Themes From an AI and ML Roundtable Discussion

Joanna F. DeFranco
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Abstract

Artificial intelligence (AI) and machine learning (ML) are technologies that are increasingly being integrated into many critical domains such as healthcare, finance, and vehicles. These are all critical systems given their consequences of failure. Therefore, aspects of these systems such as the data gathered to train them need to be representative of the real world. For systems to be trusted by the public in the sense that they will work as intended and will not cause harm, systems should have the characteristics of trustworthy AI as outlined in NIST AI 100-1: valid and reliable, safe, secure, and resilient, accountable and transparent, explainable and interpretable, privacy-enhanced, and fair with harmful bias managed. NIST “Artificial Intelligence Risk Management Framework (AI RMF 1.0”), January 2023, https://nvlpubs.nist.gov/nistpubs/ai/NIST.AI.100-1.pdf
人工智能与 ML 圆桌讨论的主题
人工智能(AI)和机器学习(ML)技术正日益融入医疗保健、金融和汽车等许多关键领域。鉴于其故障后果,这些都是关键系统。因此,这些系统的各个方面,例如为训练它们而收集的数据,都需要能够代表真实世界。要使系统得到公众的信任,即系统能按预期运行且不会造成伤害,系统应具备 NIST AI 100-1 中概述的值得信赖的人工智能的特征:有效和可靠、安全、可靠和弹性、负责和透明、可解释和可解读、隐私增强、公平且有害偏差可控。NIST "人工智能风险管理框架(AI RMF 1.0)",2023 年 1 月,https://nvlpubs.nist.gov/nistpubs/ai/NIST.AI.100-1.pdf。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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