Stanford
University
  • Stanford Home
  • Maps & Directions
  • Search Stanford
  • Emergency Info
  • Terms of Use
  • Privacy
  • Copyright
  • Trademarks
  • Non-Discrimination
  • Accessibility
© Stanford University.  Stanford, California 94305.
Human-Centered Artificial Intelligence: Trusted, Reliable and Safe | Stanford HAI

Stay Up To Date

Get the latest news, advances in research, policy work, and education program updates from HAI in your inbox weekly.

Sign Up For Latest News

Navigate
  • About
  • Events
  • AI Glossary
  • Careers
  • Search
Participate
  • Get Involved
  • Support HAI
  • Contact Us
Skip to content
  • About

    • About
    • People
    • Get Involved with HAI
    • Support HAI
    • Subscribe to Email
  • Research

    • Research
    • Fellowship Programs
    • Grants
    • Student Affinity Groups
    • Centers & Labs
    • Research Publications
    • Research Partners
  • Education

    • Education
    • Executive and Professional Education
    • Government and Policymakers
    • K-12
    • Stanford Students
  • Policy

    • Policy
    • Policy Publications
    • Policymaker Education
    • Student Opportunities
  • AI Index

    • AI Index
    • AI Index Report
    • Global Vibrancy Tool
    • People
  • News
  • Events
  • Industry
  • Centers & Labs
Your browser does not support the video tag.
event

Human-Centered Artificial Intelligence: Trusted, Reliable and Safe

Status
Past
Date
Wednesday, October 30, 2019 12:00 PM - 4:00 PM PST/PDT
Topics
Ethics, Equity, Inclusion

The next generation of user experiences will produce 1000-fold improvements in human capabilities.  This new tools will amplify, augment, enhance, and empower people, just as the Web, email, search, navigation, digital photography, and many other applications have already done. Rather than emphasize autonomous machines and humanoid robots as team partners, these new tools will produce comprehensible, predictable, and controllable applications that promote self-efficacy, human responsibility, and social participation at scale.  The goal is to ensure human control, while increasing the level of automation. 

Share
Link copied to clipboard!
Event Contact
celia.clark@stanford.edu
650-725-4537

Related Events

Alexandr Lenk & Arvind Karunakaran | Industry Conversation with Instacart
SeminarSep 23, 202612:00 PM - 1:15 PM
September
23
2026

This seminar pairs a case study of AI diffusion with an organizational approach to technological changes in the workplace.

Seminar

Alexandr Lenk & Arvind Karunakaran | Industry Conversation with Instacart

Sep 23, 202612:00 PM - 1:15 PM

This seminar pairs a case study of AI diffusion with an organizational approach to technological changes in the workplace.

Marlowe | AI + Data for Science with Stephen Baccus
SeminarSep 23, 2026
September
23
2026

Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.

Event

Marlowe | AI + Data for Science with Stephen Baccus

Sep 23, 2026

Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.

World Development Report 2026: The Promise of Artificial Intelligence
Sep 24, 20269:00 AM - 4:15 PM
September
24
2026
Event

World Development Report 2026: The Promise of Artificial Intelligence

Sep 24, 20269:00 AM - 4:15 PM

Improved designs that produce trusted, reliable, and safe (TRS) systems will build on successful direct manipulation guidelines that provide a visual display of the objects of interest, rapid, incremental, and reversible operations, with informative feedback for every user action. Elevators, thermostats, airbags, text messaging systems, and the 737 MAX provide positive and negative lessons, in charting the landscape of autonomy and control.  Design guidelines and independent oversight mechanisms for prospective design reviews and retrospective analyses of failures will clarify the role of human responsibility, even as automation increases.  


Ben Shneiderman

Emeritus Distinguished University Professor in the Department of Computer Science, Founding Director (1983-2000) of the Human-Computer Interaction Laboratory (http://hcil.umd.edu), and a Member of the UM Institute for Advanced Computer Studies (UMIACS) at the University of Maryland.  He is a Fellow of the AAAS, ACM, IEEE, and NAI, and a Member of the National Academy of Engineering, in recognition of his pioneering contributions to human-computer interaction and information visualization. His widely-used contributions include the clickable highlighted web-links, high-precision touchscreen keyboards for mobile devices, and tagging for photos.  Shneiderman’s information visualization innovations include dynamic query sliders for Spotfire, development of treemaps for viewing hierarchical data, novel network visualizations for NodeXL, and event sequence analysis for electronic health records.

Ben is the co-author with Catherine Plaisant of Designing the User Interface: Strategies for Effective Human-Computer Interaction (6th ed., 2016).  He co-authored Readings in Information Visualization: Using Vision to Think (1999) and Analyzing Social Media Networks with NodeXL (2nd edition, 2019).  His book Leonardo’s Laptop (MIT Press) won the IEEE book award for Distinguished Literary Contribution. The New ABCs of Research: Achieving Breakthrough Collaborations (Oxford, 2016) describes how research can produce higher impacts.