메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색

논문 기본 정보

자료유형
학술저널
저자정보
Joff P. N. BRADLEY (Teikyo University) 정성은 (성균관대학교)
저널정보
한국영어영문학회 영어영문학 영어영문학 제66권 제4호
발행연도
2020.1
수록면
585 - 603 (19page)

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색

초록· 키워드

오류제보하기
Concerned with the manifold crises in knowledge production and the very concept of originality itself in the humanities, this essay juxtaposes the work of two very different people, namely, the great British writer George Orwell and the French philosopher Bernard Stiegler. This is undertaken to critique what the latter calls the unprecedented evolution of the “global mnemotechnical system” or the so-called Big Data revolution. The author finds in the time of artificial intelligence (AI) an emergent and epochal conflict arising between the authentic and inauthentic, the natural and the artefactual and where, in the contemporary moment, the humanities and AI partake in the agon of intelligence. To understand this agon, I will focus on the question of corruption, that is, the corruption of knowledge and the possibility of the corruption of the dogmatic code, as I am interested in the connection between creativity, invention and resistance. It seems like at present, just as Orwell envisioned, there is a struggle for the freedom to think in terms other than the totalitarianism of language and thought (from Big Brother to Big Data to Big Other). The humanities and AI are embroiled in an agon of intelligence and because of this the great uncertainty we suffer in these times, the search must begin in earnest for a new way of thinking, indeed a new kind of philosophy. The author considers the prospect of algorithmic dominance through Orwellian, Stieglerian, and Deleuzian lenses in order to call for the revaluation and affirmation of negentropic, that is contributory, forms of knowledge.

목차

등록된 정보가 없습니다.

참고문헌 (25)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

최근 본 자료

전체보기

댓글(0)

0