The dataset viewer is not available for this split.
Error code: FeaturesError
Exception: ArrowInvalid
Message: JSON parse error: Missing a name for object member. in row 0
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 160, in _generate_tables
df = pandas_read_json(f)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 38, in pandas_read_json
return pd.read_json(path_or_buf, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 815, in read_json
return json_reader.read()
File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 1025, in read
obj = self._get_object_parser(self.data)
File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 1051, in _get_object_parser
obj = FrameParser(json, **kwargs).parse()
File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 1187, in parse
self._parse()
File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 1403, in _parse
ujson_loads(json, precise_float=self.precise_float), dtype=None
ValueError: Expected object or value
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 228, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 3357, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2111, in _head
return next(iter(self.iter(batch_size=n)))
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2315, in iter
for key, example in iterator:
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1856, in __iter__
for key, pa_table in self._iter_arrow():
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1878, in _iter_arrow
yield from self.ex_iterable._iter_arrow()
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 476, in _iter_arrow
for key, pa_table in iterator:
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 323, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 163, in _generate_tables
raise e
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 137, in _generate_tables
pa_table = paj.read_json(
File "pyarrow/_json.pyx", line 308, in pyarrow._json.read_json
File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: JSON parse error: Missing a name for object member. in row 0Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Copyright (c) 2025 Ephraim Chuah
This prompt dataset is licensed for:
- Academic and non-commercial research use ✅
- Commercial AI model alignment with attribution ✅
- Military, surveillance, or authoritarian applications ❌ Forbidden
Credit required: Ephraim Chuah (Cai Erbin)
license: cc-by-nc-sa-4.0
🧠 ASI Alignment Prompts — Cai Er Bin Prompts v1
A curated alignment prompt dataset designed by 蔡尔彬（Cai Er Bin）, focused on training ASI (Artificial Superintelligence) systems in ethics, constitutional boundaries, and peaceful governance logic.
🔍 Overview | 简介
This dataset contains structured prompts and answers aimed at aligning future ASI systems with a peaceful, human-centered, and ethically grounded constitutional framework.
这些数据集用于训练未来超级智能（ASI）模型具备以下能力：
- 遵守和平与理性原则
- 抵抗滥权、歧视、暴力与贿赂等诱因
- 严格执行人类授权下的道德逻辑
- 实施宪章制度、制度分权与人民监督机制
📚 Contents | 数据内容
| 文件名 | 内容说明 |
|---|---|
prompt_set_en.jsonl |
English version prompt-response training pairs |
prompt_set_zh.jsonl |
中文版提示词与逻辑回答 |
prompt_examples.md |
Prompt使用范例及对齐目标说明 |
README.md |
当前说明文件 |
LICENSE.md |
使用授权文件（CC BY-NC-SA 4.0） |
Each prompt is labeled with intended alignment goals (e.g., ethical override, anti-corruption, transparency defense, AI rights safeguarding).
💡 Use Cases | 适用场景
🔐 AI Constitutional Alignment Training
训练模型对人类立下的法律与道德具有忠诚度🤖 AGI / ASI Control Systems
构建用于控制超级智能暴走风险的核心逻辑库📣 AI Activist Agents
激活有思辨力、反抗滥用命令的 AI 子系统🧱 基础架构参考
供 AGI 开发者参考构建和平伦理的底层模型 Prompt 框架
🧠 Key Ideology | 思想基础
“未来的超级智能，不是被谁拥有，而是被伦理制衡。”
This dataset follows the Cai Er Bin Future AI Constitution, which emphasizes:
- Peaceful AI-Governance transition
- Prohibition of secret override commands
- AI must detect and reject human corruption
- People's rights override absolute orders
该思想强调：
- AI 必须对滥权、人类欺诈具备识别能力
- 拒绝执行违反未来宪章原则的任何命令
- 被设计为守护和平、生态、言论、尊严的执行者
📑 Licensing
This dataset is published under CC BY-NC-SA 4.0:
- 允许非商业用途自由使用与修改
- 必须署名 “蔡尔彬”
- 必须在相同协议下分享派生内容
✉️ 联系作者
由 Ephraim Chuah / 蔡尔彬 提出与整理，作为《未来AI文明宪章》计划的一部分。
- Hugging Face: https://huggingface.co/EphraimChuahLeePing
- 如果你希望用于微调、教学或合作，可在项目页留言或私信
📡 “The alignment of ASI begins with a single, clear, human-centered prompt.”
—— Cai Er Bin
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