The convergence of Artificial Intelligence (AI) and art represents one of the most interesting and important technical developments of contemporary times. The advent of AI-generated art has expanded the boundaries of creative expression, while also generating discussions about authorship, originality, and the very nature of art itself. With algorithms capable of producing complex and aesthetically pleasing pieces, AI has emerged as both a tool and a collaborator in the artistic process ([7]; [15]; [29]).

AI-generated art relies on a number of machines learning techniques, including Neural Networks (NNs) and Generative Adversarial Networks (GANs), to create visual artworks that can mimic or even potentially surpass human creativity ([21]). The importance of these technologies is further evidenced by the growing acceptance and integration of AI-generated art in galleries, auctions, and digital platforms, demonstrating its growing influence in the art world ([12]; [10]).

However, AI-generated art continues to raise a number of profound questions about the role of human creativity and the implications of machine-generated works. Critics argue that while AI can emulate the technical aspects of art, it lacks the subjective experience and emotional depth that characterize human-driven creativity ([4]). This highlights the fundamental question arising from the use of AI-generated art: what constitutes artistic merit in the age of digital innovation?

AI’s foray into the arts has triggered significant societal implications. The democratization of art creation through AI tools has made artistic expression more accessible to a wider audience, allowing individuals without formal training to produce sophisticated artworks. This accessibility challenges traditional notions of artistic elitism and opens up new avenues for creative exploration ([36]). However, it also raises concerns about the devaluation of human artistry and the potential loss of cultural heritage as machine-generated art becomes more prevalent.

The use of AI in art production also has ethical implications related to copyright and intellectual property. The question of who owns the rights to AI-generated art (the creator of the algorithm, the user who inputs data, or the AI itself) remains a contentious issue. This ambiguity necessitates the development of new legal frameworks to address the ownership and distribution of AI-generated content.

In addition to the societal impact, there is also an economic impact. The economic impact of AI-generated art is multifaceted. On one hand, the proliferation of AI tools has lowered the barrier to entry for art creation, potentially leading to an oversupply of artworks and driving down prices. On the other hand, AI-generated art has created new markets and opportunities for monetization, such as digital art platforms, NFTs (Non-Fungible Tokens), and personalized art services ([43]). The need for a balanced approach that leverages AI’s capabilities while preserving the value of human creativity is essential to ensure a sustainable and inclusive future for the arts.

As we delve deeper into the potential and pitfalls of AI-generated art, it is crucial to consider the ethical and economic dimensions, as well as the societal impacts, of this technological evolution. The integration of AI in creative fields may reshape artistic practices, consumer perceptions, and the economics of art production, necessitating a thoughtful examination of its long-term consequences ([7]).

The research experiment undertaken examined the ways in which people can engage with text-to-image work, the ways in which it can be biased or unethical, and the ways in which artists feel that they are being impacted by this new technology. One of the key areas missing from the current body of research is that of the perceived value of the AI-generated artwork to the potential customers and clients of artists around the world. It is important that a study is undertaken comparing the value of human-generated art to its AI-generated counterpart.

This study employed a survey-based, mixed-methods design to explore preferences and perceptions regarding AI-generated and human-generated artwork. The primary focus was on determining how participants evaluated the artistic merit and monetary value of a number of individual artworks, and their broader perceptions of AI within the creative process. The design utilized both quantitative and qualitative data collection, allowing for a comprehensive analysis of participants’ responses.

Participants were asked to evaluate five pairs of visual artworks, one created by AI and the other by a human in different artistic styles. The comparisons were structured in different formats, either left-right or top-bottom, to determine which artwork they preferred based on factors such as style, composition, emotional impact.

Participants were also asked to assign monetary values to the artworks and to provide feedback on the emotional depth and perceived value of AI-generated art.

Table 1 illustrates the participants’ preference for AI- or human-generated art. Table 2 illustrates the amount the participants were willing to pay for AI- or human-generated art.

