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Government Service Delivery: Beyond Al and Machine Learning
Conferences & Talks



Recently, it seems the whole world has started using Artificial Intelligence (AI) for everything from making purchasing recommendations online and setting the temperature on your thermometer, to controlling machines in factories and driving trucks. 

But the inability for these systems to explain “why” the decisions and recommendations where made can cause confusion, uncertainty, and loss of trust. Prominent folks such as Bill Gates, Elon Musk, and Stephen Hawking have sounded the warning on relying too much on these opaque systems. Although many things need to be done to ensure the safety and increase transparency of AI, a new area of research called Explainable AI (XAI) may be part of the solution.

XAI aims to build AI that can describe why a certain recommendation was made, leading to systems that are easier to understand, trust, and ultimately to work with. There are several large research efforts being undertaken by organizations such as the Defence Advanced Research Projects Agency (DARPA) of the US Department of Defence, as well as the Palo Alto Research Center (PARC). Aki Ohashi will describe why XAI may be needed, the current activities within this nascent field, and the potential impacts and implications on government and industry.


upcoming events   view all 

What is the Future of Cybersecurity?
Alissa Johnson
26 September 2017 | George E. Pake Auditorium, PARC
PARC Forum  

Bringing Reliable (and Transparent) AI to Business (Keynote)
Tolga Kurtoglu, Keynote Presenter
28 September 2017 | Santa Clara, CA
Conferences & Talks  

AI’s Impact on Industry (Keynote Power Panel)
Tolga Kurtoglu, Moderator
28 September 2017 | Santa Clara, CA
Conferences & Talks