From Bleeding Edge to Leading Edge: GAI and Reciprocal Intelligence in eDiscovery

[EDRM Editor’s Note: This article was first published August 20, 2023 and EDRM is grateful to Rob Robinson and ComplexDiscovery for permission to republish. The opinions and positions are those of ComplexDiscovery.] 

ComplexDiscovery Editor’s Note: In an era where technology continually pushes the boundaries of what’s possible, the integration of Generative Artificial Intelligence (GAI) and Reciprocal Intelligence within the legal field presents a transformative opportunity. This article delves into the nuanced relationship between human experts and AI, focusing on the concept of Reciprocal Intelligence—a balanced partnership where AI is not merely a tool but a creative partner. By exploring the application of GAI and Reciprocal Intelligence in eDiscovery, the article highlights how this dynamic collaboration could redefine the entire Electronic Discovery Reference Model (EDRM).

Industry Backgrounder

From Bleeding Edge to Leading Edge: GAI and Reciprocal Intelligence in eDiscovery

ComplexDiscovery Staff

Reciprocal Intelligence: Bridging Human Expertise and AI in eDiscovery

The legal technology field is on the brink of a transformation that could redefine the practice of eDiscovery. At the heart of this change lies the potential of Artificial Intelligence (AI), a technology that mimics* human intelligence, including learning, reasoning, and problem-solving. Within AI, a specialized branch known as Generative Artificial Intelligence (GAI) emerges, capable of generating new data instances and offering innovative solutions.

The application of AI and GAI in various fields, including legal technology, is often approached through two distinct paradigms: Collaborative Intelligence and Reciprocal Intelligence. 

Collaborative Intelligence represents a synergistic relationship between humans and AI. It focuses on teamwork, where AI assists human efforts, but it may lead to a dominant-subordinate dynamic where one party’s insights overshadow the other’s contributions.

Reciprocal Intelligence, on the other hand, takes the concept of collaboration to a new level. It represents a balanced partnership where humans and AI learn from and grow with each other, emphasizing equality and mutual growth. Unlike Collaborative Intelligence, where the relationship may be one-sided, Reciprocal Intelligence ensures a balanced interaction, fostering a more harmonious relationship.

The distinction between Collaborative and Reciprocal Intelligence is not merely theoretical; it has practical implications in various domains, including financial, legal, operational, and ethical considerations of AI and GAI. Understanding and applying Reciprocal Intelligence in these areas may help ensure the leading-edge benefits of AI/GAI use without the bleeding-edge risks.

More Than Just Task Completion

Integrating AI and Generative Artificial Intelligence (GAI) with Collaborative and Reciprocal Intelligence requires a comprehensive perspective considering broader financial, legal, operational, and ethical implications. Financially, Reciprocal Intelligence may guide responsible investment in AI, balancing innovation with risk management. Legally, it can foster compliance, ensuring that AI operates within the law’s boundaries. Operationally, Reciprocal Intelligence may enhance efficiency, focusing on effective task completion without compromising human values. Ethically, it can guide the development of AI in a manner that respects human dignity, societal norms, and compliance with industry and professional ethical requirements. This holistic approach ensures that the deployment of AI aligns with overarching societal values, transcending task-oriented goals and reflecting a balanced and responsible alignment with the complex needs of individuals, organizations, and professions

eDiscovery, GAI, and Reciprocal Intelligence

In the specific context of eDiscovery, the integration of GAI and Reciprocal Intelligence could transform the entire Electronic Discovery Reference Model (EDRM), enhancing efficiency and effectiveness across all stages:

• Identification: Collaborative Intelligence might assist in locating potential sources of relevant information through predefined algorithms, while Reciprocal Intelligence could enable GAI to learn from human insights, adapting and refining search parameters for more precise identification.
• Preservation: In Collaborative Intelligence, GAI might follow human-directed protocols to protect data against alteration or destruction. In contrast, Reciprocal Intelligence could allow GAI to suggest and implement innovative preservation strategies based on continuous learning from human feedback.
• Collection: Collaborative Intelligence may involve GAI in gathering information based on set guidelines, while Reciprocal Intelligence could foster a dynamic interaction where GAI and human experts jointly determine the most efficient collection methods.
• Processing: While Collaborative Intelligence might use GAI to reduce the volume of data and convert it into usable formats based on existing rules, Reciprocal Intelligence could enable GAI to develop new processing techniques by learning from human expertise.
• Review: Collaborative Intelligence may employ GAI to evaluate data for relevance and privilege using predefined criteria. Reciprocal Intelligence, however, could allow GAI to evolve its review strategies by understanding and adapting to human judgment and contextual nuances.
• Analysis: In Collaborative Intelligence, GAI might analyze data for content and context following human-established patterns. Reciprocal Intelligence could enable a more nuanced analysis, where GAI learns from human insights to uncover hidden patterns and relationships.
• Production: Collaborative Intelligence may utilize GAI to deliver data in predetermined formats, while Reciprocal Intelligence could enable GAI to customize data delivery based on ongoing collaboration and understanding of human needs.
• Presentation: While Collaborative Intelligence might involve GAI in displaying data findings in standard ways, Reciprocal Intelligence could lead to more interactive and tailored presentations, where GAI learns from human preferences and feedback to enhance the clarity and impact of data visualization.

From identification to presentation, the collaboration between human experts and GAI evolves from mere assistance to a dynamic partnership, where Reciprocal Intelligence not only allows for continuous learning and adaptation but also fosters a balanced interaction between human insights and AI capabilities.

From Bleeding Edge to Leading Edge

The future of GAI and Reciprocal Intelligence in eDiscovery is one of promise and potential, painting a vivid picture of a world where legal professionals and AI are not just collaborators but true partners. It’s a narrative that speaks to what might be possible in legal technology, where human creativity meets AI’s computational prowess and where technology enhances human capabilities. The journey is just beginning, but the path is clear: a new era where legal professionals and AI could become true partners, standing on the brink of a transformation that could redefine the very essence of eDiscovery.

By understanding and applying the principles of Reciprocal Intelligence, we may unlock the leading-edge benefits of AI and GAI without succumbing to the bleeding-edge risks.

*AI systems are designed to mimic human intelligence by learning from data, recognizing patterns, making decisions, and even adapting to new information or stimuli. While AI can replicate certain aspects of human intelligence, it’s essential to note that AI does not possess consciousness or emotions, and its understanding and reasoning are based on algorithms and data rather than human-like cognition.

Assisted by GAI and LLM Technologies

Additional Reading

• Even FLOE? A Strategic Framework for Considering AI in eDiscovery
• The Shot Heard ‘Round the Legal World: AI’s Role and the Judicial Reaction

Source: ComplexDiscovery