2017 Report

This report aggregates a diverse set of data, makes that data accessible, and includes discussion about what is provided and what is missing. Most importantly, the AI Index 2017 Report is a starting point for the conversation about rigorously measuring activity and progress in AI in the future.

Volume of Activity

The Volume of Activity metrics capture the "how much" aspects of the field, like attendance at AI conferences and VC investments into startups developing AI systems.

Technical Performance

The Technical Performance metrics capture the "how good" aspects; for example, how well computers can understand images and prove mathematical theorems.

Derivative Measures

We investigate the relationship between trends. We also introduce an exploratory measure, the AI Vibrancy Index, that combines trends across academia and industry to quantify the liveliness of AI as a field.

Towards Human Peformance

We outline a short list of notable areas where AI systems have made significant progress towards matching or exceeding human performance. We also discuss the difficulties of such comparisons.

Expert Forum

We include subjective commentary from a cross-section of AI experts. This Expert Forum helps animate the story behind the data in the report and adds interpretation the report lacks.
Susan Alzner
Barbara Grosz
Eric Horvitz
Kai-Fu Lee
Sinovation Ventures
Alan Mackworth
Andrew Ng
Stanford, Coursera
Daniela Rus
Megan Smith
USA CTO, shift7
Sebastian Thrun
Stanford, Udacity
Michael Wooldridge


Yoav Shoham (Chair)
Ray Perrault
Erik Brynjolfsson
Jack Clark
James Manyika
Calvin LeGassick
(Project Manager)
(Project Manager)