Design World

  • Home
  • Technologies
    • 3D CAD
    • Electronics • electrical
    • Fastening & Joining
    • Factory automation
    • Linear Motion
    • Motion Control
    • Test & Measurement
    • Sensors
    • Fluid power
  • Learn
    • Ebooks / Tech Tips
    • Engineering Week
    • Future of Design Engineering
    • MC² Motion Control Classrooms
    • Podcasts
    • Videos
    • Webinars
  • LEAP AWARDS
  • Leadership
    • 2022 Voting
    • 2021 Winners
  • Design Guide Library
  • Resources
    • 3D Cad Models
      • PARTsolutions
      • TraceParts
    • Digital Issues
      • Design World
      • EE World
    • Women in Engineering
  • Supplier Listings

Building A Better ‘Bot’: Artificial Intelligence Helps Human Groups

By Yale University | May 18, 2017

Share

Artificial intelligence doesn’t have to be super-sophisticated to make a difference in people’s lives, according to a new Yale University study. Even “dumb AI” can help human groups.

In a series of experiments using teams of human players and robotic AI players, the inclusion of “bots” boosted the performance of human groups and the individual players, researchers found. The study appears in the May 18 edition of the journal Nature.

“Much of the current conversation about artificial intelligence has to do with whether AI is a substitute for human beings. We believe the conversation should be about AI as a complement to human beings,” said Nicholas Christakis, co-director of the Yale Institute for Network Science (YINS) and senior author of the study. Christakis is a professor of sociology, ecology & evolutionary biology, biomedical engineering, and medicine at Yale.

The study adds to a growing body of Yale research into the complex dynamics of human social networks and how those networks influence everything from economic inequality to group violence.

In this case, Christakis and first author Hirokazu Shirado conducted an experiment involving an online game that required groups of people to coordinate their actions for a collective goal. The human players also interacted with anonymous bots that were programmed with three levels of behavioral randomness — meaning the AI bots sometimes deliberately made mistakes. In addition, sometimes the bots were placed in different parts of the social network. More than 4,000 people participated in the experiment, which used a Yale-developed software called breadboard.

“We mixed people and machines into one system, interacting on a level playing field,” Shirado explained. “We wanted to ask, ‘Can you program the bots in simple ways?’ and does that help human performance?”

The answer to both questions is yes, the researchers said.

Not only did the inclusion of bots aid the overall performance of human players, it proved particularly beneficial when tasks became more difficult, the study found. The bots accelerated the median time for groups to solve problems by 55.6%.

Furthermore, the researchers said, the experiment showed a cascade effect of improved performance by humans in the study. People whose performance improved when working with the bots subsequently influenced other human players to raise their game.

The findings are likely to have implications for a variety of situations in which people interact with AI technology, according to Christakis and Shirado.

For instance, there may be an extended period in which human drivers share roadways with autonomous cars. Likewise, military scenarios may include more operations in which human soldiers work in tandem with AI. There also are myriad possibilities for online situations pairing humans with AI tech.

“There are many ways in which the future is going to be like this,” Christakis said. “The bots can help humans to help themselves.”


Filed Under: AI • machine learning, M2M (machine to machine)

 

Related Articles Read More >

Part 6: IDE and other software for connectivity and IoT design work
Part 4: Edge computing and gateways proliferate for industrial machinery
Part 3: Trends in Ethernet, PoE, IO-Link, HIPERFACE, and single-cable solutions
Machine Learning for Sensors

DESIGN GUIDE LIBRARY

“motion

Enews Sign Up

Motion Control Classroom

Design World Digital Edition

cover

Browse the most current issue of Design World and back issues in an easy to use high quality format. Clip, share and download with the leading design engineering magazine today.

EDABoard the Forum for Electronics

Top global problem solving EE forum covering Microcontrollers, DSP, Networking, Analog and Digital Design, RF, Power Electronics, PCB Routing and much more

EDABoard: Forum for electronics

Sponsored Content

  • Renishaw next-generation FORTiS™ enclosed linear encoders offer enhanced metrology and reliability for machine tools
  • WAGO’s smartDESIGNER Online Provides Seamless Progression for Projects
  • Epoxy Certified for UL 1203 Standard
  • The Importance of Industrial Cable Resistance to Chemicals and Oils
  • Optimize, streamline and increase production capacity with pallet-handling conveyor systems
  • Global supply needs drive increased manufacturing footprint development

Design World Podcasts

June 12, 2022
How to avoid over engineering a part
See More >
Engineering Exchange

The Engineering Exchange is a global educational networking community for engineers.

Connect, share, and learn today »

Design World
  • Advertising
  • About us
  • Contact
  • Manage your Design World Subscription
  • Subscribe
  • Design World Digital Network
  • Engineering White Papers
  • LEAP AWARDS

Copyright © 2022 WTWH Media LLC. All Rights Reserved. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of WTWH Media
Privacy Policy | Advertising | About Us

Search Design World

  • Home
  • Technologies
    • 3D CAD
    • Electronics • electrical
    • Fastening & Joining
    • Factory automation
    • Linear Motion
    • Motion Control
    • Test & Measurement
    • Sensors
    • Fluid power
  • Learn
    • Ebooks / Tech Tips
    • Engineering Week
    • Future of Design Engineering
    • MC² Motion Control Classrooms
    • Podcasts
    • Videos
    • Webinars
  • LEAP AWARDS
  • Leadership
    • 2022 Voting
    • 2021 Winners
  • Design Guide Library
  • Resources
    • 3D Cad Models
      • PARTsolutions
      • TraceParts
    • Digital Issues
      • Design World
      • EE World
    • Women in Engineering
  • Supplier Listings