Bridging AI and Philosophy: Exploring Non-Western Perspectives

Bridging AI and Philosophy: Exploring Non-Western Perspectives

Table of Contents

1. Introduction
2. What is AI Alignment?
3. The Philosophical Tendencies in AI Alignment Research
   1. Connectionism and Sub-symbolic Representations
   2. Behaviorism and Reinforcement Learning
   3. Humane Theories of Motivation
   4. Decision Theory and Rationality
   5. Consequentialism and Ethics
4. The Need for Philosophical and Disciplinary Pluralism
5. Examples of Non-Western Philosophy in AI Alignment
   1. Representing and Learning Human Norms
   2. Robustness to Ontological Shifts and Crises
   3. Valuing and Disvaluing: The Phenomenology
6. The Value of Pluralism in AI Alignment
   1. Avoiding the Streetlight Fallacy
   2. Robustness of Moral and Normative Uncertainty
   3. Pluralism as Political Pragmatism
   4. Pluralism as an Ethical Commitment
7. Steps Forward: Embracing Pluralism in AI Alignment Research
8. Conclusion

Introduction

Today, we live in an age dominated by advancements in artificial intelligence (AI). As AI continues to evolve, so does the importance of AI alignment - the practice of building intelligent systems that act in accordance with human values. However, the field of AI alignment has mainly been influenced by a narrow set of philosophical perspectives. This article aims to highlight the need for greater philosophical and disciplinary pluralism in AI alignment research by exploring the Current tendencies and the potential contributions of non-Western philosophy.

What is AI Alignment?

AI alignment refers to the project of developing AI systems that are aligned with human values and interests. This is considered a crucial cause area due to the potential impact of AI on the future of our civilization. The task of aligning AI with human values is challenging, as human values are complex and often Context-dependent. Simple solutions may lead to catastrophic outcomes, highlighting the need for extensive research and collaboration in the field.

The Philosophical Tendencies in AI Alignment Research

Current AI alignment research exhibits several philosophical tendencies that Shape its approach. These tendencies include:

1. Connectionism and Sub-symbolic Representations: AI alignment research tends to focus on neural networks and deep learning, prioritizing interpretability, scalability, and robustness.

2. Behaviorism and Reinforcement Learning: The emphasis is on modeling humans as reinforcement learning agents, learning from data rather than employing reasoning and planning.

3. Humane Theories of Motivation: AI alignment often models humans as motivated by reward signals or desires, neglecting the role of reasons and principles in human motivation.

4. Decision Theory and Rationality: Rationality is primarily defined in decision-theoretic terms, emphasizing expected value maximization and Bayesian inference.

5. Consequentialism and Ethics: AI alignment tends to view value and ethics in terms of outcomes and states of the world, often aligning with consequentialist frameworks.

The Need for Philosophical and Disciplinary Pluralism

The current state of AI alignment research reveals a lack of interdisciplinary collaboration and philosophical diversity. This limited perspective hinders the exploration of crucial considerations and alternative solutions. To overcome this challenge, the field needs greater philosophical and disciplinary pluralism. This would involve engaging with multiple philosophical traditions and paradigms to tackle the complex problems of AI alignment effectively.

Examples of Non-Western Philosophy in AI Alignment

Non-Western philosophy, such as Confucian ethics and Buddhist philosophy, has the potential to provide valuable insights and solutions to open problems in AI alignment. For instance:

1. Representing and Learning Human Norms: Confucian ethics emphasizes the importance of social norms and practices in shaping human values and behavior. This perspective can inform AI systems on how to infer and internalize human norms.

2. Robustness to Ontological Shifts and Crises: Buddhist philosophy challenges the Notion of an objectively real world and offers insights into dealing with ontological shifts. It suggests iterative approaches to changing representations and conceptual engineering to better suit our goals and minimize suffering.

3. Valuing and Disvaluing: The Phenomenology: Buddhist, Jain, and Vedic philosophies explore the subjective experiences and varieties of valuing. These perspectives can inform AI systems in understanding and learning human values more effectively.

The Value of Pluralism in AI Alignment

Embracing philosophical pluralism in AI alignment research offers several advantages, such as:

1. Avoiding the Streetlight Fallacy: Diversifying philosophical perspectives helps prevent the oversight of crucial insights present in non-Western philosophical traditions.

2. Robustness of Moral and Normative Uncertainty: Pluralism allows for a broader range of approaches to address moral and normative uncertainty in AI alignment, reducing the risks of misalignment.

3. Pluralism as Political Pragmatism: Engaging with various philosophical perspectives fosters inclusivity and political pragmatism, increasing the likelihood of societal acceptance and buy-in for AI systems.

4. Pluralism as an Ethical Commitment: Respecting and embracing pluralism aligns with the Core principles of autonomy and equal consideration of value. It recognizes the diversity of human values and aims to preserve them in AI systems.

Steps Forward: Embracing Pluralism in AI Alignment Research

To incorporate greater pluralism in AI alignment research, prospective researchers and funders should consider the following steps:

1. Encourage interdisciplinary collaboration and engagement with multiple philosophical traditions.
2. Foster support for AI alignment research in various disciplines, including human-computer interaction, cognitive science, ethics, and academic philosophy.
3. Recognize and address founder effects and participation barriers, ensuring a more diverse and inclusive research community.
4. Lower barriers to participation and promote the ethical consideration of multiple perspectives.

Conclusion

AI alignment is a complex and challenging field that requires interdisciplinary collaboration and a diverse range of philosophical perspectives. By embracing philosophical pluralism, researchers can expand their understanding of AI alignment and reduce the risk of misalignment. Non-Western philosophy offers valuable insights and solutions to open problems in AI alignment. Moving forward, it is essential to foster an inclusive, pluralistic approach in the pursuit of aligning AI with human values.