How do People and AI Interact?

 Addressing one of the most fundamental questions:  How do people and AI work together?   There are so many components, and they are likely to be continually changing as we progress.   We examined, and continue to examine modes like interactive conversations, Attentive systems, Intelligent micro services,  Task analysis,  Process design, Visual interactions and more.  I much like the emphases described below.

Where are we going from here?   How will humans and machines need to adjust to make these interactions efficient?   Where do we start to make success likely?   Following the below, and look forward to the published tools promised.   Join us.

Google announces: PAIR: the People + AI Research Initiative
Written by  
Martin Wattenberg, Senior Staff Research Scientist, Google Brain
Fernanda Viégas, Senior Staff Research Scientist, Google Brain

The past few years have seen rapid advances in machine learning, with dramatic improvements in technical performance—from more accurate speech recognition, to better image search, to improved translations. But we believe AI can go much further—and be more useful to all of us—if we build systems with people in mind at the start of the process.

Today we’re announcing the People + AI Research initiative (PAIR) which brings together researchers across Google to study and redesign the ways people interact with AI systems. The goal of PAIR is to focus on the "human side" of AI: the relationship between users and technology, the new applications it enables, and how to make it broadly inclusive. The goal isn’t just to publish research; we’re also releasing open source tools for researchers and other experts to use.

PAIR's research is divided into three areas, based on different user needs:

Engineers and researchers: AI is built by people. How might we make it easier for engineers to build and understand machine learning systems? What educational materials and practical tools do they need?

Domain experts: How can AI aid and augment professionals in their work? How might we support doctors, technicians, designers, farmers, and musicians as they increasingly use AI?

Everyday users: How might we ensure machine learning is inclusive, so everyone can benefit from breakthroughs in AI? Can design thinking open up entirely new AI applications? Can we democratize the technology behind AI? .... "