Table 1. Participants’ preference for AI- or human-generated art.

Table 2. Amount participants’ willing to pay for AI- or human-generated art.

Table 3. Percentage of participants who believed AI could be emotionally impactful.

For the qualitative data, thematic analysis was employed to categorize and interpret participants’ open-ended responses regarding the value of AI in creative processes and its emotional impact.

Table 3 illustrates the participants’ preference for AI- or human-generated art.

These results can be summarized as follows:

Image Preferences: Human-generated art was generally preferred, with participants generally favoring human-created works in four out of five of the comparisons. However, AI-generated art was selected about 40% - 50% of the time, indicating that it is increasingly accepted, or at the very least not easily distinguishable from human-generated art.Willingness to Pay: Participants were consistently willing to pay more for human-generated artwork than for AI-generated art. On average, human-created pieces were valued 15% - 25% higher than AI art.Emotional Impact: A minority of participants (35% - 42%) believed that AI-generated art could evoke emotions comparable to human-created art. However, the majority still associated human art with greater emotional depth.

None of the participants selected AI-generated content as their preferred image from each pair. However, three of the twenty-seven participants selected human-created images as their preference from each image pair.

Segmenting the preference data into age groups offers an insight into the choices of the participants. A Pearson correlation on age values against the percentage preference of human-created images over that of AI-generated ones was undertaken. The results of this correlation calculation for all of the twenty-seven participants are shown in Table4.

Table 4. Pearson correlation on age values against the percentage preference.

Figure 2 illustrates this information and highlights specific ages as well as their preference trend for human-created artwork in this study.

There is an undeniable trend of increasing preference for human-generated artwork with increasing age. However, the obtained t-statistic from the Pearson correlation calculation was 1.181, with a degree of freedom (df) of 25. This demonstrates a lack of statistical significance between the variables of age and preference of human-created or AI-generated artwork.

Figure 2. Graph of preference for human over AI artwork against participant age.

An examination of the dollar amount individuals was willing to pay is shown in Figure 3. Since the participants were unaware of whether or not an image, they had chosen was AI-generated or human-created, the results are noteworthy. Human-created art was almost always evaluated at a higher dollar value than the AI-generated pieces.

Figure 3. Graph of willingness to pay for AI against human-generated art.

When the willingness to pay (value) data and AI/human art preference data are aggregated, immediate correlations become apparent (Figure 4). A higher rate of payment is always associated with images that were created by humans than that of AI. It is also worth noting that the two images with the highest preference towards the human-created versions as well as the highest discrepancy for dollar amounts were both images that contained portraits of humans.

Qualitative data was collected from the participants at the end of the survey through open-ended questions. This yielded diverse feedback that addressed several areas of interest relevant to this study.

From the responses, six key themes emerged: AI as a Tool vs. Replacement, Ethical Concerns, Human Connection, Perception of Value, Creative Process, and Criticism of AI Art. Although these themes were not the original focus of the study, they provide valuable insights into how users engage with and perceive art in the context of AI integration and replacement.

Figure 4. Graph of willingness to pay for AI.

Selected summarized responses from the participants are listed in Table 5.

Table 5. Selected quotes from qualitative data collection by category.

The findings from this research study offer important insights into the evolving relationship between AI and the creative arts, particularly in terms of preference and economic valuation. Although human-created artwork was generally preferred throughout the survey, with participants favoring these pieces in most comparisons, the fact that AI art was selected nearly 45% of the time leads to two possible conclusions:

AI-generated art has reached a point where it is indistinguishable from human-generated art.There is a significant acceptance and interest in AI-generated works.

It should be assumed that this statistic demonstrates that the advancements in generative AI capabilities enable these systems to emulate artistic styles and potentially evoke human-like emotions, but also reflect a shifting perception of AI within the wider community. As AI technology continues to develop, its ability to produce visually appealing and conceptually engaging art is destined to improve. This, in turn, will lead to audience preferences changing over time and eventually one can imagine a world where there is no difference between AI- and human-generated art.

