創新及科技解決方案

解決方案編號

S-0546

解決方案名稱

Using Explainable AI for transparent and reliable ML models

解決方案描述

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.

應用領域

財經
城市管理
發展
法律及保安
房屋
工商業
廣播
環境
基礎設施
教育
就業及勞工
康樂及文化
氣象
人口
社會福利
食物
衛生
運輸

使用的技術

機器學習
人工智能
深度學習
數據分析
預測分析

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／機構名稱

Glassbox AI Limited

電郵地址

aaliya@ust.hk

電話號碼

56924402

網址

xai.hk

地址

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

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