Generative Games & Governance Exchange

That isn't covered in the materials I've been given, so I can't answer it. The parts I couldn't find are listed below.

My materials outline how to compare local AI generation against any alternative by weighing per-attempt marginal cost, iteration speed, quality ceiling, engineering overhead, provenance and reproducibility rather than presenting a vendor-price table [1][2][3][4][5]. They state that at library scale the marginal cost of an extra generation attempt approaches electricity alone on a single laptop-class GPU (8 GB) and that many attempts are typical in practice [1][2]. They also state the engineering burden of running locally is substantial and permanent — tooling for memory management, retries, quality gates and scheduling is required [3]. The materials warn that small‑memory local models have a quality ceiling (hands, faces, text) and hosted services or illustrators are better for a few hero assets [4][6]. Throughput and wall‑clock timings on the referenced 8 GB machine (measured September 2026) give concrete pacing: stills in seconds, animations in minutes, and a library maintenance pass taking a working day [7][4]. Supplier risk and control are documented: running locally makes upgrades a deliberate internal decision and preserves asset provenance and reproducibility because models and inputs are stored as files we keep [8][5].

The pipeline verifies internal consistency and measured behavior: every number a build reports is recomputed from the finished ticket pool (deck size, payback, hit rate, volatility and related statistics) and slot reels are simulated to confirm returns and hit frequencies, so the system can tell you whether the math in the package matches its spec and lives inside the pipeline’s bands [1][2]. A passed verification therefore guarantees those measured properties and that the build can produce exportable math evidence (PAR sheet, retained inputs) for external review [3][4]. What it does not do is judge whether those verified numbers make for good player experience or are commercially sensible for a market or room — the materials say human judgment and human review catch those matters and that verification does not establish commercial sensibility or legal clearance of names/themes [5]. Human editors can adjust pools and rebalance numbers, but any edit forces full recomputation and re‑verification rather than a partial pass [6][2]. My materials don’t cover how to translate verified math into effective player experience, nor how to map permitted math or required disclosures to specific jurisdictions; those are outside the pipeline and require market research, human judgement and jurisdiction‑specific compliance review [5][4].

The session materials say any edit to a verified build forces a full re‑verification: an edited game “is not a verified game until it has been through the checks again” [1] and prize or pool edits trigger full recomputation of all reported statistics [2]. Regenerated visual assets and asset integrity issues are explicit rejections unless regenerated and rechecked: every named symbol must have its artwork present and valid, corrupt or missing image files are discarded and regenerated, and a build missing one file does not ship [3][4]. Game‑mathematics changes require recomputation of deck size, payback, hit rate, prize floor and payout integrity before release [5][2]. Changing shipped bytes directly is also outside the pipeline until the package is re‑verified [1]. The materials do not state whether model/version changes or prompt edits (which may alter generated assets) are treated automatically as edits that require re‑verification, so that point is unknown from these materials [6].