Title:
Opportunities and Perils of Data Science

Simple item page
dc.contributor.author Spector, Alfred Z.
dc.contributor.corporatename Georgia Institute of Technology. College of Computing en_US
dc.contributor.corporatename Georgia Institute of Technology. School of Computer Science en_US
dc.contributor.corporatename Two Sigma Investments en_US
dc.date.accessioned 2021-10-22T17:46:20Z
dc.date.available 2021-10-22T17:46:20Z
dc.date.issued 2021-10-15
dc.description Presented in-person and online via Bluejeans Events on October 15, 2021 att 2:00 p.m. en_US
dc.description Dr. Alfred Z. Spector was most recently CTO and Head of Engineering at Two Sigma, a firm dedicated to algorithmic approaches to a wide collection of financial optimization problems. His career has led him from innovation in large scale, networked computing systems to broad engineering and research leadership. Most recently, he has been writing a book on Data Science, which will be published in early 2022. Spector lectures widely on the growing importance of computer science across all disciplines based on the evocative phrase, CS+X. More recently, he has written and lectured on the societal implications of data science -- both the great benefits and the unintended consequences. en_US
dc.description Runtime: 64:39 minutes en_US
dc.description.abstract Data science has provided unprecedented opportunities to learn new insights and to predict, recommend, cluster, classify, transform, and optimize. Catalyzed by large-scale, networked computer systems, vast availability of data, and machine learning algorithms, data science has been extraordinarily impactful to-date, and it holds great promise in all disciplines. However, no new technology arrives without complications, and we have recently seen both the press and various political circles illustrating real, potential, and fictional implications of the field. This presentation aims to balance the opportunities provided by data science against the many challenges that have ensued. At its core, the talk proposes a rubric that practitioners can apply to tease out data science’s complexities and also maps out seven categories of data sciences challenges, ranging from engineering to ethics. The talk is illustrated with examples from many applications, and it concludes with some suggested ways to address the downsides of the field. en_US
dc.format.extent 64:39 minutes
dc.identifier.uri http://hdl.handle.net/1853/65394
dc.language.iso en_US en_US
dc.relation.ispartofseries School of Computer Science Colloquium;
dc.relation.ispartofseries School of Computer Science Lectures
dc.subject Classify en_US
dc.subject Cluster en_US
dc.subject Data science en_US
dc.subject Optimization en_US
dc.subject Prediction en_US
dc.title Opportunities and Perils of Data Science en_US
dc.type Moving Image
dc.type.genre Lecture
dspace.entity.type Publication
local.contributor.corporatename College of Computing
local.contributor.corporatename School of Computer Science
local.relation.ispartofseries School of Computer Science Colloquium
relation.isOrgUnitOfPublication c8892b3c-8db6-4b7b-a33a-1b67f7db2021
relation.isOrgUnitOfPublication 6b42174a-e0e1-40e3-a581-47bed0470a1e
relation.isSeriesOfPublication 63de5985-0c5c-405a-a8cc-20cbcb51c285
Files
Original bundle
Now showing 1 - 4 of 4
No Thumbnail Available
Name:
spector.mp4
Size:
303.49 MB
Format:
MP4 Video file
Description:
Download video
Download
No Thumbnail Available
Name:
spector_videostream.html
Size:
1.32 KB
Format:
Hypertext Markup Language
Description:
Streaming video
Download
No Thumbnail Available
Name:
transcript.txt
Size:
54.72 KB
Format:
Plain Text
Description:
Transcription
Download
Thumbnail Image
Name:
thumbnail.jpg
Size:
51.12 KB
Format:
Joint Photographic Experts Group/JPEG File Interchange Format (JFIF)
Description:
Thumbnail
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
3.13 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
Scholarly Events