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Sae bom Kwon

dblp:199/3210 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Human-AI interaction · 100%
Artificial intelligence
1 paper
Multi-agent systems · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Human-AI interaction
user perception of AI
0.312017
Us vs. Them: Understanding Artificial Intelligence Technophobia over the Google DeepMind Challenge Match · CHI 2017
Knowledge, reasoning and agents › Multi-agent systems
Game AI
0.112017
Us vs. Them: Understanding Artificial Intelligence Technophobia over the Google DeepMind Challenge Match · CHI 2017

Methods — techniques the papers use, named apart from their topics

interviews · 0.6case study · 0.6
YearPublicationVenuePosition
2017 Us vs. Them: Understanding Artificial Intelligence Technophobia over the Google DeepMind Challenge Match
abstract
Various forms of artificial intelligence (AI), such as Apple's Siri and Google Now, have permeated our everyday lives. However, the advent of such "human-like" technology has stirred both awe and a great deal of fear. Many consider it a woe to have an unimaginable future where human intelligence is exceeded by AI. This paper investigates how people perceive and understand AI with a case study of the Google DeepMind Challenge Match, a Go match between Lee Sedol and AlphaGo, in March 2016. This study explores the underlying and changing perspectives toward AI as users experienced this historic event. Interviews with 22 participants show that users tacitly refer to AlphaGo as an "other" as if it were comparable to a human, while dreading that it would come back to them as a potential existential threat. Our work illustrates a confrontational relationship between users and AI, and suggests the need to prepare for a new kind of user experience in this nascent socio- technological change. It calls for a collaborative research effort from the HCI community to study and accommodate users for a future where they interact with algorithms, not just interfaces.
Changhoon Oh, Yoojung Kim, SoHyun Park, Sae bom Kwon, Bongwon Suh
CHI5