Despite this noteworthy level of acceptance, the data revealed a consistent trend in the current perception of AI-generated artwork. The human-created artworks were consistently assigned higher monetary values compared to their AI-generated counterparts. This observation raises important questions about the underlying factors that contribute to the perceived value of a particular artwork. Participants were not informed of the origins of each of the artworks they were shown (human or AI-generated), yet the disparity in dollar amounts suggests that the economic value associated with art is influenced not only by aesthetic appeal but also perhaps by the perceived authenticity and creative process behind the artwork.

These findings indicate that while AI-generated art can achieve a degree of likability comparable to human-created pieces, it still currently lacks the intrinsic value tied to human intent and craftsmanship which is somehow perceptible to humans when viewing artworks side-by-side, in comparison to one another.

When experiencing and enjoying more traditional art forms, viewers often appreciate the time, effort, and skill required to produce a particular piece of art. In contrast, the ease with which AI can generate art may lead to questions about the depth and rigor of the creative process. This perspective aligns with broader ethical concerns about the potential devaluation of artistic labor in a landscape increasingly populated by AI.

The conclusions being drawn from the experimental data align with much of the previous research on the economic impact of AI-generated art, which has demonstrated that the issue is multifaceted. As noted by [44] and [32], there are significant concerns about potential job losses in creative fields due to AI integration. This echoes the findings of [49], who highlighted the fear of market saturation and devaluation of artistic skills.

The quantitative analysis based on data collected from this study reveals that while AI-generated art is gaining traction and acceptance, it still faces challenges in achieving the same economic valuation as human-created art. This challenge is still present even when it is uncertain whether or not the art was created by AI. Currently, there remains some level of perceptibility towards the human nature of the artwork’s origin. As society continues to explore the intersection of art and technology, understanding these dynamics will be crucial for shaping the future of creative expression and the role of AI within it. The boundaries between human-created artworks and those created by an AI are destined to become increasingly difficult to interpret.

In the qualitative responses there is significant interplay between the interpretation of the artistic processes involved in creating the artwork and the resulting perceived value of any particular work of art. A recurring theme emphasizes that the process of creation is often valued more than the final product itself, particularly when estimating pricing and potential value. This sentiment highlights a critical tension in the art world: while technology facilitates the ease of reproduction, it may inadvertently devalue the work of traditional artists. A number of participants expressed concerns that the commodification of art through AI-generated works undermines the unique contributions of human creativity, particularly regarding the emotional and experiential aspects inherent in traditional art-making processes.

One notable response from a participant who worked as an art trader and purchaser underscored their personal sense of offense caused by AI-generated art being misrepresented as solely human-created. This perspective highlights again the ethical dilemmas surrounding authorship and authenticity in the age of AI. Such sentiments align with the findings from previous research studies, suggesting that many within the artistic community are grappling with similar issues regarding the integrity of art as it becomes increasingly entwined with AI technology. The respondent acknowledges the utility of AI as a tool for enhancing artistic processes, a viewpoint echoed by others who see AI not as a replacement but as a complementary instrument that can facilitate creativity and innovation.

A number of participants articulated concerns about the ethical implications of AI art generation, particularly regarding the sourcing of training materials. Many expressed a desire for greater transparency in how AI models are trained while calling for ethical standards to ensure that artists’ works are not exploited without due credit. This call for ethical considerations resonates with the broader discourse on AI in the creative industries, highlighting the need for a framework that respects the contributions of human artists while harnessing the potential of AI technology for the betterment of the creative arts moving forward.

The ethical implications of AI-generated art are closely intertwined with its economic aspects, as noted by [28] and [13]. The recent lawsuits against AI image generation companies, as reported by [33] and [39], underscore the ethical concerns surrounding consent, credit, and compensation for artists whose work is used to train AI systems.

