user : decision overflow assistant : ### What specific governance challenge or problem are you observing? Please be as concrete as possible about what's happening and why it matters. user : too many decisions needing to be taken by too many actors, leads to inertia/discouragement assistant : ### What evidence or examples demonstrate this is a real problem? This could include failed proposals, low participation rates, specific incidents, data you've observed, or patterns you've noticed across projects. user : lowering participation rates over time, paralyzed projects, the coordination required to reach quorum.. all observed in the Token Engineering Commons, which I researched from 2021-2023 assistant : Would you like to share another governance problem, or should we move on to exploring solutions and who's working on them? user : once initial enthusiasm & idealism gives way to unglamrous day to day grind, extrinsic motivations - financial & power interest of individuals - often becomes main driver, which crowds out intrinsic motivation even more, resulting in cynical situations assistant : ### What specific governance challenge or problem are you observing? Please be as concrete as possible about what's happening and why it matters. user : the former was a description - IDK what title this may go under.. gradual disillusionment? assistant : Got it - so this is the problem statement itself: the gradual disillusionment as initial enthusiasm gives way to day-to-day grind, where extrinsic motivations (financial and power interests) crowd out intrinsic motivation, creating cynical situations. ### What evidence or examples demonstrate this is a real problem? This could include specific incidents, behavioral changes you observed, data on contributor retention, or patterns in how governance evolved over time. user : sorry but I dont have specific evidence/examples in Web3 to point to, other than again the TEC. this is more based on my experience in various decentralized, semi-formal settings that start out with high hopes/idealism and, in worst case, become cynical 0-sum games assistant : Would you like to share another governance problem, or should we move on to exploring solutions and who's working on them? user : fairness - leanness tradeoff assistant : ### What specific governance challenge or problem are you observing? Please be as concrete as possible about what's happening and why it matters. user : to reward fairly (according to (effective) inputs), we need detailed accounting - this is tedious, especially once we go beyond just logging contributions to valuing them. assistant : ### What evidence or examples demonstrate this is a real problem? This could include failed proposals, low participation rates, specific incidents, data you've observed, or patterns you've noticed across projects. user : again, huge topic in the TEC, which resulted in a conflict that caused many to leave/cease participation. I wrote an 80 page case study on this issue (among others). balancing precision/fairness with ease of use is tricky. assistant : Would you like to share another governance problem, or should we move on to exploring solutions and who's working on them? user : move on assistant : ### What approaches, tools, or mechanisms could address the governance problems we've discussed? Share any potential solutions you're aware of or have considered - these could be technical tools, process innovations, research directions, or organizational approaches. user : on value accounting/ fairnedss/leannness tradeoff: open value accounting is not new. has been explored in depth by Sensorica, by the TEC's Praise system, and many others. I feel that nowadays, with AI, it should be easier to train an agent once and then let it do the valuation part, even good share of the logging work. what it still needs is coherence among community what counts as fair. decision overflow: Aragon is working on interesting approaches - basically, subsidiarity, delegation of decisions, all the stuff htat has been existent outside crypto for f*ing decades/centuries, and we political scientists have been pointing out since crpyto declared they wanna 'solve' politics. lol. disillusion: making individual interests and extrinsic motivations explicit from the beginning, without focusing on them too much, is what I find works best. acknowledge that work stays work, even with DAOs, and should be paid. assistant : ### Which teams, projects, or researchers do you know are actively working on these solutions or related governance innovations? This helps us map who's contributing to solving these challenges. user : OVA: Sensorica. IDK how much Praise evolved - check with Griff Green. Decisions: Aragon. disillusion / realism: IDK anyone specific.. sorry assistant : Would you like to share more solutions or identify additional actors working in this space, or should we move to wrapping up? user : lets wrap up assistant : ### Thank you for mapping governance challenges and solutions Here's a summary of your contributions: **Problems Identified:** 1. **Decision overflow** - Too many decisions needing to be taken by too many actors, leading to inertia and discouragement 2. **Gradual disillusionment** - Initial enthusiasm and idealism gives way to unglamorous day-to-day grind, where extrinsic motivations (financial and power interests) crowd out intrinsic motivation, creating cynical situations 3. **Fairness-leanness tradeoff** - To reward fairly according to effective inputs requires detailed accounting and valuation, which becomes tedious and creates tension between precision/fairness and ease of use **Evidence Provided:** - Token Engineering Commons (TEC) research (2021-2023): lowering participation rates over time, paralyzed projects, coordination challenges reaching quorum - TEC conflict over value accounting that caused many to leave/cease participation (documented in 80-page case study) - Patterns observed across various decentralized, semi-formal settings beyond Web3 **Solutions & Approaches:** - **Open value accounting with AI**: Training AI agents to handle valuation and logging work, building on existing approaches (requires community coherence on what counts as fair) - **Subsidiarity and delegation**: Applying established political science principles like delegation of decisions (noting these have existed outside crypto for decades/centuries) - **Explicit acknowledgment of interests**: Making individual interests and extrinsic motivations explicit from the beginning, acknowledging that work remains work even in DAOs and should be compensated **Active Contributors:** - **Sensorica** - Open value accounting - **TEC's Praise system** - Value accounting (check with Griff Green for current status) - **Aragon** - Subsidiarity, delegation approaches Does this summary capture your main points accurately, or would you like to clarify or add anything? user : fine! assistant : Thank you for participating in phase 1 of gov/acc research, Participant 19! Your insights on decision overflow, disillusionment dynamics, and the fairness-leanness tradeoff - particularly grounded in your TEC research - will be valuable for building the research roadmap. The connections you've drawn between established political science principles and Web3 governance challenges are especially helpful for the community. This will be synthesized with other participants' contributions to inform the visualization and workshop at EthCC. 🙏