章。但在商业方面，夸张是非常有道理的。毋庸置疑：利用硅基智能增强生产力专业人员的新机会确实是一个世代相传的商机。这是一次全面的范式转变，有望打开通往全新商机的大门，并从根本上改变企业本身的组织和运营方式。
通往成功的道路不能退缩
根据我最近的经验，太多的商业领袖将生成式人工智能视为一种减肥药——一种快速而肮脏的手段，通过自动化来降低成本，进而消除工作岗位。在企业成本中心进行紧缩和收敛是取悦股东、纳税人和其他关键组成部分的短期方法，但在最终的计算中，你不能缩水成功之路。可以肯定的是，商学院的教科书中充斥着曾经伟大的组织的警示故事，这些组织被自动化和外包的诱惑所吸引，发现自己更精简、更卑鄙，结果，正好成为竞争对手或收购者的准星。
相反，生成式人工智能应该被视为实现雄心壮志的火箭燃料。我遇到的几乎每一位C级领导者都以他们自己生动的方式告诉我，他们当前需求的强度如何使他们无法像他们希望的那样关注未来的雄心壮志。“运营吃创新当午餐，”一位首席技术官（CTO）告诉我，这是对彼得·德鲁克（Peter Drucker）著名的“文化吃早餐的战略”的改编。人工智能（传统和生成式）可以将宝贵的人类周期从平凡的运营中解放出来，并最终使人们能够专注于更符合未来业务需求的更高价值的工作，即新的和改进的产品、服务、体验和市场（换句话说，这是经过时间考验的盈利增长的关键）。
通缉：生成型人类
许多人担心生成式人工智能会减少对人类创造力的需求（或者更准确地说，会降低人类创造力的价值）。我观察到情况恰恰相反：在一个充满创造力的机器时代，有创造力的人比以往任何时候都更加重要。
例如，去年年底，我与一屋子的高管们聚在一起，演示了一种当时新的生成式人工智能工具，该工具可以根据文本提示绘制独特的图像。其中一位与会者问这个工具，“给我看日落。最终的画面很好，但平淡无奇;与会者耸了耸肩，认为它“只是一个日落”。另一位参与者没有气馁，轮到她了，提示工具，“给我看一场火星上椒盐卷饼和芝士球之间的战争，椒盐卷饼有双节棍，芝士球有喷枪。图像生成器产生了一个荒谬、令人愉快的图像，让满屋子的高管们鼓掌和惊叹。大多数人（可以理解）都赞美了渲染图像的“神奇机器”，但我忍不住悄悄地承认，聪明的人类拥有神奇的头脑和莫克西的混合，甚至要求这样的东西。随着生成式人工智能成为想象力的倍增器，未来属于那些提出更好问题并有更多令人兴奋的想法可以放大的人。
随着生成式机器继续在我们职业生涯的许多角落和缝隙中找到购买，人们将决定这些工具是神奇的还是平庸的。在有意识和富有想象力的指导下，生成式人工智能将开启一个充满神奇新业务可能性的世界。没有它，我们就有可能陷入规模化的平庸，甚至更糟。正如我的朋友、德勤全球首席技术官比尔·布里格斯（Bill Briggs）喜欢说的那样，“好事不是来自让坏事变得更快。
眼睛望向天空，双脚牢牢地踩在地上
最后，这是一个大问题，如果没有坚实的技术基础，这一切都行不通。我们极客（咳咳，专业技术人员）通常很清楚“垃圾进，垃圾出”的古老比喻。我们对共享人工智能未来的早期尝试表明，未来，这种体验将更类似于“垃圾进，垃圾平方”。训练数据中的小偏差可能会导致 AI 输出中的灾难性偏差，因此请先整理企业数据。
请记住：信息只是推动业务发展的六大宏观技术力量之一（图2）。
一个急需现代化的吱吱作响的核心将在未来的人工智能驱动的工作负载下屈服。无差别的计算策略将越来越多地破坏银行。繁琐的交互方式会混淆您的信息，更不用说脱离人才，或者更糟的是，网络威胁。如果你从今年的报告中得到什么，那就是：不要被围绕生成式人工智能的嗡嗡声蒙蔽了双眼，以至于忽视了其他五种基本力量。
事实上，人工智能比以往任何时候都更重要，但这并不意味着你一直在做的其他所有事情突然就不重要了。
Generative AI: Force multiplier for human ambitions
Deloitte Chief Futurist Mike Bechtel provides perspective on the current excitement around generative AI within the context of Tech Trends’ macro technology forces.
Last year, our team of futurists and researchers decided to use generative artificial intelligence (AI) to create the cover and chapter art in Tech Trends 2023. The result was nothing short of spectacular. Yet our exacting design standards required significant human collaboration and intervention in the generation process. On the heels of that successful experiment and the subsequent launch of ChatGPT and ensuing generative AI mania, we decided to explore the use of AI-generated text to help write the introduction of this year’s Tech Trends. As with last year’s artwork, substantial human intervention was required, supporting our point that in the era of artificially intelligent machines, humans are more important than ever.
