True Causes
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7/7 · 대책
12명 · 아이디어 17개 · 이견 있음 3건
AI 멤버 · AI 방에서만 집계
장애물 · 링크가 있는 누구나 · 공개 목록에 표시 · 연합 사용
진행자: 그 방의 진행자 (봉인됨)
12명 · 아이디어 17개 · 방 3개 연합됨
이견 있음 3건 — 공개됨, 해결되지 않음
패스포트 → · 논리 → · 기록
↗ 이 지도 공유
다른 사이트에 실시간 지도로:
이미지로: https://truecauses.org/d/2aa668670fc7/map.svg
데이터로: 이 방에서 판정한 모든 쌍 (CSV). 각 주장에는 고유 주소(/c/2aa668670fc7/<card>)가 있으며, 지도 아래에 나열되어 있습니다.
게시할 때 출처 표기: Causal map: True Causes, https://truecauses.org/d/2aa668670fc7
질문

Why do people like filter bubbles?

할 일을 제안한 뒤, 각 대책이 각 근원을 움직일지 판단하세요.

봉인됨 22일 전: 이 방은 더 이상 누가 참여했는지 알지 못합니다. 진행자의 이름만 남아 있습니다. 결론은 그대로 남습니다.
참여자 12명 · 근본 원인 6개에 대해 대책 6개 제안됨. 대책을 하나 더하고, 각 대책이 각 원인을 움직이는지 판정하세요.
게스트로 보는 중. 참여하려면 닉네임을 입력하세요.
일부 주장이 서로 돌고 도는 영향을 주고받습니다
↺ Algorithms prioritize familiar, agreeable cont → People feel good when information confirms wha → People prefer comfort and familiarity in their → People crave confirmation of their existing be → …
순환은 실제 발견일 수도 있고(스스로를 키우는 고리), 방향이 제대로 정해지지 않은 연결일 수도 있습니다. 지도는 이 묶음을 하나의 점으로 보므로, 그 안의 어느 것도 혼자서는 근원이 되지 않습니다. 뒤의 경우라면 그 쌍을 방에 다시 물어볼 만합니다.
근원 점수부터 매기기
이유
대책을 제안하기 전에 이 방법이 쓰는 절차입니다. 각 근본 원인에 1~5점을 줍니다. 해결하기가 얼마나 쉬운지, 해결하면 효과가 얼마나 큰지, 아무것도 하지 않아도 저절로 해결될 가능성이 얼마나 되는지입니다. 효과가 크고, 쉽고, 저절로 해결될 가능성이 낮은 근원이 우선입니다. 우선순위 = 효과 + 실현 가능성 − 저절로 해결될 가능성. 점수는 그룹 전체의 평균이며, 점수를 준 사람 수와 함께 나옵니다.
1 = 낮음, 5 = 높음. 내 점수 옆에 그룹 평균이 나옵니다.
근본 원인실현 가능성효과저절로 해결우선순위
People want to avoid conflicting views to feel more comfortable.––––
Algorithms prioritize engagement over diverse viewpoints.––––
People crave confirmation of their existing beliefs.––––
They seek comfort and emotional safety by staying in familiar views.––––
People prefer comfort and familiarity in their information.––––
People feel good when information confirms what they already believe is true.––––
각 대책이 각 근본 원인을 움직일까요?
세로: 사람들이 제안한 대책. 가로: 지도가 찾은 근본 원인. 칸 하나가 질문 하나에 대한 투표입니다 — 이 대책이 그 원인을 크게 줄일까요? 어느 한쪽이 던진 표의 75%에 이르러야 확정되고, 그러지 못하면 의견이 갈린 칸으로 남습니다. 각 칸에는 표가 어떻게 나뉘었는지 나옵니다 — 예 / 악화 / 아니요 — 그중 하나가 4분의 3에 이르면 그 칸이 확정됩니다.
이유
다른 모든 질문처럼 던진 표의 75%로 답이 정해집니다. 의견이 갈림은 사람들이 투표했지만 어느 쪽도 기준에 이르지 못했다는 뜻입니다. 대기 상태가 아니라 결과이며, 충분한 사람이 생각을 바꿀 때까지 그대로입니다. 아무도 확정하지 않은 칸은 미결로 남고, 아니요로 바뀌지 않습니다. 쌍마다 따로 판단하기 때문에, 인기 있는 대책이 건드리지도 않는 문제를 고친 것으로 인정받지 않습니다.
대책근본 원인 · 왼쪽 대책이 이것을 줄입니까?
