For nearly a year, we’ve seen the COVID-19 numbers. It’s been an ever-growing climb on news channels, positive cases and daily death totals, fatality percentages, and more. The constant flow of information has been as overwhelming as it has heartbreaking. But what does all of this information mean, and what do we do with it? How do we know what the numbers are telling us? Clio Andris, whose work on a visualization tool released last summer has been met with much media attention and public use, joins the Interaction Hour to discuss.

The Covid-19 pandemic has necessitated a new approach to education, forcing some students to mix in-person learning with remote and others to learn only from the confines of their own homes. The pandemic has brought to the fore new challenges and potential solutions to address the pressing needs of students and educators, and it could expedite a transformation in how we think about education in the long term. Today, we’re joined by David Joyner, the executive director of online education in Georgia Tech’s College of Computing. He’ll help us understand the pressing needs during the pandemic, the long-term benefits of online education, and how we might bridge the gap between the best of both worlds.

One of the biggest challenges to achieving equity, diversity, and social impact in computing is how we engage with traditionally underrepresented populations in the field. Associate Professor Betsy DiSalvo is the principal investigator on the DataWorks project, a program that has brought employment and engagement to non-data scientists. In this episode, we’ll discuss the accomplishments of DataWorks, explore how it engages those without a background in computational thinking, and how it improves our pursuit of equity in computing.

It is a uniquely challenging time in human history. We are facing a deadly global pandemic that has killed more than half a million people and caused a tidal effect across all levels of our society – from health care to the economy to education to our social lives, and much, much more. In our own country, we are facing civil unrest as we reckon with the impacts of centuries of oppression and disproportionate treatment and opportunity of the Black community. And we must meet these pressing needs in the midst of a technological revolution that, if not handled properly, will continue to compound our past failures and threaten to leave us behind, unable to keep up. In times like these, it is important to remember what – or more accurately, whom – is at the center of all we do in Georgia Tech’s School of Interactive Computing.

Data ethics is central to all we do as researchers, educators, innovators, entrepreneurs, and even consumers. And yet it's an area that is woefully understood by the general public. Companies misuse data and take advantage of consumers who aren't entirely sure what they agree to when they sign the terms of use. Data that was meant to solve one important challenge is repurposed in unintended ways. How can we encourage our researchers to begin thinking about these implications? How can we make data use and ethics more accessible to the general public? All this and more is discussed on this LIVE edition of the Interaction Hour with Ayanna Howard, featuring guests Amy Bruckman, Ben Shapiro, and Amanda Meng.

Are humans too willing to transfer trust to AI systems that may or may not have earned it yet? What factors lead to that trust? What’s the threshold for how trustworthy a system, like autonomous vehicles, must be before we deploy worldwide, and how do we get there?

In a previous episode of the Interaction Hour, we discussed one potential space that could benefit from virtual reality. A group that included one of our faculty, Neha Kumar, was using the technology in the educational space, working with local teachers to develop virtual lessons that showed improved engagement and performance. Today, we return to the topic. Virtual and augmented reality continue to be among the most promising technologies, but what they are, what they will become, and where we will benefit is still up for debate. Even more pressing are the potential pitfalls – like privacy – which, without proper vigilance, could be exploited in much the same ways as social media.

Think about the most recent news headline you read. Was it completely objective, void of any presupposition of truth or language that may lead readers down one particular path of understanding? Or did it, more likely, contain subtle cues about how the message was being framed, casting doubt on its veracity or reliability. Every day, we are inundated with these types of texts that, on the surface, proclaim to be arbiters of truth but, due to simple word choice and message framing, can bias their consumers. Luckily, new tools are being developed to help us become more critical recipients of media. In this podcast, we chat with Diyi Yang about how artificial intelligence can help us identify this subjective bias in text – and how AI itself can reflect our own preexisting biases.

Machine learning. It’s a term often used, but not always understood in the world of technology. Every day, new innovations, products and capabilities are introduced and adopted by people all over the world, but there’s a bit of a disconnect between researcher and consumer. How is a system trained? Why does it make certain decisions under certain conditions? What kind of reasoning goes into its decision making, and how can we trust that its choice is informed, objective and, ultimately, correct?

Online communities like Reddit or Twitter act like town halls, where opinions are shared and everyone, in theory, has a voice. Only, it doesn’t always work like that. What was once optimistically viewed as a solution to public discourse, offering promises of open and logical discussions where anyone with a keyboard and an internet connection could speak their piece, has instead become a bit of a Wild West. Message boards have degraded into sources of harassment, misinformation, radicalization, and more. The question is: How can you moderate, while also maintaining the promise of free speech? How can you avoid discouraging posters whose content was moderated or removed, while encouraging them to remain a part of public discourse?