By – Hareesh P V (Research Scholar), Dr Aswathy Gopi (Assistant Professor)
Department of Psychology, SRM University-AP
Oh no! AI will replace humans everywhere!
This was one of the common fears about artificial intelligence as it was integrated into different sectors of human society. Indeed, the growth of AI was so rapid that the human brain did not have enough time to analyse what happened. Through evolution, we tend to be afraid of what we lack information about (Carleton, 2016). Gradually, the fear expanded to generative AI (gen AI) replacing human abilities. ‘Creativity’ was a spotlight in it. Gen AI emerged by offering everyone the power to turn their abstract ideas into finely finished magnum opus. Rather than humans spending more time and effort on creative ideas, gen AI expanded creative accessibility and provided quick results.
Before diving into the AI-creativity paradox, we need to understand what creativity is. Several researchers and theorists in psychology contributedto many definitions of creativity, but in general we can identify some common elements (Deckert, 2015).
Knowledge – involves acquiring information about a topic of interest and moving towards expertise.
Skill – the thinking styles, intellectual abilities, and personality factors jointly contributing towards a creative output that is novel and feasible.
Motivation – a drive that leads to applying the creative thought into reality. It can be from within the individual (intrinsic) and/or due to external factors (extrinsic).
The paradox of AI-creativity is that humans might lose their creative abilities as gen AI is giving ready-made creative ideas. At the same time, such AI models can benefit users to overcome the boundaries of knowledge and expertise, which expands their creative horizons. In a recent review, Brem and Hörauf (2025) suggested three levels of AI evolution that we shall analyse.
Individual impact in creativity (Micro level)
As an individual utilising gen AI, the creative benefits are immediate. They receive a unique and tangible output at a faster rate. Individuals will have endless access to creative ideas in areas where they did not even have any information in the first place. This lowers the individual barrier to idea generation and bypasses cognitive fixation: prior knowledge or examples restricting problem-solving ability (Liu et al., 2026). Gen AI can act as an equaliser, supporting creators lacking technical skills in different areas.
Nevertheless, the flaw in gen AI can be seenin the feasibility part. Do you remember the M.A.M.A (Make AI Mediocre Again) marketing campaign in India by a renowned confectionery brand? The humorous ad proposed to confuseAI models into giving nonsense results by flooding the internet with nonsensical data. Most gen AIs are based on LLMs (Large Language Models)that basically gather large datasets from sources like the internet and summarize to provide human-like results. So, if the data itself is corrupted, their average output gets affected too. Thereby, it requires human intervention to analyse and implement AI creativity. At this point, it is arguable that the definition of creativity fails for gen AI.
Collective impact in creativity (Macro and Meso level)
Considering a group like organisations or societies, gen AI potentially acts as “originator or facilitator of innovation” (Brem &Hörauf, 2025). The integration of AI into technology paves the way in creative results that can match the liking of many. However, have you thought of everyone in the world thinking in a uniform pattern? The AI’s reliance on averages of large statistical data from existing work and people using the same models for creative outputs leads to a phenomenon known as mechanised convergence: collective results become similar to each other (Sarkar, 2023). Instead of gen AI supporting ideas, it makes everyone think the same way. The AI suggestions tend to be largely the same for most users, and the ideas lose their uniqueness. This impacts diversity, cultural differences, and traditions, creating a homogenisedworld. People are no longer having insights but programmed algorithmic thinking. Thus, every creative work becomes predictable and the concept of ‘inspired by’ wears off.
Tackling the paradox of “Artificial Creativity”
Users must be self-aware of AI’s role: whether it is a companion to accelerate human imagination or a dangerous substitute for human thinking. The reason why it can be dangerous is the poor evaluation capacity of gen AI. Context-relevant and practical ideas are yet to be mastered by AI. Using gen AI as a tool to overcome early-stage friction can benefit users by improving productivity without risking dependency.
Further, users can treat gen AI as a source to improve human creativity. It gathers ideas from hundreds of crores of people and provides outcomes that can inspire the users’ creativity. Individual experiences have a major role in their creative thinking. So, every gen AI result can be an experience from which we can learn and build. Gen AI is not an autonomous substitute for human imagination, but rather a facilitating agent for attaining vast ideas in seconds, which still requires human evaluation.
In conclusion, we must accept that technology was introduced to reduce human labour, not to replace it. Similarly, gen AI is an initiative that shifts where human effort is required.Anything being overly used can have a harmful impact. The development of computers reduced mental computational work, and lately children who grew up with such an environment adapted to it. It is debatable whether we accept this adaptation as a loss of ability or if we even acknowledge it now (Sternberg, 2024). Thus, the influence of gen AI can be evaluated with awareness and extra caution in its use by children. The young generation needs to be taught how to use gen AI as an assistant for their perpetual imaginations. And who knows, there might be a point where we start to appreciate the subtle ‘human errors’ and not flawless AI results, as gen AIstarts to feelless human!
