In our automated lives, we generate and interact with unprecedented amounts of data. This sea of information is constantly searched, catalogued, analyzed and referenced by machines with the ability to uncover patterns unseen by their human creators. These new insights have far reaching implications for our society. From our everyday presence online, to scientists sequencing billions of genes or cataloging billions of stars, to cars that drive themselves – this series of six lectures will explore how the confluence of humans, data and machines extends beyond science – raising new philosophical and ethical questions.
All content for Humans, Data and Machines is the property of University of Arizona and is served directly from their servers
with no modification, redirects, or rehosting. The podcast is not affiliated with or endorsed by Podjoint in any way.
In our automated lives, we generate and interact with unprecedented amounts of data. This sea of information is constantly searched, catalogued, analyzed and referenced by machines with the ability to uncover patterns unseen by their human creators. These new insights have far reaching implications for our society. From our everyday presence online, to scientists sequencing billions of genes or cataloging billions of stars, to cars that drive themselves – this series of six lectures will explore how the confluence of humans, data and machines extends beyond science – raising new philosophical and ethical questions.
Vincent J. Del Casino Jr., Vice President, Academic Initiatives and Student Success, Professor, School of Geography and Development, University of Arizona
This talk challenges the notion that “big data” are what people believe they are – large, singular inanimate manifestations of our proxy selves – and argues that there is no “big data” really, just millions of small bits and pieces brought together through a series of algorithmic possibilities. But, big data analytics and the robotic futures that they engender are clearly producing anxieties for everyday social life and institutions, such as the university, have to manage these anxieties as they rethink themselves in relation to big data analytics and their concomitant robotic futures. As a result, universities have to double-down on investments in a broad education by asking how big data are represented in society, how human life is being organized in relation to big data, and how an interdisciplinary future can help manage the rapid changes produced by advances in robots and robotic technologies.
Humans, Data and Machines
In our automated lives, we generate and interact with unprecedented amounts of data. This sea of information is constantly searched, catalogued, analyzed and referenced by machines with the ability to uncover patterns unseen by their human creators. These new insights have far reaching implications for our society. From our everyday presence online, to scientists sequencing billions of genes or cataloging billions of stars, to cars that drive themselves – this series of six lectures will explore how the confluence of humans, data and machines extends beyond science – raising new philosophical and ethical questions.
