Of Cyborg Developers and Big Brother Programming AI

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dc.contributor.authorAlexandru, Carol V.
dc.contributor.authorGall, Harald C.
dc.date.accessioned2017-12-28T02:19:20Z
dc.date.available2017-12-28T02:19:20Z
dc.date.issued2018-01-03
dc.description.abstractThe 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.extent6 pages
dc.identifier.doi10.24251/HICSS.2018.703
dc.identifier.isbn978-0-9981331-1-9
dc.identifier.urihttp://hdl.handle.net/10125/50592
dc.language.isoeng
dc.relation.ispartofProceedings of the 51st Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectFrontiers in AI and Software Engineering
dc.subjectartificial intelligence, machine learning, software engineering, vision
dc.titleOf Cyborg Developers and Big Brother Programming AI
dc.typeConference Paper
dc.type.dcmiText

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