Publicly available datasets are one of the key drivers for commercial AI software. The use of publicly available datasets (particularly for commercial purposes) is governed by dataset licenses. These dataset licenses outline the rights one is entitled to on a given dataset and the obligations that one must fulfil to enjoy such rights without any license compliance violations. However, unlike standardized Open Source Software (OSS) licenses, existing dataset licenses are defined in an ad-hoc manner and do not clearly outline the rights and obligations associated with their usage. This makes checking for potential license compliance violations difficult. Further, a public dataset may be hosted in multiple locations and created from multiple data sources each of which may have different licenses. Hence, existing approaches on checking OSS license compliance cannot be used. In this paper, we propose a new approach to assess the potential license compliance violations if a given publicly available dataset were to be used for building commercial AI software. We conduct trials of our approach on two product groups within Huawei on 6 commonly used publicly available datasets. Our results show that there are risks of license violations on 5 of these 6 studied datasets if they were used for commercial purposes. Consequently, we provide recommendations for AI engineers on how to better assess publicly available datasets for license compliance violations.
翻译:公开可得的数据集是商业AI软件的关键驱动因素之一。使用公开可得的数据集(特别是用于商业目的的数据集)受数据集许可证管制。这些数据集许可证概述了某人在特定数据集上享有的权利和在不违反许可证合规的情况下必须履行的义务;然而,与标准化的开放源码软件许可证不同,现有数据集许可证是以临时方式界定的,没有明确说明与其使用有关的权利和义务。这使得检查可能的违反许可证遵守情况很困难。此外,公共数据集可能存放在多个地点,由多个数据来源创建,每个来源都有不同的许可证。因此,无法使用现有的检查开放源码软件合规情况的方法。在本文件中,我们提出新的办法,评估在使用公开可得的某一数据集用于建立商业AI软件的情况下,可能违反许可证合规情况。我们在瓦威6区对两个产品组进行试验,通常公开使用数据集。我们的结果显示,如果这6个研究的数据集中,如果用于商业用途,则可能存在违反许可证的风险。因此,我们建议采用新的方法,用以评估可能违反许可证合规情况。因此,我们建议如何更好地使用公开认证。