创新及科技解决方案

解决方案编号

S-0546

解决方案名称

Using Explainable AI for transparent and reliable ML models

解决方案描述

As AI grows at a rapid pace, it is vital to keep up with digital transformation in traditional industries, especially governance. However, the complexity of the novel solutions makes technology incompliant and difficult to interpret. At Glassbox AI, we aim to shed light on these black box models with the use of our proprietary Explainable AI (XAI), providing the ability to understand how predictions are made. Backed by researchers and professors, our XAI allows for overall explanations of how a model behaves, break down individual predictions into its features, model performance evaluations as well as fairness and bias calculations.
By adopting XAI, companies can improve the transparency, accountability, compliance, user understanding, and error detection capabilities of Artificial Intelligence (AI)systems. Overall, the use of our XAI services would lead to more effective and equitable decision-making processes.

应用领域

运输
财经
卫生
发展
环境
广播
人口
工商业
气象
社会福利
房屋
法律及保安
城市管理
食物
基础设施
康乐及文化
教育
就业及劳工

使用的技术

预测分析
数据分析
人工智能
机器学习
深度学习

使用例子

1.	Banking and Finance: Enhance customer trust and mitigate risk of discrimination while conducting credit scoring, fraud detection, and investment management using transparent and fair Artificial Intelligence systems.
2.	Regulatory Services: Increase accountability of trained models dealing with sensitive data by ensuring decisions are made fairly and without bias.
3.	Healthcare: Ensure interpretability and accuracy in medical diagnosis, treatment recommendations, drug development and more with ExplainableAI.

Our XAI allows projects to leverage cutting edge technologies responsibly due to model explainability and ethical AI standards to ensure fairness. This makes machine learning adoption trustworthy for all stakeholders, including institutions running these projects as well as the general public.

公司／机构名称

Glassbox AI Limited

电邮地址

aaliya@ust.hk

电话号码

56924402

网址

xai.hk

地址

Unit 740, Building 19W, Hong Kong Science & Technology Park, Pak Shek Kok, NT, HK

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