Human-Integrated Automation Intelligence (HiAi) is a meta-framework for designing, managing, and scaling systems where humans, agents, and avatars operate together in a continuous, adaptive ecosystem.
At the core of HiAi are the RELIC principles. These principles provide a structured, foundational approach to building and governing complex systems, ensuring that technology amplifies human capabilities rather than replacing or constraining them. Although often presented as modern innovations, the principles behind automation have roots stretching back thousands of years.
[R] Reliable Modular Design
Build systems, agents, and avatars that consistently perform as intended. Ensure predictability, maintainability, and independent scalability, with safeguards against errors and unexpected behaviors. Agents are semi-autonomous systems that execute tasks, often starting as proto-automation needing human guidance. Avatars are human-facing representations of agents that communicate, guide, or interact with humans, and can serve as incentives or visual cues. For example, an agent may autonomously assign employee shifts, while its avatar communicates the schedule, answers questions, and provides alerts. The agent performs the work; the avatar makes it actionable and visible to humans.
[E] Reengineer Environments and Tasks
Restructure workflows, environments, and avatars to optimize efficiency for humans and agents navigating them. Consider timing, sequencing, and task dependencies to maximize performance and reduce complexity.
[L] Feedback Loops
Establish continuous, process-centric cycles of observation, adjustment, and refinement among humans, agents, and avatars. Monitor performance, detect risks, adjust processes, and iteratively refine behavior to sustain operational excellence. Feedback loops ensure the system adapts to changing conditions in real time.
[I] Incentives to Amplify Human Capacity
Design initiatives and incentive structures that enhance human performance while leveraging agents and avatars. Include safeguards to prevent gamification or system gaming that could undermine outcomes. Avatars can serve as visual feedback, recognition, or engagement tools. Initiatives should promote engagement, accountability, and motivation while ensuring alignment with ethical standards and human-centered principles.
[C] Continuous Learning with Context
Enable ongoing, evolution-centric learning for humans, agents, and avatars. Utilize feedback and experiential data to improve performance, advance agents from proto-automation to full automation, and drive meaningful development in human skills, decision-making, and behaviors, while scaling safely across the system. Continuous learning focuses on long-term adaptation and improvement beyond immediate process adjustments.
