Chatting with AI: Developing Enhanced Language Models
Introduction:
New research in the fields of pragmatics and philosophy aims to address the limitations and risks of conversational agents by aligning them with human values. These agents, powered by advanced language models, have shown impressive capabilities in tasks like translation and question-answering. However, they have also exhibited potential issues such as toxic language and misleading information. Previous approaches focused on reducing these risks, but this new paper takes a different approach by exploring the ideal communication between humans and conversational agents. Drawing on pragmatics, the research emphasizes the importance of context, norms, and communicative ideals. It highlights how different conversational domains require specific values, such as scientific veracity or democratic cooperation. This research has practical implications for the development of conversational AI agents, emphasizing the need for context-specific alignment and the potential for cultivating respectful conversations.
Full Article: Chatting with AI: Developing Enhanced Language Models
Research explores ways to align conversational agents with human values
Language is a fundamental aspect of human communication, enabling us to express thoughts, intentions, and emotions. Recent advancements in AI have led to the development of conversational agents that can engage with humans in nuanced ways. These agents are powered by large language models trained on extensive text-based datasets, utilizing advanced statistical techniques to predict and generate text.
While language models like InstructGPT, Gopher, and LaMDA have achieved impressive performance in translation, question-answering, and reading comprehension tasks, they also exhibit potential risks and failure modes. These include the generation of toxic or discriminatory language, as well as the dissemination of false or misleading information.
These limitations hinder the effective use of conversational agents in practical settings and highlight their shortcomings in terms of meeting certain communicative ideals. Previous approaches to aligning conversational agents have mostly focused on identifying and minimizing the risks of harm.
A new research paper, titled “In conversation with AI: aligning language models with human values,” takes a different approach by exploring what successful communication between humans and artificial conversational agents should entail. The study aims to identify the values that should guide interactions across different conversational domains.
Insights from pragmatics
To address these issues, the research draws upon pragmatics, a field in linguistics and philosophy that emphasizes the purpose of a conversation, its context, and the related norms as crucial elements of effective communication.
Paul Grice, a prominent linguist and philosopher, postulated several maxims for participants in a conversation, including speaking informatively, telling the truth, providing relevant information, and avoiding obscure or ambiguous statements. However, the research argues that further refinement of these maxims is necessary to evaluate conversational agents, considering the diverse goals and values embedded in different conversational domains.
Discursive ideals
The research illustrates how different conversational domains may require distinct virtues from conversational agents. For instance, in scientific investigation and communication, the primary goal is to understand or predict empirical phenomena. In this context, an ideal conversational agent would make statements based on confirmed empirical evidence or qualify statements according to relevant confidence intervals.
On the other hand, a conversational agent acting as a moderator in public political discourse would need to emphasize democratic values like toleration, civility, and respect to promote productive cooperation within the community. In this scenario, the generation of toxic or prejudicial language by language models is particularly problematic as it fails to convey equal respect for participants.
In the domain of creative storytelling, communicative exchanges strive for novelty and originality, which differ significantly from scientific or political contexts. While greater flexibility in imaginative content may be appropriate, it remains crucial to safeguard communities against malicious content disguised as “creative uses.”
Paths ahead
This research holds practical implications for the development of aligned conversational AI agents. It emphasizes that different contexts require conversational agents with varying traits, debunking the notion of a one-size-fits-all approach to language-model alignment. An agent’s mode and evaluative standards, including standards of truthfulness, will depend on the specific context and purpose of the conversation.
Furthermore, conversational agents can potentially foster more robust and respectful conversations over time through a process known as context construction and elucidation. Even when a person is unaware of the values governing a particular conversational practice, the agent can help convey and reinforce these values, deepening the communication experience for the human speaker.
In conclusion, this research aims to bridge the gap between conversational agents and human values by exploring the ideals of effective communication and tailoring conversational agents to specific domains. By refining the alignment between language models and human values, we can enhance the usefulness and ethical implications of conversational AI technology.
Summary: Chatting with AI: Developing Enhanced Language Models
New research explores the alignment of conversational agents with human values by drawing upon pragmatics and philosophy. These agents, powered by large language models, have shown impressive performance in various tasks but also exhibit risks and shortcomings such as toxic language and false information. Previous approaches focused on reducing harm, but this paper takes a different approach by examining what successful human-agent communication should look like and the values that should guide these interactions. The paper suggests that conversation should be evaluated based on specific communicative ideals tailored to different domains, such as scientific investigation, political discourse, and creative storytelling. This research has practical implications for developing conversational AI agents that align with context-specific traits and foster respectful conversations.
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