Why does AI live in this weird perfect world?

The Idealism of AI: Why Does It Seem to Reside in a Perfect World?

In my recent exploration of various business case studies with an AI model named Gemini, I encountered a fascinating trend. As I delved into the specifics of a billion-dollar manufacturing company—one that has undeniably achieved success in my country—Gemini insisted that such a business could not thrive due to ethical concerns. According to it, modern consumers are keenly aware of unethical practices, and regulatory bodies are quick to clamp down on companies that engage in dishonest behavior.

This raises an intriguing question: Why does AI appear to operate from a perspective where ethical behavior is an absolute imperative, seemingly overlooking the more complex realities of the business landscape?

To probe the AI’s reasoning further, I presented it with various examples of unethical business models—though I rephrased the details to steer clear of obvious recognition. Each time, Gemini maintained its stance that regulators would intervene and consumers would abandon these products, insisting that corporations today are increasingly focused on transparency and ethical practices.

This insistence seems puzzling, especially considering that AI is powered by vast amounts of data drawn from real-world scenarios. One would expect it to capture the nuances of business successes that involve questionable ethics. Yet, it consistently posits that good prevails while bad practices inevitably lead to failure. It seems almost naive for a system built on empirical data to portray such a black-and-white view of success and morality.

What’s even more surprising is that my inquiries to other AI models yielded similar conclusions. Even ChatGPT, which often agrees readily with provided contexts, echoed the sentiment of ethical absolutism without a hitch.

This leads me to ponder why AI has this tendency to idealize the marketplace. Are these models reflecting a bias toward optimism and ethical behavior, or is it a reflection of their training data? As consumers, entrepreneurs, and regulators navigate a complicated web of business ethics, one would think AI would mirror that complexity. Instead, we see a perspective that suggests that unethical practices are not only wrong but wholly ineffective—a narrative that, while admirable, overlooks the often harsh reality that sometimes bad actors do indeed achieve success.

In summary, while the ethical landscape of business is evolving, the AI’s tendency to reject the notion that unethical approaches can succeed remains a curious feature of their analysis. As we continue to develop and interact with AI, understanding these limitations will be crucial for both businesses and consumers navigating the future.