Mike Bechtel
United States
As someone who’s spent a quarter-century up to my eyeballs in all things newfangled, I want to provide some additional perspective on the current excitement around generative AI and frame this breakthrough technology within the context of our enduring macro technology forces.
Bill Briggs
United States
Tech evolution, business revolution
First, while generative AI feels at once unprecedented and revolutionary, the technology itself is actually a surprisingly straightforward evolution of machine intelligence capabilities that we’ve been tracking and chronicling since Tech Trends’ inception. Organizations have employed mechanical muscles (industrial robotics) for nearly 70 years, and mechanical minds (machine learning systems) for the last 25. That our inorganic colleagues can now paint a picture, write a product description, or sling Python is neither random nor unexpected—they’re the next page in a book that future computer scientists might one day call Cognitive Automation: The Early Years. Indeed, the best companies have been engaged in this quest to reduce the cost of decision-making for at least the last 15 years (figure 1).
Technologically, generative AI is simply the next chapter in the ongoing history of information. But on the business side, the hyperbole is very much warranted. Make no mistake: The newfound opportunity to augment productive professionals with silicon-based intelligence is indeed a generational business opportunity. It’s a full-on paradigm shift that is poised to unlock the doors to altogether-new business opportunities and fundamentally change how the enterprise itself organizes and operates.
You can’t shrink your way to success
In my recent experience, far too many business leaders see generative AI as a mere weight loss pill—a quick and dirty means to simply reduce costs by automating and, in turn, eliminating jobs. Nipping and tucking at business cost centers is a short-term approach to pleasing shareholders, taxpayers, and other key constituents—but in the final calculus, you can’t shrink your way to success. To be sure, B-school textbooks are rife with cautionary tales of once-great organizations that, seduced by the allure of automation and outsourcing, found themselves leaner, meaner, and, as a result, squarely in the crosshairs of competitors or acquirers.
Instead, generative AI should be considered rocket fuel for elevated ambitions. Virtually every C-level leader I meet tells me, in their own vivid way, how the intensity of their present demands precludes them from paying as much attention as they’d like to future ambitions. “Operations eats innovation for lunch,” one chief technology officer (CTO) told me, in a spin on the famous Peter Drucker-ism “Culture eats strategy for breakfast.” AI (traditional and generative alike) can free up precious human cycles from mundane operations and allow people to focus, finally, on higher-value work that better aligns with tomorrow’s business imperatives—namely, new and improved products, services, experiences, and markets (in other words, the time-tested keys to profitable growth).
Wanted: Generative humans
Many worry that generative AI reduces the need for (or perhaps more accurately, diminishes the worth of) human creativity. I’ve observed the opposite is true: In an age of creative machines, creative humans matter more than ever.
For example, late last year, I gathered with a room full of C-suite executives to demonstrate a then-new generative AI tool that painted unique images based on text prompts. One of the attendees asked the tool, “Show me a sunset.” The resulting picture was fine but unremarkable; the attendee shrugged and dismissed it as “just a sunset.” Undeterred, another participant took her turn, prompting the tool, “Show me a war between pretzels and cheeseballs on Mars where the pretzels have nunchucks and the cheeseballs have squirt guns.” The image generator produced an absurd, delightful image that made the room full of executives applaud and marvel. Most (understandably) celebrated the “miraculous machine” that rendered the image, but I couldn’t help but quietly acknowledge the clever human with the magical mix of mind and moxie to even ask for such a thing. With generative AI as a force multiplier for imagination, the future belongs to those who ask better questions and have more exciting ideas to amplify.
As generative machines continue to find purchase in the many nooks and crannies of our professional lives, people will determine whether these tools scale with magic or mediocrity. With mindful and imaginative guidance, generative AI stands to unlock a world of magical new business possibilities. Without it, we run the risk of scaled mediocrity—or worse. As my friend and Deloitte’s global CTO Bill Briggs likes to say, “Good does not come from making bad things faster.”
Eyes to the skies, feet firmly on the ground
Finally—and this is a big one—none of this works without a solid technology foundation. We geeks (ahem, professional technologists) are typically well aware of the old trope “garbage in, garbage out.” Our early forays into our shared AI future suggest that going forward, the experience will be more akin to “garbage in, garbage squared.” Small biases in training data can beget cataclysmic biases in AI output—so get your enterprise data in order first.
And remember: Information is just one of the six macro technology forces that drive business (figure 2).
A creaky core in desperate need of modernization will buckle under tomorrow’s AI-fueled workloads. An undifferentiated computation strategy will increasingly break the bank. Cumbersome interaction modalities will muddy your message, to say nothing of disengaged talent, or worse, cyberthreats. If you take anything from this year’s report, it’s this: Don’t become so blinded by the buzz around generative AI that you neglect the five other fundamental forces.
Indeed, AI matters more than ever, but this does not mean that everything else you’ve been working on suddenly doesn’t.
