10 surprising ways Generative AI will impact Knowledge Work

The key to success in creating content is to produce more content at a faster rate than your competitors. It's like throwing darts at a dartboard - the more darts you throw, the greater the chance of hitting the bullseye. In the past, companies solved this challenge by outsourcing to writing mills and freelancers. However, with the emergence of generative text, you can rapidly produce different variations of content with ease.

The true insight will continue to be rare.

With any evolution in technology, there is a corresponding productivity trap. The productivity trap is where productivity improvements lead to higher expectations and demands for output, which can, in turn, create pressure to work longer hours or take on additional tasks.

Workers will be overworked or stressed, leading to burnout or reduced well-being. Additionally, there may be a risk of devaluing the role of human creativity and expertise in these domains as generative AI systems become more capable of producing high-quality outputs.

As generative AI systems become more advanced and capable of generating high-quality outputs in a variety of domains, there may be pressure to use these systems to produce more content or output at a faster rate with tighter timelines for production.

In order to produce more text, images, content, and video, it is essential to monitor the automated systems closely to minimize the risk of errors. This is true for automation in general.

As automated systems become more efficient, such as those that rely on generative AI, the role of human operators becomes even more critical. While these systems reduce the need for manual effort, they also increase the importance of human involvement in monitoring and managing the process. However, when people become overly reliant on generative AI systems, they may become bored and pay less attention, which can lead to increased errors and mistakes.

If work can be performed locally, the demand for freelance services and outsourcing to other countries may decrease, as the only requirement will be for someone to generate ideas and hypotheses while the AI machine performs its task. The individual can then evaluate the output produced by the machine.

In the future, we are likely to see a rise in prompt engineering experts who excel in crafting effective prompts. As prompt generation is more of an art than a science, I anticipate that professionals with expertise in psychology and persuasion will also be interested in this field due to their strong communication skills. While AI will be able to create content, it may not always be perfect, which is where the role of artists may come in, providing tweaks to make the content more suitable for its intended purpose.

You have seen this in the clothing industry. People pay a premium for bespoke suits over ones that were machine created. I suspect this will happen with content creation. You might see unique labels poping up like bespoke writing, bespoke artistry, bespoke design, etc.

If these expectations for output are not balanced by corresponding improvements in work-life balance or job quality, it could create a situation where workers are overworked or stressed, leading to burnout or reduced well-being. Additionally, there may be a risk of devaluing the role of human creativity and expertise in these domains as generative AI systems become more capable of producing high-quality outputs.

This could cause civil unrest or dissatisfaction. Large drove of smart, dissatisfied people with nothing to do could lead to more significant societal problems: higher crime rates, loss of talent, protest/demonstrations and, at worse, radicalization.

As we have already witnessed with Elon Musk and his team advocating for a deceleration of AI development, many questions remain unanswered regarding generative AI. One of these is whether generative AI will eventually replace the creative license of artists, coders, and creators. This could lead to a plethora of legal challenges as the current unregulated frontier of generative AI evolves, and new regulations are called for.

Red tape increases corporations' costs, meaning that knowledge workers will have to deal with more bureaucracy and compliance, which will require new compliance jobs to be created.

Based on my observations, corporations often prioritize their operational costs over their employees' work-life balance, despite their claims to the contrary. The reality is that corporations tend to view employees as a cost center that requires investment and oversight. Furthermore, some view humans as inherently lazy and difficult to manage.

There is a growing trend toward automating jobs to reduce costs and increase productivity, even at the expense of human jobs. Many corporations prioritize lowering budgets and having fewer people working at higher productivity levels to increase shareholder value. Unfortunately, this trend is likely to continue in the future.