인공지능의 추천이 소비자의 심리적 반발에 미치는 영향
The Influence of AI Recommendation on Consumer Reactance
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초록
온라인 쇼핑과 IT 기술이 눈부시게 발전하며 기업들은 인공지능에 기반한 추천 알고리즘을 현장에 활발히 적용하고 있다. 기업 측면에서는 추천 관련 인력을 대체함으로써 비용을 줄이고 소비자는 대용량의 데이터를 통해 적합한 제품을 추천 받게 되므로 인공지능 추천 시스템의 도입은 양자 모두에게 환영받을 일이다. 그러나 인공지능이 추천의 주체로 등장하는 이 변화를 소비자가 과연 흔쾌히 수용하고 있는가를 질문할 필요가 있다. 과거 연구에 따르면 소비자들은 인공지능이 소비자 개개인의 고유성을 고려하지 못한다고 판단하여 인공지능의 개입을 부정적으로 평가했다. 본 연구는 이에 더하여 인공지능의 개입에 대한 심리적 반발이라는 장애물이 소비자에게 존재함을 보이고 있다. 좀 더 구체적으로 설명하면 인간이 추천할 때보다 인공지능이 추천할 때 소비자는 자신이 통제 당한다는 생각이 강해지고 그 결과 심리적 반발이 강해지는 것이다. 세 개의 실증연구가 이러한 주장을 뒷받침한다. 연구 1에서는 수제 맥주를 추천하는 상황을 가정하고 인간(직원, 전문가) 대비 인공지능의 추천이 심리적 반발을 증가시키는가를 검증했다. 결과는 예상대로 인공지능 조건에서 더 강한 심리적 반발이 나타났다. 연구 2에서는 매개효과를 검증했다. 즉, 인공지능의 추천이 의사결정을 돕는 게 아니라 통제한다고 생각하여 심리적 반발이 발생한다는 가설을 검증했고 이를 지지하는 결과가 나타났다. 연구 3에서는 커피 원두를 추천하는 상황을 가정하고 소비자의 통제욕구가 조절변수로 작용함을 보였다. 통제욕구가 강한 경우 인간 대비 인공지능의 추천 제품에 대한 구매의도가 낮아졌으나 통제욕구가 약한 경우 이 효과는 사라졌다.
Abstract
The development of online shopping and IT technology has driven the rapid growth of companies’ adoption of AI recommendation agents. Companies can save human costs by replacing recommendation staff with AI and consumers can be satisfied with a proper alternative recommended by AI using big data. Thus both sides would welcome the AI agent. However, it is worthy of asking whether consumers readily accept the change made by AI. According to past studies, consumers perceive that AI is less able than humans to consider consumers’ unique characteristics, consequently showing negative responses to AI’s suggestions. The current research proposes another hindrance to the AI agent adoption, which is psychological reactance. When AI makes a recommendation, consumers’ perception that they are controlled or manipulated becomes stronger than when a human makes a recommendation. The stronger perception of being controlled results in a higher reactance. Three studies provide evidence supporting our contention. Study 1 showed that psychological reactance increases in the AI-recommendation condition than the human(employee and expert) conditions. In Study 2, participants perceive that AI controls their decision process rather than helps them and this perception causes reactance. Lastly, Study 3 showed a boundary condition. Consumers with high desirability of control are less willing to buy a recommendation by AI than by a human. But this effect is weakened for consumers with low desirability of control.
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