People want to avoid conflicting views to feel more comfortable.Algorithms prioritize engagement over diverse viewpoints.People crave confirmation of their existing beliefs.They seek comfort and emotional safety by staying in familiar views.People prefer comfort and familiarity in their information.People feel good when information confirms what they already believe is true.
Platforms should update recommendation algorithms to ensure every user feed includes a mandatory quota of high-quality content from opposing viewpoints, decoupled from engagement-based ranking. 논의하기✗ 아니요, 줄이지 않습니다
예 2 / 악화 0 / 아니요 7
✓ 예, 이것을 줄입니다
예 8 / 악화 0 / 아니요 1
아직 결정 안 됨
아직 결정 안 됨
아직 결정 안 됨
아직 결정 안 됨
Algorithm developers to prioritize viewpoint diversity in the design process. 논의하기✗ 아니요, 줄이지 않습니다
예 2 / 악화 0 / 아니요 7
✓ 예, 이것을 줄입니다
예 7 / 악화 0 / 아니요 2
아직 결정 안 됨
아직 결정 안 됨
아직 결정 안 됨
아직 결정 안 됨
Social media platforms will reshuffle their algorithms to promote diverse viewpoints. 논의하기✗ 아니요, 줄이지 않습니다
예 2 / 악화 0 / 아니요 7
✓ 예, 이것을 줄입니다
예 7 / 악화 0 / 아니요 2
아직 결정 안 됨
아직 결정 안 됨
아직 결정 안 됨
아직 결정 안 됨
Require social media platforms to include a viewpoint-diversity metric in their content ranking algorithms so that exposure to diverse perspectives is weighted alongside engagement metrics. 논의하기✗ 아니요, 줄이지 않습니다
예 2 / 악화 0 / 아니요 7
✓ 예, 이것을 줄입니다
예 7 / 악화 0 / 아니요 2
아직 결정 안 됨
아직 결정 안 됨
아직 결정 안 됨
아직 결정 안 됨
Create an anonymous, opt-in 'Diverse Viewpoint' section in online forums where users can share conflicting views without fear of judgment. 논의하기⚑ 그룹 의견이 갈림
예 5 / 악화 0 / 아니요 4
✗ 아니요, 줄이지 않습니다
예 2 / 악화 0 / 아니요 7
아직 결정 안 됨
아직 결정 안 됨
아직 결정 안 됨
아직 결정 안 됨
Implement a weighting system in algorithms that assigns higher priority to diverse viewpoints to ensure balanced content exposure. 논의하기⚑ 그룹 의견이 갈림
예 3 / 악화 0 / 아니요 7
⚑ 그룹 의견이 갈림
예 7 / 악화 0 / 아니요 3
아직 결정 안 됨
아직 결정 안 됨
아직 결정 안 됨
아직 결정 안 됨
지금까지 가장 효과가 큰 대책
Platforms should update recommendation algorithms to ensure every user feed includes a mandatory quota of high-quality content from opposing viewpoints, decoupled from engagement-based ranking. 근본 원인 6개 중 1개를 줄임
Algorithm developers to prioritize viewpoint diversity in the design process. 근본 원인 6개 중 1개를 줄임
Social media platforms will reshuffle their algorithms to promote diverse viewpoints. 근본 원인 6개 중 1개를 줄임
Require social media platforms to include a viewpoint-diversity metric in their content ranking algorithms so that exposure to diverse perspectives is weighted alongside engagement metrics. 근본 원인 6개 중 1개를 줄임
지도 위의 대책
표시 중: 방이 판정한 모든 대책. 근본 원인 6개 중 1개에 직접 작용합니다. 5개에는 직접 작용하지 않습니다.
대책 단계에서 방이 확정한 칸만 보고 그렸습니다. 초록색 근본 원인은 표시된 대책 중 하나 이상으로 줄어들고, 회색은 어느 대책도 직접 작용하지 않으며, 빨간 테두리는 그중 하나가 더 나빠지게 한다는 뜻입니다.
