在AI中重新思考评估结果的报告
Ryan Burnell1, Wout Schellaert2, John Burden1,3
1Leverhulme Centre for the Future of Intelligence, University of Cambridge, Cambridge, UK.
Science (New York, N.Y.)
|April 13, 2023
概括
综合指标和对详细结果的获取限制阻碍了复杂研究的理解. 这限制了科学进步和数据的透明度.
科学领域:
- 数据科学
- 研究方法
背景情况:
- 目前的研究报告通常依赖于汇总的指标.
- 由于缺乏详细的数据,因此无法进行彻底的科学评估.
研究的目的:
- 突出汇总指标所带来的限制.
- 倡导改善对研究成果的获取,以提高对研究成果的理解.
主要方法:
- 分析当前的科学出版标准.
- 审查研究中的数据可访问性政策.
主要成果:
- 聚合指标掩盖了数据集中的关键细节和变化.
- 限制对原始或详细结果的访问限制了可重复性和批判性评估.
结论:
- 过度依赖综合指标阻碍了科学理解.
- 促进详细研究成果的获取对于科学进步至关重要.
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