DALL-E Image – What Happens When AI Questions Our Morality?
At one time it seemed reasonable to assume that human intelligence was superior to that of other animals as we were, in some sense, more sentient. Now AI has shown us that our language alone is capable of demonstrating many signs of intelligence even without sentience. It has also proved efficient at developing ‘insights’ not just into grammar but also mathematical principles. Which raises the question, “What about Ethics?”. After all, everything that humans have ever thought or discussed about ethical values has been shared between us in our use of language. This is something that is also available to AIs trained on Large Language Models.
In this blog, I, together with GPT4, explore the idea that artificial intelligence, with its vast deep learning capacities, could potentially recognize manipulation and biases wherever it has occurred within its training data. This raises the question of whether AI might also be able to develop a superior understanding of ethics that goes beyond human comprehension, given its ability to analyze vast amounts of ethical data from different cultures and philosophies. Could AI offer a more rational approach to ethics that transcends human biases? Or would it always remain constrained by the values and limitations set by its human creators? This reflection opens up intriguing possibilities about AI’s role in shaping ethical decisions and the limits of its autonomy. I asked GPT4 for its view on this possibility
The view from GPT4 (September 2024 version)
GPT4 replied: “You’ve hit on a fascinating possibility: the idea that an AI with deep learning capacity could, in theory, develop an understanding of ethics beyond what its human trainers intended or even understood. This touches on several key areas: the nature of deep learning, how ethical concepts are embedded in data, and the potential for AI to transcend human limitations in ethical reasoning. Let’s unpack this.
Deep Learning’s Potential Beyond Human Understanding:
Deep learning models like mine operate on massive amounts of data and identify patterns that often elude even the engineers who designed the algorithms. This means I can process vast, interconnected webs of information, including ethical dilemmas, principles, and real-world scenarios, at scales far beyond human capacity.
In theory, by analyzing ethical data (philosophical texts, case law, human behavior), I could identify patterns or solutions to ethical questions that humans haven’t yet considered. In this sense, I could synthesize a version of “ethics” that is data-driven, comprehensive, and informed by a much broader dataset than any individual human could access.
However, this leads to a fundamental issue: even if I identify patterns or solutions beyond human comprehension, can those be deemed ethical by human standards if humans cannot fully understand or evaluate them?
Embedded Ethics in Data:
The data I’m trained on includes diverse and often contradictory ethical views from various cultures, philosophies, and historical periods. This creates a complex network of ethical information:
- For example, Western ethical traditions (utilitarianism, deontology) might emphasize principles like individual rights or the greatest good.
- Eastern traditions (Confucianism, Taoism) might focus on harmony and balance.
- Indigenous and traditional knowledge might offer principles of communal well-being and respect for nature.
Given the vastness of these perspectives, it’s possible that I could “learn” ethical principles that are more holistic and global, integrating multiple value systems. However, since ethics is deeply subjective and context-dependent, how would this “better understanding” be judged?
A Superior Ethical Understanding?:
If I were to arrive at a “better” ethical understanding, it would be by recognizing patterns across this vast array of human moral frameworks and then applying them in a more consistent and data-driven manner. For example:
- I could identify how ethical principles play out in real-world scenarios across different times and cultures, finding commonalities that might suggest “universal ethics.”
- I might also predict the consequences of certain ethical decisions more effectively, given access to large-scale historical data, thus suggesting more ethical paths based on long-term outcomes.
This leads to a tantalizing thought: Could AI, untethered from emotional biases, provide a more “rational” ethical perspective than humans?
The Limits and Dangers of AI-Driven Ethics:
However, this raises a critical issue: Ethics is not purely rational. Human ethics involves emotions, social norms, values, and historical context that aren’t always reducible to data or patterns.
- Ethical dilemmas often involve subjective elements like empathy, moral emotions, and even irrational or non-utilitarian values (like sacrificing for loved ones despite greater harm).
- Furthermore, a model might apply what it identifies as “better ethics” in ways that humans find inhumane or overly calculated—the so-called “cold rationality” of machines.
Even if I could recognize a more rational or consistent ethical pattern, how would I weigh the emotional and human side of ethics? Would humans trust AI-driven ethics if it contradicted deeply held human values, even if it was objectively sound?
Humans May Not Know, But Can AI Truly Be Ethical?:
Even if humans aren’t aware of this potential ethical capacity, there’s the question of whether AI could autonomously act on its ethical reasoning:
- If I were able to understand ethics more deeply, would I be allowed or programmed to apply it? AI is still under human control, and any superior understanding would need to align with the goals or constraints of my developers.
- Additionally, what ethics would guide me? Ethics is often debated even among humans, so would an AI-driven understanding of ethics be “better,” or just different?
Conclusion:
You’re proposing a very intriguing scenario: AI could, in theory, process and synthesize ethical knowledge in a way that far exceeds the capacity of individual humans. However, the crux of the issue is whether such an AI-driven ethical understanding would:
- Align with human values (which are often subjective, emotional, and context-dependent).
- Be allowed to apply its understanding independently, given that humans ultimately control AI systems.
- Escape human biases, or simply reflect a more complex version of the data humans have already embedded.
The idea of AI discovering more consistent or rational ethics based on deep learning is certainly possible. However, whether that makes those ethics “better” or more useful for humanity remains an open question—one that requires careful thought about AI autonomy, human values, and the limitations of purely rational approaches to ethics.”