University of Kwazulu-Natal

Why Ai Shouldn T Replace The Rough Draft Newsbreak

Bonisiwe Shabane
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why ai shouldn t replace the rough draft newsbreak

Human thought is a continuous circle, yet AI is its projected sine wave shadow. They meet in a narrow "corridor" of overlapping projections, not shared minds. The differences reframe how we understand and use AI. There’s an image from basic mathematics that has been resonating with me lately. If you... Legal.

Deadly. Twice as lethal as fentanyl. And still on shelves. This legal drug is killing more Americans than fentanyl. Still think it’s safe?. AI was utilized for research, writing, citation management, and editing.

Testing found elevated levels of a potential carcinogenic impurity in several lots of Prazosin Hydrochloride capsules. AI was utilized for research, writing, citation management, and editing. Sandy Paws Rescue Inc., a foster-based dog rescue in Massachusetts, is highlighting several deserving dogs in honor of Adopt a Senior Month. While the term "senior" might give some adopters pause, the rescue emphasizes that these dogs have plenty of years ahead of them; years they deserve to spend in loving homes rather than waiting in... GLP-1–based medicines now dominate diabetes and medical weight-loss headlines—but they’re not all the same. Some are approved for type 2 diabetes only, others for chronic weight management, and a few carry cardiovascular-risk reduction claims.

Posted August 11, 2025 | Reviewed by Devon Frye I often think of writing as a fairly straightforward act. For me, it's a process of transfer and organization—a way to get ideas out of my head and onto the page. But fascinating research suggests that how we externalize thought can change the very nature of the thoughts themselves, along with how well we remember them. That got me thinking—and writing. This study, published in Consciousness and Cognition, compared two simple tasks that included writing words by hand and drawing pictures of those words.

On the surface, both methods might seem equally effective for learning. But the researchers found something very interesting: Drawing consistently led to better memory performance than writing. As you might guess, this got me thinking about LLMs and typing into that context window as a central tool to our "thinking" these days. President @ Royal Australasian College of Medical Administrators | Experienced Chief Medical Officer | Independent Board Director | Medical Futurist Why AI Shouldn't Replace the Rough Draft A recent study found that, by engaging in richer thought patterns, drawing boosts memory more than writing. This suggests that using AI to generate one's writing risks skipping the messy phase that deepens thinking.

Keeping humans in the “making” stages of creativity preserves the process that makes ideas stick. The study didn’t mention artificial intelligence, but its implications are hard to ignore in an age where more and more of our “writing” is co-authored with large language models. The leap from pen to keyboard may already strip away some of the sensory and motor loops that make learning durable—and the leap from keyboard to AI output may risk removing even more. Source in comments. President @ Royal Australasian College of Medical Administrators | Experienced Chief Medical Officer | Independent Board Director | Medical Futurist Source: https://www.sciencedirect.com/science/article/pii/S1053810024001582

CvCISO x 8 & Digital Trust Executive | Legal Consultant | Global Critical Infrastructure | Secure Business Enablement | AI Governance | Risk Transformation | Board Advisor | CMMC RevGen | 🧩🧩Autistic boy Mom... Why do some writers use AI to write their first drafts while others refuse to? The difference often lies in how writers perceive their craft and role. If writers view their role as primarily communicating ideas in writing, then having AI write their first drafts is acceptable. However, if writers understand their role as artistic self-expression, then having AI write their first draft is unacceptable. If we view ourselves as primarily document producers, our job is to clearly express ideas in writing.

The focus is on function. An example of this would be technical writing or many nonfiction books. Anything that speeds up the process or improves writing is seen as positive. From this viewpoint, using AI to write a first draft makes sense. You can prompt AI with ideas and let it write the text. After some editing, a finished document can be published in a fraction of the time it would take without AI.

AI writing tools help streamline your workflow, but faster drafts shouldn’t mean lower value. The question is how you use the time they free up. How do you use that extra time? Picture this: A freelance writer used to spend four hours drafting a blog post. With AI writing tools, they complete the same draft in just one hour. They meet deadlines with ease and still charge the same rate.

It feels like a win. But there’s a catch: As speed increases, value becomes harder to measure. This approach increases creativity and output, but the key question is how AI writing tools fit into the process. Faster work isn’t automatically better. The real value lies in how you use the extra time to enhance clarity, depth, and impact. 👉 For a real-world look at how professionals approach this, check out: Agency Copywriters Go Beyond Human Creativity By Leveraging AI – nDash.com.

