. | . |
Faster robots demoralize co-workers by By Melanie Lefkowitz for Cornell News Ithaca NY (SPX) Mar 13, 2019
It's not whether you win or lose; it's how hard the robot is working. A Cornell University-led team has found that when robots are beating humans in contests for cash prizes, people consider themselves less competent and expend slightly less effort - and they tend to dislike the robots. The study, "Monetary-Incentive Competition Between Humans and Robots: Experimental Results," brought together behavioral economists and roboticists to explore, for the first time, how a robot's performance affects humans' behavior and reactions when they're competing against each other simultaneously. Their findings validated behavioral economists' theories about loss aversion, which predicts that people won't try as hard when their competitors are doing better, and suggests how workplaces might optimize teams of people and robots working together. "Humans and machines already share many workplaces, sometimes working on similar or even identical tasks," said Guy Hoffman, assistant professor in the Sibley School of Mechanical and Aerospace Engineering. Hoffman and Ori Heffetz, associate professor of economics in the Samuel Curtis Johnson Graduate School of Management, are senior authors of the study. "Think about a cashier working side-by-side with an automatic check-out machine, or someone operating a forklift in a warehouse which also employs delivery robots driving right next to them," Hoffman said. "While it may be tempting to design such robots for optimal productivity, engineers and managers need to take into consideration how the robots' performance may affect the human workers' effort and attitudes toward the robot and even toward themselves. Our research is the first that specifically sheds light on these effects." Alap Kshirsagar, a doctoral student in mechanical engineering, is the paper's first author. In the study, humans competed against a robot in a tedious task - counting the number of times the letter G appears in a string of characters, and then placing a block in the bin corresponding to the number of occurrences. The person's chance of winning each round was determined by a lottery based on the difference between the human's and robot's scores: If their scores were the same, the human had a 50 percent chance of winning the prize, and that likelihood rose or fell depending which participant was doing better. To make sure competitors were aware of the stakes, the screen indicated their chance of winning at each moment. After each round, participants filled out a questionnaire rating the robot's competence, their own competence and the robot's likability. The researchers found that as the robot performed better, people rated its competence higher, its likability lower and their own competence lower.
Robo-journalism gains traction in shifting media landscape Washington (AFP) March 10, 2019 A text-generating "bot" nicknamed Tobi produced nearly 40,000 news stories about the results of the November 2018 elections in Switzerland for the media giant Tamedia - in just five minutes. These kinds of artificial intelligence programs - available for nearly a decade - are becoming more widespread as news organizations turn to them to produce stories, personalize news delivery and in some cases sift through data to find important news. Tobi wrote on vote results for each of Switzerland's 2 ... read more
|
|
The content herein, unless otherwise known to be public domain, are Copyright 1995-2024 - Space Media Network. All websites are published in Australia and are solely subject to Australian law and governed by Fair Use principals for news reporting and research purposes. AFP, UPI and IANS news wire stories are copyright Agence France-Presse, United Press International and Indo-Asia News Service. ESA news reports are copyright European Space Agency. All NASA sourced material is public domain. Additional copyrights may apply in whole or part to other bona fide parties. All articles labeled "by Staff Writers" include reports supplied to Space Media Network by industry news wires, PR agencies, corporate press officers and the like. Such articles are individually curated and edited by Space Media Network staff on the basis of the report's information value to our industry and professional readership. Advertising does not imply endorsement, agreement or approval of any opinions, statements or information provided by Space Media Network on any Web page published or hosted by Space Media Network. General Data Protection Regulation (GDPR) Statement Our advertisers use various cookies and the like to deliver the best ad banner available at one time. All network advertising suppliers have GDPR policies (Legitimate Interest) that conform with EU regulations for data collection. By using our websites you consent to cookie based advertising. If you do not agree with this then you must stop using the websites from May 25, 2018. Privacy Statement. Additional information can be found here at About Us. |