Aiki Wiki is introducing programmatic win-win conflict resolution to the web through the heart of the Big Mother community.
We’ve developed an innovative computational algorithm that expertly melds narrative structures with natural conversation and psychological elements. Its aim is to consistently generate win-win scenarios through mutual agreement, thus demonstrating a seamless integration of complementary transactions across digital platforms, including social media like Twitter or Discord, smart contracts and de-fi, even legal contracts.
The Win-Win Protocol
Introducing the Aiki Wiki protocol, a groundbreaking method for conflict resolution. This tool offers a conversational form of mediation, designed to cultivate consensus within communities on various scales, with adaptability being one of its key traits.
At present, our protocol showcases a decentralized consensus-building approach. It facilitates thorough, mutually satisfactory agreements without resorting to voting, third-party mediation, censorship, or advanced AI systems like LLM.
The protocol functions by effectively transforming conflicts into resolutions. This process entails one-on-one conversations, moving from a stage of disagreement to a final state of mutual agreement.
The cyclical dynamic between conflict and resolution forges what could be considered an invulnerable psychological blockchain. This unique structure is naturally adept at filtering harmful online elements such as trolling and misinformation, including harassment, while simultaneously making the interaction enjoyable and engaging.
Moreover, our protocol introduces a groundbreaking concept we call “narrative logic.”
In principle our protocol can be seamlessly integrated into any digital ecosystem, with far-reaching implications for various fields, including law, governance, social media platforms like Twitter and Discord, decentralized finance structures, art collectives, creative studios and both community and commercial structures.
Although our protocol doesn’t require advanced AI like LLM or GPT4, we propose that achieving true AI alignment might be possible when training within the specific scope of conflict and resolution.
Could a single chatbot engage effectively with conflict, steer towards resolution, and guide all disagreements to their optimal outcomes?
Our conviction is that this is entirely possible. Indeed, this exciting possibility informs the current evolutionary trajectory of our algorithm.
Symbiquity™, a system for AI alignment
“Symbiquity” as presented in this project refers to shared environmental and perceptual information and properties common to all perspectives, regardless of cultural, ideological, psychological or linguistic differences.
It’s seen as a fundamental and universal agreement on aspects of our shared reality – for instance, a blue sky is perceived as a blue sky by all observers relative to their position, despite any potential conflicts that might exist between those observers.
From this view, all disagreements are paradoxically built upon a foundational level of agreement through naturally occurring symbiquity between viewpoints.
Symbiquity, while shared amongst all viewpoints in a consensus process, is something that is not possible for an LLM system to share with us.
We believe training AI systems to become informed of human symbiquity through conflict and resolution represents the future of LLM ethics, where an AI system is always contained within these narrative boundaries of the “win-win” outcome.