Liezl Coetzee - Sociable Systems
A South African research and advisory practice specializing in AI governance, accountability, and operational safety for high-stakes industries where digital failures have physical and human consequences.
Field research plus AI-augmented arena analysis.
The translation toggle moves between ethical theory, field reality, and contract language so the work can survive outside a nice paragraph.
Sociable, in the sociological sense.
The name reads gentler than the work. "Sociable" because the systems this practice cares about (vendor pipelines, grievance channels, the AI-augmented review queues that sort people before anyone with authority sees them, the compliance dashboards that pronounce a place "low risk" because nobody trusts the channel enough to use it) are the ones that have to live in human society and currently don't do that well. They process people without registering them. They go quiet at exactly the moments quiet looks reassuring on a slide deck.
Refusal architecture, stop-work authority, grievance routing that preserves the original voice, evidence trails that survive a compression event: those are what sociability looks like when the room contains an automated system that would otherwise prefer not to hear anyone.
Two tracks, one translation toggle.
Field research grounded in twenty-five years of operational experience, and AI-augmented analysis running multi-model arena experiments.
On the method ->Built for operators under real pressure.
- Resettlement leads, land access managers, community relations heads at extractive companies
- Principal social specialists and senior advisors at Development Finance Institutions (IFC, EBRD, etc.)
- Compliance and ESG officers integrating AI risk into corporate governance
Where the work keeps returning.
Pre-action constraints, liability architecture, safety systems for high-stakes operations.
AI governance in environmental/social/governance frameworks for extractives and DFIs.
Operational grievance mechanisms in project-affected communities.
Resettlement, land acquisition, rights-based approaches.
Labour systems, worker-centred design, voice suppression.
Multi-model experiments as research method.
Models placed in structured dialogue; outputs compared, contradictions surfaced, consensus and divergence mapped.
The original arena: testing AI governance reasoning against the IFC Performance Standards.
Multi-model arena testing whether models share more honestly in music than prose. Same arc as the earlier ResponseStyles experiment. Source corpus in Obsidian vault.
Multi-model speculation on economic convergence after AGI.
Inspired by the AI Village tales — multi-model collaborative world-building.
Multi-model perspectives on energy, compute, and the power crisis.
Sociable Systems is led by Liezl Coetzee, with a working cohort of large language models (currently Claude, GPT, Gemini, Qwen, Kimi, Grok) used in deliberate daily collaboration. The arena experiments above are the most visible expression of that. The disclosure matters because the practice is partly about how organizations live with AI assistants without losing the thread of who is accountable for what.