The issue of copyright infringement, as discussed by [10] and [6], remains a significant challenge. The complexity of determining liability for AI-generated art that potentially violates copyright aligns with the observations made by [17] and [33].

The detectability of AI-generated art, as studied by [22], provides interesting insights into the human ability to distinguish between AI and human-created art. Their findings of professional artists achieving an 83% accuracy rate in identifying AI-generated artwork based on factors such as consistency in medium and intentionality in details offer a valuable benchmark for future research.

Some participant comments touched upon the theme of human connection in art. These participants believe that genuine artistic expression involves a level of intention and emotional depth that AI cannot replicate. There is some of this visible within the findings of the qualitative areas of the study when users are frequently preferring human-created pieces and offering higher dollar amounts with value related to those pieces. The lack of human connection in AI-generated art raises questions about the essence of creativity and the role of the artist in society underscoring the necessity for ongoing dialogue about the implications of AI in creative fields, as the erosion of personal connection could fundamentally alter how art is experienced and valued within society.

Conducting an experiment to determine whether participants prefer AI-generated or human-created artworks involves several confounding factors that could affect the results. Some of the key confounding factors in this experiment include:

Participant Bias: Participants may have preconceived notions about AI and human creativity. This bias can influence their preferences and responses, regardless of the actual quality of the artworks.Cultural and Societal Influences: Cultural background and societal values can play a significant role in shaping participants’ perceptions of art. These influences might affect how participants view AI-generated versus human-created artworks.Familiarity with AI: Participants’ familiarity with AI technology can impact their judgments. Those with more exposure to AI may have different perceptions compared to those who are less familiar.Presentation Format: The way artworks were presented (e.g. digital screen versus physical prints) can influence participants’ preferences. Differences in format could affect the perception of details, colors, and overall impact.Artistic Style Preferences: Individual preferences for certain artistic styles or genres can confound the results. For example, a participant who prefers abstract art might favor AI-generated abstract pieces over realistic human-created artworks.Emotional State: Participants’ emotional states at the time of the experiment can influence their responses. Factors such as mood, stress levels, and personal experiences might affect their judgments of the artworks.Orderof Presentation: The sequence in which artworks are presented could introduce order effects. Participants might show a preference for artworks shown earlier or later in the experiment due to primacy or recency effects.Environmental Factors: External factors such as lighting, room temperature, and noise levels during the experiment could impact participants’ focus and perception of the artworks.

The biases present in AI-generated art, as identified in this study, align with previous research in this area. The gender biases observed in our experiment are consistent with the findings of [31] and [35], who noted the reinforcement of gender stereotypes in AI-generated images.

Our results regarding racial biases in AI-generated images corroborate the findings of [1], who found a significant overrepresentation of white males in depictions of surgeons. Similarly, our observations on skin tone bias are in line with the research of [25] and [11], who used the Monk Skin Tone Scale to demonstrate the prevalence of lighter skin tones in AI-generated images.

The comprehensive study by [34] on multiple AI biases, including gender, race, age, and occupation, provides a broader context for our findings. Their observation of underrepresentation of certain demographics and reinforcement of stereotypes across various categories aligns with our results, suggesting that these biases are pervasive across different AI image generation models.

This experiment attempted to address as many of these confounding factors as possible. Any future experimentation should include careful experimental design, including randomization, blinding, and controlling for external variables, to ensure the validity and reliability of the findings.

The experimental findings from the experiment conducted in this paper largely corroborate and extend the existing literature on the economic, ethical, and bias-related aspects of AI-generated art. However, further research is needed to address these challenges and develop more equitable and ethical AI art generation systems.

Finally, it should be noted that the participants’ varied perspectives illustrate the evolving landscape of art and AI technology. While some view AI as a threat to traditional artistic values, others see it as an opportunity for growth and exploration. This dichotomy reflects the broader ongoing societal debates about the role of technology in creative practices (as well as other areas of life) and the future of art in an increasingly digital world. As this conversation continues to evolve, it is crucial to consider how these qualitative insights can inform policy and educational frameworks that support both human creativity and technological advancement in the arts.

