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Humans, Data and Machines
University of Arizona
6 episodes
6 months ago
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.
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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.
Show more...
Courses
Education
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Machine Influencers and Decision Makers
Humans, Data and Machines
59 minutes
7 years ago
Machine Influencers and Decision Makers
Jane Bambauer, Professor of Law, University of Arizona James E. Rogers College of Law Machine learning is shaping human lives in both obvious and subtle ways. Important economic and legal decisions about credit, employment, and criminal justice are already made with the aid of complex algorithms, raising difficult questions about whether machines can make decisions that are accurate and fair. Machine learners can become biased when the programmed objectives or the training data used to teach the algorithm are flawed. On the other hand, machines have some advantages over humans since they do not apply pre-existing assumptions and can more quickly recognize unexpected patterns. Machine learning also affects the human experience by creating advertising, suggestions, chat-bots, and even auto-generated news articles tailored to the individual. The government has some power to constrain artificial intelligence, but there are practical and constitutional limits to legal interventions.
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.