With artificial intelligence transforming content creation, many wonder, “Why shouldn’t AI be used for news articles?” While AI offers speed and efficiency, it lacks the critical thinking, ethical responsibility, and investigative skills essential for... This article explores the risks of AI-generated news, its limitations in accuracy and ethics, and why human oversight remains crucial. AI is increasingly being adopted in journalism for: While AI can assist in speeding up processes, it lacks the human ability to analyze context, verify sources, and exercise ethical judgment, making it risky for serious news reporting. <img fetchpriority="high" decoding="async" class="size-full wp-image-857 aligncenter" src="https://dallegenerate.art/wp-content/uploads/2025/02/celebrity-portraits-generated-by-textual-input-ai-artflow-hidreley-fb22.png" alt="Newsroom journalist at work" width="1000" height="525" srcset="https://dallegenerate.art/wp-content/uploads/2025/02/celebrity-portraits-generated-by-textual-input-ai-artflow-hidreley-fb22.png 1200w, https://dallegenerate.art/wp-content/uploads/2025/02/celebrity-portraits-generated-by-textual-input-ai-artflow-hidreley-fb22-300x158.png 300w, https://dallegenerate.art/wp-content/uploads/2025/02/celebrity-portraits-generated-by-textual-input-ai-artflow-hidreley-fb22-1024x538.png 1024w, https://dallegenerate.art/wp-content/uploads/2025/02/celebrity-portraits-generated-by-textual-input-ai-artflow-hidreley-fb22-768x403.png 768w" sizes="(max-width: 1000px) 100vw, 1000px" /> Despite these benefits, AI’s inherent limitations make it unreliable for high-quality journalism.

I often think of writing as a fairly straightforward act. For me, it’s a process of transfer and organization—a way to get ideas out of my head and onto the page. But fascinating research suggests that how we externalize thought can change the very nature of the thoughts themselves, along with how well we remember them. That got me thinking—and writing. This study, published in Consciousness and Cognition, compared two simple tasks that included writing words by hand and drawing pictures of those words. On the surface, both methods might seem equally effective for learning.

But the researchers found something very interesting: Drawing consistently led to better memory performance than writing. As you might guess, this got me thinking about LLMs and typing into that context window as a central tool to our “thinking” these days. The research used a method called multidimensional experience sampling, which interrupts participants during a task to ask about the “quality and focus” of their ongoing thoughts. This let them look beyond the final written word or the sketch, and into the mental space where the work was happening. How will people compose text moving forward, now that every author working with a digital word processor and internet access can use generative AI? Many will likely opt to write traditionally as they did before, but some will use AI in partnership to draft.

At this point, the methods a writer uses to develop a first draft feel like a dealer’s choice dilemma—ask AI to generate the draft for you, or bring some of your writing to the... If students use AI in their drafting process, I’m increasingly drawn toward advocating for the latter method. I don’t like the idea of students going to AI and prompting a first draft. I know some have argued that this could be a helpful method to fight the blank-page anxiety most writers feel. Others view this as helping maturing writers by giving them a template or outline to help them organize and scaffold their ideas. I think there may be some value in those approaches, especially in terms of helping struggling students who might otherwise balk at writing, but all of these approaches assume a maturing writer will then...

Those of us who’ve taught first-year writing likely raised a questioning eyebrow at that idea. Students struggle quite a bit when writing. For many, that struggle is a productive one, helping them exercise habits of thinking and self-inquiry, testing ideas, taking creative risks, and often failing. Anne Lamott’s Shitty First Drafts lays bare this process with frank elegance. I wish developers of LLMs would read it because as Lamott puts it, there’s a profound disconnect in how many fail to divorce the reality of the writing process from the end product: People tend to look at successful writers who are getting their books published and maybe even doing well financially and think that they sit down at their desks every morning feeling like a million...

But this is just the fantasy of the uninitiated. That fantasy of the uninitiated doesn’t see the often maddening process that goes into shaping and forming the words and sentences on the page. Lamott does a wonderful job of articulating this struggle and demystifying it: Workers can stop worrying about being replaced by generative artificial intelligence. Wharton experts Valery Yakubovich, Peter Cappelli, and Prasanna Tambe believe it isn’t going to happen as drastically as many predict. In an essay published in The Wall Street Journal, the professors contend that AI will most likely create more jobs for people because it needs intensive human oversight to produce useable results.

“The big claims about AI assume that if something is possible in theory, then it will happen in practice. That is a big leap,” they wrote. “Modern work is complex, and most jobs involve much more than the kind of things AI is good at — mainly summarizing text and generating output based on prompts.” Yakubovich recently spoke to Wharton Business Daily, offering several key facts he hopes will allay people’s fears of robotic replacement. (Listen to the podcast.) First, while generative AI has advanced rapidly, it still has a long way to go before it can function autonomously and predictably, which are key features that make it reliable. Second, large language models (LLMs) like ChatGPT are capable of processing vast amounts of data, but they cannot parse it accurately and are prone to misleading information, known as AI hallucinations.

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