Ethical Responsibilities of Preserving Academicians in an Age of Mechanized Learning: Balancing the Demands of Educating at Capacity and Preserving Human Interactivity

Artificial Intelligence, Open Standards, And Emerging Education

The proliferation of increasingly-complex systems of artificial intelligence, intelligent machines, information aggregation and interpretation is driven, in part, by educational opportunity and profit. Though there are numerous ways to approach the boundaries and meanings of “intelligence” when applied to computerized technology, several themes are especially critical: educational data modeling in the aggregate is expanding and is, thus, becoming more accurate and reliable; the way intelligence is defined may need serious revision soon; and the ways people learn are being tested and refined with technology. The rapidity of such innovation is underpinned with open standards, open source software, and systems designed for linking data (like JSON-LD) from searches to outcomes. What this means to classrooms, both virtual and brick-and-mortar, to students, and to instructors is an open question. Certain specific projects that link individual data, educational opportunities, and transparent assessment, like open digital badges, bridge together the current capabilities with a promise to the immediate future (Schenke, Tran, & Hickey, 2013).