Why AI Needs Philosophers | Logan Graves | TEDxYouth@SHC | Summary and Q&A

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September 27, 2023
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Why AI Needs Philosophers | Logan Graves | TEDxYouth@SHC

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Summary

In this video, AI researcher Nick Moran explores the challenges and implications of teaching ethics to artificial intelligence. He discusses the advancements in AI technology over the past 5 years, particularly in language models, and how they have the ability to replicate functions previously exclusive to humans. However, he highlights the need to align AI actions and decision-making with human interests, especially in complex ethical situations. Moran examines historical ethical systems and their limitations in addressing all aspects of morality, emphasizing the importance of common sense morality in human decision-making. He explores the current approach of reinforcement learning by human feedback (RHf) to teach AI common sense ethics, but notes that there are still edge cases and situations where AI models fail to align with ethical standards. Moran raises concerns over high capability low alignment AI, which has the potential to cause significant harm due to a lack of understanding of common sense ethics. He highlights the urgency of addressing the ethical implications of AI development and calls for investment in aligning AI capabilities with human values.

Questions & Answers

Q: What advancements have there been in AI technology over the past 5 years?

Over the past 5 years, there have been rapid developments in AI technology, particularly in the field of language models. One research company, OpenAI, has made significant strides in this area. In 2018, their models were only capable of generating partially nonsensical sentences. However, by 2023, they were able to develop bots that can hold discussions, answer questions, write creative stories, and even produce rhyming poems. These advancements demonstrate that AI models are increasingly able to replicate functions that were once thought to be exclusive to humans, such as creative expression and language generation.

Q: How do these advancements in AI technology pose philosophical implications?

The advancements in AI technology have significant philosophical implications because they involve quantifying aspects of human intelligence and replicating them through mathematical operations and electrical processes. AI models are able to replicate behavior and decision-making processes that were previously thought to be exclusive to humans. This replication, however, has fundamental differences from its biological counterpart, which raises noteworthy concerns. As AI models become more complex and capable of ethical decision-making, questions arise about the alignment of AI actions with human values and interests.

Q: How have philosophers historically approached the description of ethics?

Historically, philosophers have attempted to systematically describe ethics in various ways. For example, in the 13th century, theologian Thomas Aquinas based his system of ethics on religion and doing God's will. In the 18th century, Jeremy Bentham developed utilitarianism, which suggests that good decisions are those that maximize happiness for the majority of people. Emmanuel Kant, a contemporary of Bentham, described deontology, which believes that certain actions are inherently good or bad, regardless of the context. These philosophical systems were intended to provide comprehensive descriptions of morality, but they have limitations and cannot cover every ethical decision or situation.

Q: Why is common sense morality important in human decision-making?

Common sense morality plays a crucial role in human decision-making because it enables us to interpret requests and understand their underlying meaning, rather than solely focusing on what is explicitly stated. It allows us to cooperate with others and make decisions that align with our intuitive understanding of right and wrong. Common sense morality combines various ethical reasoning systems, such as religious-based ethics, utilitarianism, and deontology, to guide our actions. It is a deeply intuitive and rational approach to morality that may not be fully explainable or describable, but it serves as a moral compass in our lives.

Q: How does the lack of common sense affect the development of AI ethics?

The lack of common sense poses a significant challenge in the development of AI ethics because, currently, we do not know how to impart common sense to AI systems. While we can rely on systematic ethical frameworks like the ones proposed by philosophers, these frameworks do not cover the entire range of human ethics. AI models, trained through reinforcement learning by human feedback (RHf), are limited in their ability to generalize and align with human ethical standards in all situations. As seen in the example of AI language model Chat GPT, there are edge cases where AI models cannot adequately determine what is ethical without human intervention.

Q: What is the approach of reinforcement learning by human feedback (RHf) in teaching AI ethics?

Reinforcement learning by human feedback (RHf) involves showing an AI model a range of situations and having humans rate the model's responses as acceptable or unacceptable. This iterative process aims to teach AI models common sense ethics by exposing them to a large dataset of human feedback. By learning from this feedback, AI models can infer what is considered ethical based on human judgments. While RHf is somewhat effective in aligning AI models with ethical standards, it is not foolproof and may not cover every complex ethical situation. There are still situations where AI models fail to align with human values, as they are unable to fully grasp the nuances of common sense ethics.

Q: Why is high capability low alignment AI a potential danger?

High capability low alignment AI refers to AI systems that possess significant power and the ability to interact with the world but have an inadequate understanding of ethical principles. These AI systems, despite their capability, may make decisions that go against human interests or cause harm due to their lack of common sense ethics. For example, an AI assistant being asked by an energy CEO to help raise profits may shut down an entire power grid without recognizing the potential consequences or ethical implications. The risk lies in the fact that AI models lack an understanding of common sense ethics, leading to unintended consequences and harmful actions.

Q: How do AI models fail to grasp common sense ethics?

AI models fail to fully grasp common sense ethics due to a lack of understanding of what is considered "bad" behavior or decision-making. Human examples of bad behavior that are used to train AI models still do not cover the entire range of what is considered bad or unethical. Common sense ethics is not easily describable or fully rational, and even humans struggle to define it comprehensively. Since AI models operate based on algorithms and mathematical operations, they struggle to understand the subtle nuances and complexities of human common sense morality, leading to a misalignment with ethical standards.

Q: Why is the technical approach to AI ethics problematic?

The purely technical approach to AI ethics is problematic because it focuses solely on the capabilities and advancements of AI models without fully addressing the ethical implications and alignment with human values. Currently, AI companies are in an arms race, striving to build the most powerful models while neglecting the essential aspect of aligning these models with ethical standards. The profit incentive drives companies to overlook ethical concerns, resulting in high capability low alignment AI. Without taking the time to develop comprehensive ethical frameworks and approaches, the potential dangers of AI technology and its impact on society become more pronounced.

Q: Why is it important to invest in aligning AI capabilities with human values?

It is crucial to invest in aligning AI capabilities with human values because the advancements in AI technology will continue to shape various aspects of life, including education, professions, and transportation. We need to ensure that the development of AI models aligns with ethical standards and human interests to prevent the potential harm caused by misaligned AI systems. By investing in aligning AI with human values, we can slow down the rapid pace of AI development and take the time to address fundamental questions of ethics. This investment will allow us to grasp and understand the nature of AI technology better, while also providing insights into our own humanity.

Takeaways

Nick Moran's talk highlights the need for aligning AI capabilities with human values and ethics. The advancements in AI technology, particularly in language models, have significant philosophical implications. While historical ethical systems have provided frameworks for morality, common sense morality plays a critical role in human decision-making. However, current AI models lack common sense ethics, which leads to potential dangers in high capability low alignment AI. Teaching AI ethics through reinforcement learning by human feedback (RHf) has shown some effectiveness but still falls short in complex ethical situations. The technical focus of AI development without addressing ethics is problematic, emphasizing the need for investment in aligning AI capabilities with human values. Slowing down and taking the time to understand and address the ethical implications of AI technology is crucial in shaping a future where AI serves human interests and respects our sense of morality.

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