THOUGHT LEADERS Introducing New Levels of Transparency with AI – Thought Leaders
But it was a Canadian health monitoring platform that had beaten them both to the punch, sending word of the outbreak to its customers as early as on December 31, 2019! The platform, BlueDot uses artificial intelligence-driven algorithms that scours foreign-language news reports, animal and plant disease networks, and official proclamations to give its clients advance warning to avoid danger zones like Wuhan.
Yet, for all the hope that AI brings, it still poses unanswered questions around transparency and trustworthiness.
There is currently no direct mechanism to trace the reasoning implicitly used by deep learning models.
This concern has created a need for transparency in machine learning, which has led to the growth of explainable AI, or XAI. It seeks to address the major issues that hinder our ability to fully trust AI decision-making — including bias and transparency. This new field of AI brings accountability to ensure that AI benefits society with better outcomes for all involved.
Explainable, predictable and traceable AI
One way to gain explainability in AI systems is to use machine learning algorithms that are inherently explainable. For example, simpler forms of machine learning such as decision trees, Bayesian classifiers, and other algorithms that have certain amounts of traceability and transparency in their decision making. They can provide the visibility needed for critical AI systems without sacrificing too much performance or accuracy.
Noticing the need to provide explainability for deep learning and other more complex algorithmic approaches, the US Defense Advanced Research Project Agency (DARPA) is pursuing efforts to produce explainable AI solutions through a number of funded research initiatives. DARPA describes AI explainability in three parts which include: prediction accuracy, which means models will explain how conclusions are reached to improve future decision making; decision understanding and trust from human users and operators, as well as inspection and traceability of actions undertaken by the AI systems.
The launch of the first global conference exclusively dedicated to XAI, the International Joint Conference on artificial intelligence: Workshop on Explainable Artificial Intelligence, is further proof that the age of XAI has come.
See the full story here: https://www.unite.ai/introducing-new-levels-of-transparency-with-ai-thought-leaders/