Super Humanizer vs WriteHuman

The Great Elevation: How Generative AI Will Increase and not Replace Knowledge Work

Generative artificial intelligence's momentum has stoked a familiar techno-fear: that human labor will soon be displaced. Self-driving carswill put an end to truckers; engineers fear automation will decimate white-collar work; and people worry that large language models will be come the Jack the Rippers of journalism, programming, and diagnosis. However, history and economics suggest that generative AI will not replace knowledge workers as Jack the Rippers did journalists; instead, it will upgrade all work by remaking the tools that loom between us and information, democratizing access to Expertise, and returning human work to high-level judgement and empathy.

In the history of automation, it is not the amount of work that the principle changes; it is the kind of work. The spreadsheet first came on the scene in the early 1970s, but it didn't make accountants go away; it merely got rid of the boring and error-prone drudge of manual calculations that filled up their days. As a result, accountancy demand exploded, and accountants shifted from human calculators to strategic financial experts.

Generative AI is the same turning point for knowledge workers.

By allowing the complete automation of information finding, first draft generation, and data forensics, it gets rid of most of the administrative friction of knowledge work, enabling professionals to work at the apex of their cognitive flexibility.

Generative AI democratizes the ability. In the old-world enterprise, skills like advanced coding, expert market research, and polished creative assets would take years of training, millions of dollars of investment and a whole host of specialists to achieve. Generative AI is democratizing the power, as an always-on research assistant, creative junior, and software architect for the individual knowledge worker. As a result, single knowledge workers using generative AI tools can now generate output equal to that of entire teams.

Where AI Falls Short - It's worth noting that an AI doesn't have the human stuff: contextual intuition; moral judgment; empathy; and lived experience. An AI can reference its data sets to make a statistically-likely decision but cannot navigate the gray moral areas of a difficult boardroom decision; cannot develop rapport with a client mourning their family member; and certainly cannot come up with a genuinely original idea from nothing. No matter how prevalent, these human qualities will be valued in an AI world-they will be the defining unique selling point.

The story that AI will make knowledge workers unnecessary is, at its core, the story that knowledge itself is unimportant. Knowledge is not pattern-matching; it is the applied, ethical, contextual use of insight. Instead of an apocalyptic event, generative AI is the spark of a contemporary enlightenment, freeing the human mind from the mundane to focus on what's important: creating, connecting and, well, knowing.

Generative AI is advancing rapidly, understandably causing concern that computerized intelligence will eventually outpace human intellect. It is currently natural to assume that large language models will be the demise of respectable white collar employment. Law, medicine and even the arts will become entirely dominated by artificial intelligence and leave no respectable employment opportunity for human beings. History demonstrates that the adoption of new technology occurs when the return on the investment of that new technology breaks even with the cost of that new technology and lowers the price of that new technology to a level that makes it accessible to the market. Generative AI will bring about the same level of disruption, but rather than eliminate knowledge work, it will transform knowledge work by making the highest and most valued human skills empathy and moral judgement.

Automation tends to change the nature of work. It typically eliminates repetitive tasks. When accountants adopted the computer-based spreadsheet in the 1970s, they could stop doing tedious calculation tasks. Eliminating calculation tasks allowed accountants to engage in higher level analysis and advice. This new found level of analysis and advice formed the basis for the tremendous growth in the field of accounting. There are similarities in the impact of Generative AI. AI can draft reports and synthesize information. This allows knowledge workers to focus on strategic and intellectual tasks.

Moreover, using Generative AI empowers workers to do tasks that traditionally required several workers. A knowledge worker can outperform a team of workers using AI to perform various research, analysis, writing and other intellectual tasks. This gives knowledge workers tremendous flexibility and increases competition in the business world.

Let’s take a closer look at what's missing in AI. First, human cognition draws heavily on tacit knowledge. This is especially the case with regard to moral judgment and context-dependent situational awareness. Nobody can deny that AI has vastly outpaced human intelligence in processing data, but a machine lacks the discretion to analyze moral dilemmas and moral hazards, including some of the more pernicious challenges in management. In certain contexts, creatively underlying human judgment is irreplaceable. Furthermore, emotional intelligence in interpersonal relations is beyond the scope of machines. In fact, all such intuitive, tacit forms of human knowledge will be invaluable differentiators and hard-to-copy competitive edge in an AI-dominated world.

The knee-jerk fear of the possible automation of knowledge workers is overstated and misdirected. Knowledge is meaningfully synthesizing and interpreting patterns and applying contextual judgment. Ultimately, generative AI will free humanity from boring, mundane tasks to focus on the beauty of knowing.