Who is responsible for the actions of machines? Questions around who is responsible for the behavior of generative statistical algorithms, like large language models, have direct implications for our daily lives. Particularly as they become increasingly "intelligent". We chat with Pelin Kasar about the current state of philosophical debates around how to approach the ethical considerations of machines that seem to think.
Show Notes:
Complexity of AI Responsibility: Attributing responsibility in the context of AI, emphasizing the difficulty in delineating between AI and human accountability.
Defining Responsibility: The foundational aspects of responsibility, necessitating control and knowledge for intentional action, and how these apply to both humans and potentially AI systems.
Instrumentalism vs. Machine Ethics: Two philosophical positions on AI responsibility: instrumentalism, which focuses on human responsibility over tools, and machine ethics, which considers attributing moral agency to machines.
Extended Agency and Hybrid Responsibility Models: Distributed or joint responsibility between humans and AI, suggesting a nuanced approach that recognizes the role of both in ethical and responsible decision-making.
Challenges of AI in Ethical Decision-Making: The practical and philosophical challenges in applying traditional ethical theories to AI behavior, especially concerning autonomy, intentionality, and the capacity for moral reasoning.
The Role of Data and Bias: Data selection and inherent biases in AI systems, stressing the ethical implications of data-driven decision-making processes.
Legal and Ethical Frameworks for AI: Developing comprehensive legal and ethical frameworks that adequately address the unique challenges posed by AI, including accountability, transparency, and fairness.
Moral Significance of AI Tools: The moral significance attributed to AI tools and systems, suggesting that while they may not possess moral agency, their role in ethical considerations is crucial.
Predictive Responsibility and Control: The relationship between an agent's ability to predict outcomes and their ethical responsibility, especially in the context of developing and deploying AI systems.
Societal and Philosophical Implications: Broader societal and philosophical implications of AI and responsibility, questioning how advancements in AI technology challenge our traditional understanding of agency, ethics, and responsibility.
References
Daniel Dennett: Mentioned in the context of instrumentalism, suggesting that the ascription of mental states to entities can be useful for practical purposes.
Deborah Johnson: Referenced for her views on AI and ethics, particularly her perspective on machines as moral entities rather than agents with full moral responsibility.
Clark and Chalmers: Philosophers known for the extended mind hypothesis, which suggests that objects in the environment can become part of the mind's machinery.
Responsibility Attribution: Explores how responsibility is assigned, especially in the context of intentional actions by human agents.
Intentional Action: The idea that for an action to be considered intentional, it must satisfy certain conditions such as control and knowledge by the agent.
Agent with Mental States: Discusses the importance of agents having desires, beliefs, and intentions for their actions to be considered morally significant.
Instrumentalism: View that the usefulness of attributing mental states to entities (like AI) can justify such attributions without asserting their factual possession of these states.
Implicit Bias: The unconscious biases that affect decisions and actions, complicating the attribution of responsibility.
Extended Mind and Agency Theories: Philosophical concepts suggesting that tools and technologies can extend human cognitive processes and by extension, possibly, moral and ethical agency.
Hybrid Responsibility Accounts: The idea that responsibility in the context of AI might be distributed across both human agents and the AI systems themselves.
Machine Ethics: A field of study that explores the possibility of imbuing AI with ethical principles or considering them as moral agents in their own right.
Extended Agency: The notion that agency can be shared or extended through the use of external tools or systems, influencing actions and decisions.