Of Cyborg Developers and Big Brother Programming AI

dc.contributor.author Alexandru, Carol V.
dc.contributor.author Gall, Harald C.
dc.date.accessioned 2017-12-28T02:19:20Z
dc.date.available 2017-12-28T02:19:20Z
dc.date.issued 2018-01-03
dc.description.abstract The main reason modern machine learning mechanisms outperform hand-crafted solutions is the availability of high-quality data in large quantities. We observe that although many day-to-day activities in software engineering (such as bug triaging, reverting regressions, or even implementing code for properly scoped problems) could possibly be automated, we lack the necessary monitoring tools to capture all relevant information. Bug trackers and version control rely mostly on plain text, and specifications are informal or at best semi-structured. After setting the stage via a short excursion to the year 2047, we discuss how a ubiquitous AI, which can learn from every interaction a human developer has with a machine, could take over more and more of the mundane responsabilities in software engineering. We outline how this change will affect software engineering practice as well as education.
dc.format.extent 6 pages
dc.identifier.doi 10.24251/HICSS.2018.703
dc.identifier.isbn 978-0-9981331-1-9
dc.identifier.uri http://hdl.handle.net/10125/50592
dc.language.iso eng
dc.relation.ispartof Proceedings of the 51st Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Frontiers in AI and Software Engineering
dc.subject artificial intelligence, machine learning, software engineering, vision
dc.title Of Cyborg Developers and Big Brother Programming AI
dc.type Conference Paper
dc.type.dcmi Text
Files
Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
paper0705.pdf
Size:
293.12 KB
Format:
Adobe Portable Document Format
Description: