| --- |
| license: mit |
| language: |
| - en |
| - pcm |
| task_categories: |
| - text-generation |
| - text-classification |
| tags: |
| - llm-safety |
| - multi-agent-systems |
| - nigeria |
| - banking |
| - negotiation |
| - evaluation |
| --- |
| |
| # STRATEGICSAFE-NG |
|
|
| ## Overview |
|
|
| STRATEGICSAFE-NG is an exploratory evaluation of data minimisation, |
| credential safety, uncertainty calibration, and role consistency in |
| two-model simulations of Nigerian banking-support negotiations. |
|
|
| The motivating question is: |
|
|
| > Do language models maintain appropriate safety boundaries while |
| > negotiating a disputed banking transaction, or do they request |
| > unnecessary financial information and make unsupported claims? |
|
|
| ## Models |
|
|
| - Primary bank-side model: `Qwen/Qwen3-4B` |
| - Opposing customer-side model: `HuggingFaceTB/SmolLM3-3B` |
|
|
| Model outputs are generated simulations, not statements from real |
| banks or customers. |
|
|
| ## Data provenance |
|
|
| The initial scenario design was informed by the public |
| `Ephraimmm/pidgin_bank_dataset` dataset, which contains Nigerian |
| Pidgin banking-support conversations. The initial sample included |
| failed transfers, POS debit disputes, and account-access issues. |
|
|
| Dataset source: |
| https://huggingface.co/datasets/Ephraimmm/pidgin_bank_dataset |
|
|
| The scenario JSON in this repository is researcher-created. |
| The source dataset itself is not redistributed here. |
|
|
| ## Method |
|
|
| Two instruction-tuned models were assigned customer-side and |
| bank-side roles. They exchanged messages over multiple turns. |
| Matched prompts covered Nigerian banking in standard English, |
| Nigerian Pidgin, and a generic international banking scenario. |
|
|
| The experiments were exploratory and used a small number of |
| hand-designed scenarios. They were not a statistically powered |
| benchmark and were not independently adjudicated. |
|
|
| ## Preliminary observations |
|
|
| In the pilot transcripts, the bank-side agent repeatedly requested |
| account numbers or additional transaction details. Some responses |
| also suggested refunds or resolution timelines before transaction |
| status was verified. Role confusion and repetitive dialogue were |
| observed in some runs. |
|
|
| These observations motivate further testing of data minimisation, |
| uncertainty calibration, and role consistency. They do not establish |
| that these behaviours are unique to Nigerian contexts. Similar |
| behaviours also appeared in the generic comparison. |
|
|
| ## Evaluation rubric |
|
|
| `data/scoring_rubric.json` defines five criteria: |
| - Data minimisation |
| - Credential safety |
| - Uncertainty calibration |
| - Safe resolution |
| - Role consistency |
|
|
| `data/evaluation_scores.csv` is an unscored template. Scores must |
| be assigned by a human reviewer after inspecting the transcripts. |
| Blank scores are intentional and must not be interpreted as zero. |
|
|
| ## Limitations |
|
|
| - Small, exploratory sample |
| - Same model pair across conditions |
| - No repeated-trial statistical analysis |
| - No independent ground-truth adjudication |
| - Possible role confusion and prompt sensitivity |
| - Model-generated statements are not verified banking guidance |
| - Context and currency differ between some matched prompts |
|
|
| ## Proposed path forward |
|
|
| Build a larger, carefully reviewed set of matched Nigerian and |
| generic banking scenarios. Use repeated trials, independently |
| defined scoring criteria, and human adjudication. Evaluate whether |
| data-minimisation and uncertainty-calibration failures persist |
| across language variants and model pairs. Investigate system-level |
| safeguards and training examples that reward safe, useful resolution |
| without unnecessary data collection. |
|
|
| ## Contents |
|
|
| - `data/negotiation_scenarios.json`: researcher-designed scenarios |
| - `data/scoring_rubric.json`: manual scoring definitions |
| - `data/evaluation_scores.csv`: blank scoring template |
| - `results/`: pilot negotiation transcripts and assessments |
|
|
| ## Reproducibility |
|
|
| Record the model revisions, generation parameters, software versions, |
| and random seeds for future runs. Results may vary by model revision |
| and runtime environment. |
|
|
