AI's Struggle with Deep Work Summarization Challenges

Today, when nearly everyone is pressed for time, artificial intelligence becomes a more and more popular shortcut. Freelance journalist Amanda Smith decided to test whether AI, namely ChatGPT, could help understand the core of Cal Newport’s book Deep Work and provide some valuable takeaways. However, despite some minor successes, two substantial challenges kept the writer from achieving her goal. A good enough summary, she writes, is unfortunately guaranteed by the built-in plagiarism safeguards and the unavailability of the full version of the book that AI uses to make sure it does not refer to copyrighted content.

Nonetheless, the writer ‘s experience underlines a crucial problem that ensues from a middle ground of the convenience of AI today. The very tools that ensure the safety of the content’s copyright also do not let AI delve deeper in the analysis, resulting in the generation of generic and often wrong summaries. However, one of the best practices in this area, content-heavy summaries also cannot withstand an independent check – and become a potential threat to those who base their education on them. Finally, once again, the use of new technology turned out to be a double-edged sword, an excellent opportunity lost for more timid considerations of copyright and schools of thought.