Avoiding Bias in Voice User Interfaces

IxDA Pittsburgh is a local chapter of the Interaction Design Association serving the design community in Pittsburgh through activities and discussions that facilitate growth, understanding, and development of the profession.Our monthly events include seminars, panels, and workshops. Rather than meeting on a specific day or week, we remain flexible, scheduling events to meet the availability of speakers, hosts, and organizers.Our members include anyone who is interested in facilitating positive and engaging experiences for people. Our practitioners are interaction designers, industrial designers, visual designers, product designers, developers, game designers, roboticists—you name it. To become a member, all you have to do issubscribe to our mailing listto learn about events, and show up. We try to keep all of our events totally free. You can also find us onFacebook,Twitter,LinkedIn,Flickr, andour website. Please join us!

IxDA Pittsburgh

In our first event of 2020, Charles Hannon will be reprising the talk he gave at Midwest UX 2019 in Grand Rapids. Please join us!

Two PNC Plaza

<p>IxDA Pittsburgh is kicking off 2020 with a forward looking topic from one of our long-time members. Charles Hannon is sharing the talk he gave last October at Midwest UX in Grand Rapids, Michigan. Start the new year off right with your design community and PNC Enterprise Innovation Team, and join us afterwards for discussion, drinks, and maybe even a little sushi at <a href="https://www.thewarrenpgh.com" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">The Warren Bar and Burrow</a>.</p>

<h1>About the Talk</h1><p>Humans today are giving speech to robots in two ways: with machine learning algorithms that use training data to understand and generate human language; and with direct human input, as interaction designers hard-code the responses of digital assistants (Alexa, Siri, Google Home) to human utterances. Both methods are vulnerable to the introduction of bias in robot speech. The training data crawled by learning algorithms are replete with human biases—especially gender and race biases—as several high-profile examples have shown. But everyday human language also carries a variety of biases in subtle forms, many of them well known to psychologists and sociolinguists. As interaction designers dive deeper into the world of Voice User Interfaces, they need to be aware of these biases in order to avoid replicating them in the language that we “teach” to these new devices. Ideally, and over time, to the extent that we can de-bias the speech of robots, the phenomenon of Linguistic Style Matching might cause human speech, over time, to become less biased as well.</p>

<h1>About Charles</h1><p>Charles Hannon is a professor of computing and information studies at Washington &amp; Jefferson College. He teaches courses in human-computer interaction, the history of information technology, information visualization, and project management. Charles also teaches in his college’s Gender and Women’s Studies program. He writes about user experiences and interaction design, educational technology, pedagogy, and occasionally, William Faulkner. You can find his essays in interactions and Smashing Magazine and at his blog <a href="http://uxappeal.com/" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">uxappeal.com</a>.</p>

<h1>About the Venue</h1><p>We’re grateful to be hosted this month by PNC Enterprise Innovation Team. There is generally parking available on the street within a few blocks, if not right out front. Street parking downtown is metered until 6:00 pm, and there are a variety of garages to park in with varying rates. <strong>You will need to present your ID </strong>at the desk for security to check against our list of attendees.</p>

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Avoiding Bias in Voice User Interfaces

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