Four key behavioral factors can influence why there is a lack of attribution for GenAI use:
Convenience bias This bias may drive people to use Gen AI tools as they can significantly simplify tasks that would otherwise require considerable time and cognitive effort. In the race to be more productive or creative, individuals may overlook or undervalue the role of original creators, focusing instead on the immediate utility the AI offers. Social influence The "bandwagon effect," for instance, could lead people to adopt Gen AI tools because others in their social or professional circles are doing so. This social proof often acts as a validation of the tool's usefulness. Still, it can also make individuals less critical of the ethical and legal considerations involved, such as copyright infringement or attribution.
The Dunning–Kruger effect
Not-invented-here syndrome This is where individuals and organizations often undervalue innovations and creations not directly linked to them. It can manifest as a reluctance to appropriately credit original data sources when utilizing Gen AI tools, stemming from a cognitive dissonance regarding external contributions to what they perceive as "their" project. Interestingly, studies across groups of students, entrepreneurs, leaders, and employees demonstrate that the higher the person's creativity, the higher the chance of them engaging in unethical practices. Given our behavioral tendencies, the future of attribution and copyright in GenAI should include parameters and guidelines on best practices of giving due credit. This effect posits that people with limited knowledge overestimate their grasp of complex subjects. In the Gen AI domain, users may mistakenly believe they fully understand the intricate legal implications of using AI-generated content. Unfortunately, this overconfidence can lead to neglect or inadvertent disregard for critical issues such as attribution and copyright, resulting in undesirable consequences.
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