Explaining system intelligence

This blog belongs to the series about intelligent system design. You might also be interested in my previous blog, 5 Challenges to Your Machine Learning Project.

One of the guiding design principles for intelligent systems is to empower end users. If we want people to trust machines, we must share information about the underlying models and the reasoning behind the results of algorithms.This is even more vital for business applications, when users are held accountable for every decision they make.

It’s widely accepted that intelligent systems must come with a certain level of transparency. There’s even a new term for it: explainable AI. But, that’s just the beginning. As designers, we need to ask ourselves how explainable AI is tied to user interaction. What do we need to think about when we explain the results and recommendations that come from built-in intelligence? And how can we make it a seamless experience that feels natural to users?

My next article about Explanaible AI and its UX.


Human in Control or Automate Everything?

This blog is the second in a series on intelligent system design. You might also be interested in the first blog, Principles of Intelligent System Design.

It is a common misconception that artificial intelligence inevitably means 100% automation. Movie producers would have us believe that AI is going to control absolutely everything — a Skynet scenario à la Terminator. So, if you design and implement an AI system, should you fear this or just ignore it? Is there a roadmap for intelligent automation of a specific system?

My second article on User Experience and Artificial Intelligence.

My First Article: Design Principles for Intelligent Systems

So what I am doing at SAP? I can not share everything, but may be a part of it…

Currently I am lucky to work as a UX designer on such an interesting topic as User Experience for Artificial Intelligence. As Google’s designer Josh Lovejoy mentions in Method podcast, there is currently nobody who can seriously  claim he is an expert in UX for AI.

Indeed it is a very new field, so I start writing to share my thoughts, raise my questions  and get into discussion with the community.

How does machine learning impact the user interface (UI)? Should I explicitly surface the system intelligence? How much should I explain? What is the feedback loop and when it is important? Are there any UI patterns I can follow?

I try to answer all these questions in my first article on the topic.

17. Eppingen Juniors Chess Open

As my son started playing this chess tournament last year I was used to  go through this charming retro page to look up the results on this page. It was build with Microsoft FrontPage 10 years ago. Its nice blue (#0000ff) background and a yellow (#00ffff) text were almost OK. What I could not resist was a constantly running line (remember MARQUEE tag?) …

Finally I decided to make a world a little bit better and built a new version of it with Google Material Design.