“It is better to fail in originality than to succeed in imitation.” -Herman Melville
Generative Artificial Intelligence (Gen AI) has taken the digital world by storm. Add .ai to a word, make it your domain, provide a GenAI service and you are in business. GenAI can create anything we want; A poem, a picture, a song or a book, you name it, it is just a click away. Large language models rule the world, making our work easier and faster, and thereby increasing productivity.
This begs the question of whether we are moving away from the original work. Are we delegating the job of thinking to artificial intelligence? Will generative AI solve all our problems in the future?
While the power of Gen AI can create vivid images and videos, spit out lyrics and compose amazing tunes, and write articles and books, it always lacks in originality, the way humans would want to perceive information.
Genuineness in creatives
I have read articles that are published mentioning it as AI-generated and curated. Why would we be interested in what AI thinks about a particular topic? Ideally, we would be interested in what a Subject Matter Expert(SME) thinks about that topic in the real world. The article’s genuineness gets lost when it is AI generated even if it is curated by a subject matter expert.
The genuineness lies in the infinitesimal imperfections in our creations.
It is fine to ask Gen AI to draft a mail to send it to your client or a leave letter to be sent to your boss. You may also generate an image that can aid in a blog which may add value and not be unethical. Relying completely on Gen AI to create tutorials, videos, books, blogs, assignments, and articles may be too much of an ask and would be closer to plagiarism.
Is there an acceptable norm?
Can we come up with a number in percentage that we can retain from GenAI’s output so that the article is considered original? For instance, if we say that only 70% of the content or idea is original and the rest is from GenAI, would the article still be considered as original?
Listening and questioning used to be the higher-order communication skills to interact, influence, solve problems, manage conflicts and sell. The irony is that now Prompt Engineering seemed to have replaced the top communication skills to query the Large Language Models (LLMs) for better results out of GenAI.
Cons of GenAI
Deep fakes and AI-generated video calls have become part of mainstream scams and crimes. People are conned by AI generated video calls making the receiver believe that the actual person is calling.
Are the cons of GenAI superseding the advantages of GenAI?
Tools that use traditional AI seem to be fine. I use the free Grammarly tool to spot and correct spelling or grammatical errors, in blog posts. Traditional AI does not generate anything on behalf of the user, GenAI does. So creating the entire blog using GenAI may not be an ethical thing to do.
While we make our homes smart, using the power of IOT(Internet of Things) and AI, it is important not to forget to exercise our brains to make them even stronger and smarter.
I would like to do an experiment now. Whatever you read so far, came from my thoughts, which is original work.
I prompted the following into a GenAI tool and printed the results below for comparison. Please read the GenAI created blog and respond to the poll given at the end.
The prompt provided: “Write an article on “Losing Originality with GenAI” less than 500 words.
Output from GenAI
Losing Originality with GenAI: Navigating the Challenges of Creative Automation
Generative AI (GenAI) is transforming the creative landscape, enabling rapid content creation in art, writing, music, and more. However, as we embrace this technology, we face a significant concern: the potential erosion of originality.
GenAI works by analyzing vast datasets, identifying patterns, and generating content that mimics human creativity. This process is undeniably powerful, allowing for the swift production of high-quality material. Yet, this strength is also a fundamental weakness. GenAI’s outputs are inherently derivative, built on existing ideas rather than creating something entirely new. This raises an important question: Is originality being sacrificed in the pursuit of efficiency?
Traditionally, creativity has been about innovation—breaking away from the norm, exploring uncharted territories, and offering fresh perspectives. Original work challenges conventions, reflecting the unique insights and emotions of its creator. GenAI, on the other hand, operates within the confines of historical data, recombining existing elements rather than generating novel ideas. This can lead to a homogenization of content, where new creations are merely variations of the past, rather than bold steps forward.
Human vs AI-generated content
The widespread adoption of GenAI also risks devaluing the creative process itself. Crafting something truly original requires time, effort, and a deep engagement with the subject matter. It involves trial and error, reflection, and personal expression. GenAI, by contrast, offers a shortcut—content can be produced in seconds, without the need for such rigorous effort. While this can be incredibly useful, it may also encourage a culture of surface-level creativity, where quantity is prioritized over quality, and depth is sacrificed for speed.
Furthermore, as GenAI-generated content becomes more prevalent, distinguishing between original and derivative work may become increasingly difficult. The lines between human and machine-generated creativity could blur, leading to a situation where truly original work is harder to identify and appreciate. This could diminish the value placed on originality, as audiences become accustomed to polished but formulaic content.
Despite these challenges, GenAI need not spell the end of originality. Instead, it can serve as a powerful tool to augment human creativity. When used thoughtfully, GenAI can inspire new ideas, provide creative prompts, or assist in the iterative process of creation. The key is to use GenAI as a complement to, rather than a replacement for, human creativity. By doing so, we can ensure that originality remains at the heart of creative endeavors, even in an age of automation.
Conclusion
In conclusion, while GenAI offers incredible opportunities, it also poses significant challenges to originality. As we integrate this technology into our creative processes, it’s crucial to remain mindful of its limitations. By striking a balance between leveraging GenAI’s capabilities and preserving the essential human element of creativity, we can navigate this new landscape without losing the spark of originality that makes our work truly meaningful.
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