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🎯 How to with AI agents | Deep dive: can agentic RAG be used to address complex ethical dilemmas
How to build with AI

🎯 How to with AI agents | Deep dive: can agentic RAG be used to address complex ethical dilemmas

Agentic RAG can be a moral compass, or a dangerous tool of manipulation, depending on who wields it | Get started with AI | How-to guides and features

Aug 14, 2024
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🎯 How to with AI agents | Deep dive: can agentic RAG be used to address complex ethical dilemmas
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Video by Google DeepMind

Can agentic RAG be used to address complex ethical dilemmas?

Agentic RAG represents a sophisticated paradigm shift in question-answering. It employs an agent-based framework to orchestrate the complex interplay of information retrieval and reasoning across multiple documents.

By instantiating autonomous agents, this methodology enables dynamic, adaptive, and context-aware exploration of diverse textual corpora.

Core functionalities encompass comprehensive document comparison, nuanced summarization, and cross-referential analysis, culminating in a holistic understanding of the underlying information space.

Knowing that agentic RAG can be a potent tool for navigating complex ethical dilemmas by providing a structured approach to weighing conflicting values and potential outcomes.

RAG can illuminate potential consequences and trade-offs by accessing and processing vast information, including legal, ethical, and societal norms.

However, its effectiveness hinges on the quality and diversity of the data it is trained on and the ethical frameworks implemented in its development.

While RAG can offer valuable insights, it is essential to recognize that it is a tool, not a moral arbiter.

Ultimately, human judgment and responsibility remain paramount in making ethical decisions.


“How to with AI agents” is a five-part weekly series exploring AI agents’ capacity to revolutionize how we work, live, and interact with technology.

Part 1: AI agents, how to perform?

We need to understand the direction of AI agents’ improvement over time and acknowledge the importance of a combination of workflow systems, human expertise, and AI for well-balanced, ethical, and responsible distribution.

Part 2: Targeting the underserved

We'll likely see AI Agent solutions initially addressing niche markets or tasks currently considered too simple or mundane for humans. Imagine AI chatbots handling basic customer service inquiries or virtual assistants managing simple logistics tasks.

Part 3: Gradual market expansion

As AI Agent capabilities mature, they'll start encroaching on more complex tasks, gradually taking over mainstream functions currently performed by humans. Think of AI-powered financial advisors or intelligent document review tools.

Part 4: Strategy as the key driver

This market expansion hinges on continuous improvement in AI Agent performance. Advancements in areas like natural language processing, decision-making algorithms, and user interaction will be crucial.

Part 5: The democratization of AI

Disruptive innovation often leads to more accessible and affordable technologies. We might see AI Agents becoming readily available for small businesses and individuals, not just large corporations.

Deep dive: Deep dive: does a higher level of automation in AI mean less human control?

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