Introduction
Digital technologies are constantly evolving a point hopefully made clearly by the now famous essay on AI-generated text by computer technologist Timnit Gebru in 2020. The realignment of AI technologies with the real world has now made digital content production an output of AI systems. Researchers have long worked on advances in natural language generation technology that have finally come to fruition with developments in computer science and machine learning. AI text can offer economies of scale, speed and degree of control, vastly improving the overall digital reading experience. However, AI text still needs to be humanised, which plays a key role in different dimensions of the digital reading experience.
Recent discussions have identified potential quality issues and raised ethical concerns about the seemingly inherent inhumane ‘cold’ nature of AI text, and its associated ambiguity in terms of its creator’s identity, voice, bias and culpability. In this article we will examine why AI text should be humanised, and continue our discussion of issues around the digital text experience. We introduce six aspects of humanising AI text that would support ethical and trustworthy narratives.
Enhancing Relatability and Engagement
Building Trust with the Audience
Trusting their content has become an important issue between content creators and their audience. Human writers must work hard to forge a relationship of trust with their audience, but in the eyes of readers, the output of a mechanistic AI-generated text can be too sterile to feel any connection. Distancing oneself from AI content can lead to mistrust and lower retention. This is where the detail of humanising the AI can be used to great effect. Ensuring the refinement has taken place – within processes such as those using an AI writing checker to mimic a human writer’s use of nuance – and adding in aspects of human error such as colloquialisms or minor slips-of-the-pen can ensure that an AI reads heavily enough with the human touch to create resonance with the reader and build the required bond of trust.
Addressing Ethical Considerations
Promoting Transparency
When it comes to AI-created content, transparency speaks volumes about ethical content creation. Being clear that parts of the text were machine-written humanises the AI, keeping the human reader’s expectations in check. We can use AI-written content-detectors to code the content, flagging it as computer-generated, making AC dramatically less pleasurable. Whatever’s being read, readers have a right to know what they’re being fed. If they don’t want to read AI text, they shouldn’t have to; and if they don’t mind someone writing it for them, no one should have the ability to pretend the text is human-generated without their consent. Simply put, transparency promotes honest and open engagement with content, which is key to the lasting trust that readers need to invest in media.
Avoiding Misinformation
These issues correspond to two major drawbacks of AI-generated contents – the possibility for AI machine to spread misinformation, and the bias in its training models. With humanised AI text, content creators could implement more checks and balances – such as a detector of AI – to scrutinise AI outputs, and correct them if necessary, so that the information does not become inaccurate, just because an AI machine made a mistake. These safeguards can also prevent the spreading of biases in AI training models. More importantly, human oversight can help humanise AI text by providing the context and interpretation necessary to avoid misinformation.
Improving Content Accessibility
Bridging Language Gaps
Humanising doesn’t just mean making more sensitive; it also means making more inclusive. In this vein, if AI-written text is then adapted for maximum reach by translating it, that well-accommodated text will be made accessible to more people, in more languages. Syntax-sensitive systems need a little more context and a little more cultural nuance to become truly legible to non-native speakers. Human intervention helps an AI-generated text to accommodate varying degrees of linguistic literacy, so that the text can be read at different levels of ease, helping to accommodate different linguistic needs to readEAAs a result of such literacy tools, large volumes of writing could be made accessible to readers, globally.
For instance, if an article about slavery in the US were currented for an Arabic-speaking reader, a human editor would ideally adapt it by removing the occasional awkward syntactical structure, while substituting an example that would rather universally invoke past slavery. Similarly, if an AI-generated text contained overly specific medical jargon unfamiliar to its intended general-interest audience, a human editor could simplify or replace it to eliminate the barriers to comprehension. In both these scenarios, the acceptable level of oddity is subjective and comes down to the threshold of awkwardness set by the human editor.
Enhancing Readability
Because it will be important for the text to be readable by the general public, and enjoyable and non-d Bullshit AI writing should also be humanised to be palatable, and to reach a diversified population, through how the content has been structured and formatted. When text has been written by a computer, it can often read as patchy, going off on tangents and struggling to get a full point across. A checker for AI writing can make sure that the sentences are easier to follow with proper sentence structure, grammar, and punctuation. Even some diagrams (especially when it comes to tricky or intricate concepts that are hard to grasp) can serve as an excellent visual way to get the message across. Additionally, when such writings are designed to encompass diverse audiences, communication gaps can be bridged through simple rules explaining more complex topics in easier ways.
Boosting Creativity and Innovation
Encouraging Creative Expression
It might be able to spit out content with little techie defence, but AI remains far from innovative and creative. By humanising it, you bring in more original thought processes and unique perspectives that humans alone can provide. What’s that going to do to AI creativity if it’s fed a new way of thinking? It might just spit out something more revolutionary than it could on its own, and learn from this, too. If we can get the balance right to create mesmerising content that stimulates and inspires, there’s no limit to where this could go.
Expanding Content Horizons
AI’s lack of bias can be utilised to discover hitherto unexplored areas of content and ideas, but ultimately bringing out the human aspect of the content is necessary to make it relatable. AI writers and human editors need to work together to ensure the AI output is relevant in terms of lives and society. With inputs from both sides, content creators can achieve instant success by exploring niche topics and trends, before others do. The collaboration of human insight and AI efficiency can lead to the creation of more rich and interesting content.
Facilitating Seamless Integration of AI
Simplifying Content Creation
While the numerous efficiencies with integrating AI into content-creation processes may lead to content being produced at a faster rate than ever, scaling human editing resources proportionally will ensure that the AI content produced fits cohesively and seamlessly with existing human-written pieces created for a brand, while maintaining the consistency of the brand’s voice and style throughout content produced. In turn, tools such as rewrite AI can be used to smooth out AI outputs and better fit them into and align them with existing content-strategy goals, ultimately improving content flow and fostering a more cohesive, comprehensive, and ultimately valuable, impressive, and impactful content experience for human readers.
Enhancing Content Adaptability
AI text always needs modifications for fitting into specific platform and format, and the ability to humanise AI text is the guarantee of adapting AI text to specific needs by making subjective judgments accordingly. AI-generated content is always adjusted to the emotional nuances and requirements of each content-delivery channel, such as equipping it with a more friendly tone for a social network or adapting the layout to be more appropriate for a blog. Adaptability greatly boosts the dissemination of content and its impact on a variety of audiences.
Conclusion
‘Humanisation’ is not just a technical necessity; it also makes ethical, persuasive and good-quality writing more possible – perhaps ethically indispensable – if AI technologies continue to produce content. ‘Humanisation’ would be important even if Bahadori-Jahromi and others didn’t see it as a necessary step in producing safe AI-generated content for human audiences. He is also right that humanising AI text production would be important even if there were no danger that humans would immediately assume that it was written by other humans.
One reason is that the practice of humanising the outputs of AI in the process of producing them is a far more important step toward making AI rule-based without having AI replace human thinking than Bahadori-Jahromi and Katharina Muller, a fellow scholar at the University of Oxford, realise. It doesn’t only preserve the human element in digital interactions. ‘Humanisation’ also improves the trustworthiness, accessibility and quality of AI-generated content. If we introduce ‘humanisation’ into the production and consumption of AI text as more of us are exposed to more of it in the workforce and for entertainment, the human-AI symbiosis could win-win in a fundamental way for our species only in the future.
