Human involvement balances productivity and success of GenAI-created technical white papers and other information.
Technology-based articles and white papers are significant investments. Consequently, organizations seek many ways to share scientific findings that connect and resonate with target audiences.
Generative AI (GenAI) is the latest content-creating innovation. Fueled by FOMO, the accelerated adoption exposes organizations to multiple vulnerabilities.
Should organizations use GenAI to develop crucial information such as scientific white papers? Companies must comprehensively explore the pros and cons before using GenAI to create critical content.
More importantly, human oversight plays a vital role in successful GenAI adoption. Human involvement maintains company policies and ensures scientific articles generate revenue and a call to action. Here’s why.
Navigating the rewards and risks
GenAI is disrupting the global business community. Since the 2022 ChatGPT open release, the internet has been ablaze with endless AI-focused developments and efficiency applications.
Unfortunately, this is the first wave of GenAI solutions. Consequently, users are on a learning curve. In particular, several issues require clarification during the adoption process, such as:
- How will GenAI support the business and create revenue?
- What are the hazards of using AI tools?
This rush to adopt GenAI exposes legal, cybersecurity, data security, and privacy vulnerabilities. As a result, companies must carefully investigate the benefits and drawbacks of GenAI tools.
GenAI satisfies many roles
With public access, tens of millions of users can utilize AI-based applications. In general, GenAI is a productivity tool. It handles tedious tasks, thus freeing users to focus on problem-solving and other critical-thinking projects.
As a language-productivity tool, GenAI can function in diverse roles, such as:
- Technology reviewer
- Domain creator
- Advertising and marketing agent
- Educator
- Social media manager, and more.
With such flexible applications, companies can’t ignore AI. Yet, situation awareness mandates exploring all the pros and cons possible through such innovations.
Pitfalls in using GenAI
The first wave of GenAI applications is uncovering several critical problems.
GenAI doesn’t apply organizational context. In particular, GenAI tools use large language models (LLMs) trained on massive volumes of available text on the web and other sources. Too often, organizational information is not included in the LLMs. Consequently, AI-created blogs, reports, and other content lack the essence of the organization and fail to create value.
Accuracy problems. GenAI models are unpredictable. On occasion, they produce inaccurate or fabricated responses. Poor training data and procedures intensify this condition.
In addition, deploying multiple AI solutions within an organization can produce inconsistent content. When using GenAI, human oversight maintains company policy and verifies released information.
Lack of unique responses. According to Tim Mertens, Head of Productivity Development of Grammarly, the long-term use of GenAI can result in a sea of sameness. Too often, the context is undifferentiated and void of brand uniqueness. Unfortunately, the sameness impedes SEO efforts.
Lack of new data. LLMs do not retain new data, and output plateaus over time. Users are dependent on updated LLMs with expanded content. Note: OpenAI recently released its latest browsing feature, allowing websites to control how ChatGPT interacts with them. Also, ChatGPT-4 includes training data through April 2023.
AI technology is exploding. Numerous AI-based products are available to handle niche tasks. Boasting over 7,000 AI tools by August 2023, more applications are expected by year-end.
Adopting innovative solutions is a tedious process, especially for enterprise-wide implementation. In addition, many AI tools require subscription fees. Result: Users can find themselves in an economic dilemma with too many paid subscriptions and low productivity.
Mismanagement of AI creates security and privacy issues. For large companies, management must provide employees with authorized technology options. Integrating AI across an organization requires strategic oversight and meticulous scrutiny of approved software and processes. Data or queries entered in GenAI tools can become public information.
In addition, legal concerns arise when incorporating GenAI into products or services. According to a Gartner report, companies must have controls to safeguard their intellectual property and brands.
Final word
The first GenAI wave is not a magical panacea for all situations.
Sam Altman, the CEO of OpenAI, shared a clarifying opinion of GenAI in a 2022 tweet. “It’s a mistake to rely on it [ChatGPT] for anything important right now.”
GenAI is a productivity or brainstorming tool. Human involvement and oversight are crucial in managing the risks of GenAI-created documents.
Engineering, marketing, and legal departments should approve GenAI contributions to scientific materials. Likewise, professional technical writers, proofreaders, and copy editors are additional safeguards. They ensure the scientific article’s clarity, accuracy, and connectivity to the target audience.
More importantly, professional technical writers, copy editors, and proofreaders elevate success results from scientific articles and white papers. For more information on how Global Energy Writers can assist your communication project, send inquiries to globalenergywriters.com/contact-us/
Good writing tip: Human oversight and content reviews are crucial quality requirements when your company’s name is involved.
Bibliography and suggested reading
Cropp, Nicholas, “So what’s the difference between AI, GAI, ML, LLM, GANs, and GPTs?,” May 20, 2023, LinkedIn.
Davenport, Tom, “Are boards kidding themselves about Generative AI?,” Forbes, October 5, 2023.
Grammarly, “Maximizing business potential with Generative AI: The path to transformation,” August 1, 2023.
Gartner Insights, “Gartner experts answer the top Generative AI questions for your Enterprise.”
Lee, T.B. and S. Trott, A jargon-free explanation of how AI large language models work | Ars Technica, July 2023.
Martin, Nicolas, “The boom of AI tools,” August 11, 2023.
Reuters, “ChatGPT users can now browse the internet, OpenAI says,” September 27, 2023.
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