AI Explained: Is Anthropomorphism Making AI Too Human?

As eCommerce giants and tech startups strive to make online interactions more engaging, they’re turning to anthropomorphism — attributing human characteristics to nonhuman entities.

It isn’t a new concept. For decades, companies have used anthropomorphic mascots and branding to create emotional connections with consumers. The Michelin Man, Tony the Tiger, and Mr. Clean have long been fixtures in advertising. But now, this strategy is applied to AI, with intriguing and sometimes perplexing results.

Chatty Bots

Major players in the eCommerce world are at the forefront of this trend. Amazon’s Alexa, for instance, goes beyond simple voice recognition. Users can ask Alexa to tell jokes, play games or give relationship advice. Google’s virtual assistant can engage in small talk and has a range of Easter eggs programmed in, like the ability to beatbox or flip a virtual coin.

In customer service, AI-powered chatbots are increasingly being imbued with human-like qualities. Companies like Replika and Xiaoice have developed chatbots that aim to engage in emotionally intelligent conversations. These bots are designed to remember past interactions and adapt their personalities to individual users, mimicking the development of a human relationship.

The financial sector is also experimenting with anthropomorphic AI. Robo-advisors like Wealthfront and Betterment now come with friendly interfaces and conversational abilities, aiming to make financial planning more approachable. Some even have avatar representations to give a face to the AI advisor.

Retail is another area where anthropomorphic AI is making inroads. Sephora’s Virtual Artist uses AI to allow customers to try makeup virtually while providing personalized recommendations conversationally. Stitch Fix combines AI algorithms with human stylists to create a customized shopping experience, with the AI component designed to feel like a knowledgeable friend offering fashion advice.

However, this approach is not without its challenges. As AI becomes more human-like in its interactions, it can sometimes lead to confusion or unrealistic user expectations. In documented cases, customers have developed emotional attachments to AI assistants or mistaken them for real human operators, raising ethical concerns about the boundaries of human-machine interactions.

Users developing feelings for AI are not limited to individual consumers. A conversational AI called Xiaoice, developed by Microsoft for the Chinese market, received millions of messages saying “I love you” from users. This level of emotional engagement with AI raises questions about the psychological impact of anthropomorphic design in technology.

These issues become even more complex in the context of commerce. When an AI is designed to build rapport and trust with users, there’s a fine line between effective customer service and potential manipulation. The ability of AI to remember past interactions and personalize its approach could be seen as either a helpful feature or an invasion of privacy, depending on the perspective.

Experts in fields ranging from psychology to ethics are grappling with these questions. Kate Darling, a researcher at MIT Media Lab, has studied human-robot interaction and the implications of anthropomorphizing technology. Her work suggests that while anthropomorphism can make interactions with technology more intuitive, it also raises complex ethical questions about how we treat AI and what we expect from it.

The legal and regulatory landscape also struggles to keep up with these developments. In 2019, the California Consumer Privacy Act (CCPA) went into effect, requiring businesses to disclose their data collection and sharing practices to consumers. As AI systems become more personalized and human-like, such regulations may need to evolve to address the unique challenges posed by anthropomorphic AI in commerce.

Navigating this new landscape requires a delicate touch for businesses. The potential benefits of more engaging and relatable AI are clear. A study published in the Journal of Marketing found that anthropomorphized chatbots led to higher customer satisfaction and increased purchase intentions compared to non-anthropomorphized versions. However, the same study also noted that these effects were moderated by customers’ awareness of the chatbot’s artificial nature.

As we progress, anthropomorphic AI integration in eCommerce will likely become more sophisticated. Advances in natural language processing and machine learning may lead to AI systems that are increasingly adept at mimicking human conversation and behavior. Companies like OpenAI and Google’s DeepMind are pushing the boundaries of what’s possible in AI language models, which could have implications for how we interact with AI in commercial settings.

However, as these technologies evolve, so must our understanding of their implications. Transparency will be key — companies will need to be clear about the nature and limitations of their AI systems, even as they design those systems to be more approachable and human-like.

Anthropomorphism and eCommerce

The debate around anthropomorphic AI extends beyond just commercial applications. The European Parliament passed a resolution to create “electronic personhood” for sophisticated autonomous robots. While primarily focused on liability issues, it hints at the broader societal questions we may need to grapple with as AI becomes more human-like in its capabilities and interactions.

In the end, the success of anthropomorphic AI in eCommerce will likely depend on finding the right balance — human enough to be engaging and valuable but not so human-like as to be misleading or unsettling. As we navigate this new frontier, consumers and businesses must adapt to a world where the line between human and machine interaction becomes increasingly blurred.

The quirks of anthropomorphic AI in eCommerce are more than just amusing anecdotes. They represent a fundamental shift in how we interact with technology and conduct business in the digital age. As AI continues to evolve, so will our understanding of what it means to be “human-like” in bits and bytes.

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