S-0546
Using Explainable AI for transparent and reliable ML models
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.
廣播
城市管理
氣象
工商業
發展
教育
就業及勞工
環境
財經
食物
衛生
房屋
基礎設施
法律及保安
人口
康樂及文化
社會福利
運輸
人工智能
數據分析
深度學習
機器學習
預測分析
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.
Glassbox AI Limited
56924402
Unit 740, Building 19W, Hong Kong Science & Technology Park, Pak Shek Kok, NT, HK
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