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27 minutes | 20 days ago
Is the presence of a human enough to regulate an AI decision-making system?
From helping to identify tumors to guiding trading decisions on Wall Street, artificial intelligence has begun to inform important decision-making, but always with the input of a human. However, not all humans respond the same way to algorithmic advice. This episode of Consequential looks at human-in-the-loop AI, with guests Sumeet Chabria, David Danks, and Maria De-Arteaga.
29 minutes | a month ago
Enron, Wikipedia and the Deal with Biased Low-Friction Data
The Enron emails helped give us spam filters, and many natural language processing and fact-checking algorithms rely on data from Wikipedia. While these data resources are plentiful and easily accessible, they are also highly biased. This week, we speak to guests Amanda Levendowski and Katie Willingham about how low-friction data sources contribute to algorithmic bias and the role of copyright law in accessing less troublesome sources of knowledge and data.
26 minutes | 2 months ago
Can automation make peer review faster and fairer?
Peer review is the backbone of research, upholding the standards of accuracy, relevance and originality. However, as innovation in the fields of AI and machine learning has reached new heights of productivity, it has become more difficult to perform peer review in a fast and fair manner. Our hosts are joined by Nihar Shah to unpack the question of automation in the scientific publication process: could it help, is it happening already, and what does it have in common with the job application process?
0 minutes | 2 months ago
Enjoy The Long Weekend!
We're taking a day off today from our episode and will be back in December. Have a great holiday weekend!
30 minutes | 2 months ago
Is Crowdsourcing the Answer to our Data Diversity Problem?
Traditional scientific research has a data diversity problem. Online platforms, such as Mechanical Turk, give researchers access to a wider variety and greater volume of subjects, but they are not without their issues. Our hosts are joined by experts David S. Jones, Ilka Gleibs, and Jeffrey Bigham to discuss the pros and cons of knowledge production using crowdsourced data.
32 minutes | 3 months ago
If Banning Bots Won't Stop Disinformation, What Will?
Disinformation is as old as the printing press, if not older. So what has accelerated its spread now, and what can be done to stop it? On this special bonus episode of Consequential, we speak to the experts about disinformation, the election, and COVID-19.
32 minutes | 3 months ago
Knowledge Production and the Bias Pipeline: The Story of the EEG
In the first episode of Season 3 of Consequential, hosts Eugene and Lauren look at how underlying biases in the development of the EEG have impacted healthcare, medical technology, and scientific research, with guests Ben Amaba, Arnelle Etienne, Pulkit Grover, and Shawn Kelly.
2 minutes | 3 months ago
Season 3 Trailer - Knowledge is Power
In Season 3 of Consequential, hosts Eugene and Lauren will be exploring knowledge production in the Information Age. Beginning on October 21, this season will examine how AI and machine learning will impact research practices and data collection, as well as the development and dissemination of knowledge. Topics will include combatting disinformation, the ethics of crowdsourced research, and representation in open source software development.
44 minutes | 7 months ago
How Do You Reopen A State?
Today we're asking our experts: how do you coordinate a crisis response to an issue like COVID-19, where every public health decision has economic ramifications, and every economic decision has a direct impact on public health? To answer these questions, we speak to Dean Ramayya Krishnan of Heinz College; Professor of Machine Learning and Public Policy, Rayid Ghani; and Distinguished Service Professor Richard Stafford.
1 minutes | 8 months ago
An Update from Consequential
With consideration to the events of the past week and in order to hold space for the voices that are boldly challenging systemic racism and injustice, we have decided to postpone the release of our new episode. We would also like to echo the sentiment expressed by Carnegie Mellon's President Farnam Jahanian, that it is up to each one of us – no matter our background – to confront and dismantle racism and injustice wherever they exist.
33 minutes | 8 months ago
Death by a Thousand Emails
Can teams still be effective when working together remotely? Is working from home the future of work? In this week’s episode, hosts Eugene and Lauren talk to Professor Anita Williams Woolley of Carnegie Mellon’s Tepper School of Business to learn about how communication and collaboration change once teams are no longer face-to-face, and we hear from people in a variety of fields about their experience working remotely.
38 minutes | 8 months ago
How will COVID-19 Change Higher Ed?
In the span of just two weeks, the entire American higher education system moved online due to COVID-19. While this is often considered a temporary measure, the truth is that higher ed may never fully go back to normal. And in some regards, we may not want it to. In this week’s episode, hosts Eugene and Lauren talk to professors across the United States about the future of higher education.
39 minutes | 9 months ago
Sorry, Your Phone Says You Have Anxiety
How will certain new standards for data sharing and surveillance during the COVID-19 pandemic impact the future of healthcare? In episode two of Consequential's two-part deep-dive on pandemics, public health and privacy, hosts Eugene and Lauren talk to David S. Jones of Harvard University and Henry Kautz of the National Science Foundation about the impact of big data on health and privacy.
34 minutes | 9 months ago
Pandemics, Public Data, and Privacy
Mobile data records, tracking devices and government-mandated selfies have played a large role in both enforcing quarantines and providing data to better understand the coronavirus. In this week’s episode of Consequential, hosts Eugene and Lauren talk to Wilbert Van Panhuis, an infectious disease epidemiologist at the University of Pittsburgh; Tom Mitchell, the Lead Technologist of the Block Center and a computer scientist at Carnegie Mellon University; and Scott Andes, the Executive Director of the Block Center, about the importance of collecting and using data for public health, the individual privacy concerns that arise as a result of this data collection, and the challenges of striking a balance between societal benefit and personal privacy. This episode is part one of a two-episode look on large-scale public health data analytics.
3 minutes | 10 months ago
Update: Season 2 & Coronavirus Miniseason
In light of recent developments related to COVID-19, we have decided to push back our second season to focus instead on what we can learn from the coronavirus in terms of technology and society. In our mini-season, we will cover the use of large-scale public health data, remote education, and the future of work.
29 minutes | a year ago
A Policy Roadmap
Over the last 9 episodes, we’ve presented a variety of questions and concerns relating to the impacts of technology, specifically focusing on artificial intelligence. To end season 1, we want to take a step back and lay out a policy roadmap that came together from the interviews and research we conducted. We will outline over 20 different steps and actions that policymakers can take, starting with laying the necessary foundations to applying regulatory frameworks from other industries to novel approaches.
35 minutes | a year ago
Paging Dr. Robot
Don’t worry, your next doctor probably isn’t going to be a robot. But as healthcare tech finds its way into both the operating room and your living room, we’re going to have to answer the kinds of difficult ethical questions that will also determine how these technologies could be used in other sectors. We will also discuss the importance of more robust data-sharing practices and policies to drive innovation in the healthcare sector.
30 minutes | a year ago
The Future of Work
If artificial intelligence can do certain tasks better than we can, what does that mean for the concept of work as we know it? We will cover human-AI collaboration in the workplace: what it might look like, what it could accomplish and what policy needs to be put in place to protect the interests of workers.
33 minutes | a year ago
A Particular Set of Skills
The World Economic Forum has found that while automation could eliminate 75 million jobs by 2022, it could also create 133 million new jobs. In this episode, we will look at how to prepare potentially displaced workers for these new opportunities. We will also discuss the “overqualification trap” and how the Fourth Industrial Revolution is changing hiring and credentialing processes.
31 minutes | a year ago
If you think about any piece of pop culture about the future, it takes place in a city. Whether we realize it or not, when we imagine the future, we picture cities, and that idea is all the more problematic when it comes to who benefits from technological change and who does not. This episode will look at how emerging technologies can keep communities connected, rather than widen divides or leave people behind.
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