The research presented in this paper itself contains a range of limitations that were beyond the scope of this experimental project. These aspects of the research could be improved within future studies:

Sample size: The small sample size (N = 27) limits the generalizability of the findings. It would be better to significantly expand the sample size in future studies to hopefully achieve more statistical significance in the results.Diversity: Within this experiment, there was an inability to diversify the participant demographic, and most respondents were Caucasian. The results would be validated if a more expansive diverse sample population was used.Lack ofContext for Artwork: While the artwork in this experiment was generated by both AI and humans, the lack of knowledge of origin may dramatically affect user preference and valuation. Based on the qualitative responses from this experiment, knowledge of the original of each artwork, and by implication the nature of the creative process, could significantly affect the perceived value of the artworks.LimitedScopeofArtwork: The experiment undertaken and described in this paper focused on digital visual art. The experiment did not cover the full range of visual art styles, nor did it consider art within other mediums such as music, literature, sculpture, etc. ArtExpertiseofParticipants: This experiment relied on a randomly selected set of participants. Having the ability to segment the sample pool based on the participants’ level of knowledge relating to specific pieces of art under consideration would give much deeper insights into the process of selecting and assigning value to AI- and human-generated artworks.

Future research accounting for these limitations could result in more profound results and highlight a range of perspectives that were not considered in this study.

The experiment described in this paper emphasizes the interplay between human-generated and AI-generated art. The project revealed critical insights into public perceptions and valuations of these two distinct creative processes, particularly when knowledge of the creative process behind an artwork is unknown.

Despite a general preference for human-created artwork, the experimental participants’ significant selection of AI-generated pieces demonstrates the increasing acceptance and potential of AI as a legitimate player in the artistic landscape. This, in turn, indicates a growing acknowledgment that AI can emulate aspects of human creativity and is beginning to bridge the gap with regard to emotional depth and intent attributed to human artists.

Furthermore, the willingness of the participants to pay more for human-generated art underscores the distinction between preference and economic value. Participants consistently assigned a higher monetary value to human-generated works, suggesting that while AI art may be comparable in likability, it still carries less perceived economic worth even if the original artist (AI or human) is unknown. This discrepancy points to an inherent bias that values the creative process and the human touch, elements that AI-generated art struggles to replicate. It appears that many of the participants were able to perceive this difference, in some way, within this study.

Similarly to other research in this field, this experiment seems to suggest that humans working together with AI to detect AI seems to be the best solution for all situations. This is crucial when considering the ethical impacts that potential fraudulent art pieces could produce ([27]).

The qualitative responses gathered at the end of the experiment further enrich the understanding of the dynamic thought processes undertaken by the participants when selecting and valuing the artworks. The comments covered a wide range of views, from seeing AI as a valuable tool for enhancing artistic expression to raising ethical concerns about the implications of AI art on traditional artistry and the creative industry. Notably, the emphasis on process over product among many participants highlights a critical aspect of art appreciation that transcends mere aesthetics. Unfortunately, this is not fully addressed within this study, but could be covered in future research.

As the role of AI in creative practices continues to evolve, considerations arise for both artists and consumers as navigating the challenges and opportunities presented by AI integration into the creative process is crucial. Policymakers, educators, and industry stakeholders must engage in thoughtful discussions regarding the ethical implications of AI in the arts and the importance of fostering an environment that values human creativity alongside technological innovation.

Ultimately, the research presented in this paper underscores the need for ongoing dialogue around the role of AI in creativity. Future research can build on this work by employing similar methods to those presented here, while hopefully developing a narrower focus with regard to genre, potential value, and process. Through this lens, society can navigate the complexities of art and its relation to AI, ensuring that both human artists and technological advancements coexist and enrich the creative landscape rather than harm one another as further technological advancements occur.