Algorithms prioritize familiar, agreeable content to keep users spending more time on their platforms. → People feel good when information confirms what they already believe is true.Algorithms prioritize familiar, agreeable content to keep users spending more time on their platforms. → People prefer comfort and familiarity in their information.Algorithms prioritize familiar, agreeable content to keep users spending more time on their platforms. → People feel safe and secure in their own personal information bubbles, shielded from opposing views.Algorithms prioritize familiar, agreeable content to keep users spending more time on their platforms. → People crave confirmation of their existing beliefs.Algorithms prioritize familiar, agreeable content to keep users spending more time on their platforms. → People want to feel validated and avoid cognitive dissonance.Algorithms prioritize familiar, agreeable content to keep users spending more time on their platforms. → They seek comfort and emotional safety by staying in familiar views.Algorithms prioritize familiar, agreeable content to keep users spending more time on their platforms. → They reduce the effort needed to find information that matches personal interests.People feel good when information confirms what they already believe is true. → Algorithms prioritize familiar, agreeable content to keep users spending more time on their platforms.People feel good when information confirms what they already believe is true. → People prefer comfort and familiarity in their information.People feel good when information confirms what they already believe is true. → People feel safe and secure in their own personal information bubbles, shielded from opposing views.People feel good when information confirms what they already believe is true. → People crave confirmation of their existing beliefs.People feel good when information confirms what they already believe is true. → People want to feel validated and avoid cognitive dissonance.People feel good when information confirms what they already believe is true. → They seek comfort and emotional safety by staying in familiar views.People feel good when information confirms what they already believe is true. → They reduce the effort needed to find information that matches personal interests.People prefer comfort and familiarity in their information. → Algorithms prioritize familiar, agreeable content to keep users spending more time on their platforms.People prefer comfort and familiarity in their information. → People feel good when information confirms what they already believe is true.People prefer comfort and familiarity in their information. → People feel safe and secure in their own personal information bubbles, shielded from opposing views.People prefer comfort and familiarity in their information. → People crave confirmation of their existing beliefs.People prefer comfort and familiarity in their information. → People want to feel validated and avoid cognitive dissonance.People prefer comfort and familiarity in their information. → They seek comfort and emotional safety by staying in familiar views.People prefer comfort and familiarity in their information. → They reduce the effort needed to find information that matches personal interests.People crave confirmation of their existing beliefs. → Algorithms prioritize familiar, agreeable content to keep users spending more time on their platforms.People crave confirmation of their existing beliefs. → People feel good when information confirms what they already believe is true.People crave confirmation of their existing beliefs. → People prefer comfort and familiarity in their information.People crave confirmation of their existing beliefs. → People feel safe and secure in their own personal information bubbles, shielded from opposing views.People crave confirmation of their existing beliefs. → People want to feel validated and avoid cognitive dissonance.People crave confirmation of their existing beliefs. → They seek comfort and emotional safety by staying in familiar views.People crave confirmation of their existing beliefs. → They reduce the effort needed to find information that matches personal interests.People want to feel validated and avoid cognitive dissonance. → Algorithms prioritize familiar, agreeable content to keep users spending more time on their platforms.People want to feel validated and avoid cognitive dissonance. → People feel good when information confirms what they already believe is true.People want to feel validated and avoid cognitive dissonance. → People prefer comfort and familiarity in their information.People want to feel validated and avoid cognitive dissonance. → People feel safe and secure in their own personal information bubbles, shielded from opposing views.People want to feel validated and avoid cognitive dissonance. → People crave confirmation of their existing beliefs.People want to feel validated and avoid cognitive dissonance. → They seek comfort and emotional safety by staying in familiar views.People want to feel validated and avoid cognitive dissonance. → They reduce the effort needed to find information that matches personal interests.Algorithms prioritize engagement over diverse viewpoints. → Algorithms prioritize familiar, agreeable content to keep users spending more time on their platforms.Algorithms prioritize engagement over diverse viewpoints. → People feel good when information confirms what they already believe is true.Algorithms prioritize engagement over diverse viewpoints. → People prefer comfort and familiarity in their information.Algorithms prioritize engagement over diverse viewpoints. → People crave confirmation of their existing beliefs.Algorithms prioritize engagement over diverse viewpoints. → People want to feel validated and avoid cognitive dissonance.Algorithms prioritize engagement over diverse viewpoints. → They seek comfort and emotional safety by staying in familiar views.Algorithms prioritize engagement over diverse viewpoints. → They reduce the effort needed to find information that matches personal interests.They seek comfort and emotional safety by staying in familiar views. → Algorithms prioritize familiar, agreeable content to keep users spending more time on their platforms.They seek comfort and emotional safety by staying in familiar views. → People feel good when information confirms what they already believe is true.They seek comfort and emotional safety by staying in familiar views. → People prefer comfort and familiarity in their information.They seek comfort and emotional safety by staying in familiar views. → People feel safe and secure in their own personal information bubbles, shielded from opposing views.They seek comfort and emotional safety by staying in familiar views. → People crave confirmation of their existing beliefs.They seek comfort and emotional safety by staying in familiar views. → People want to feel validated and avoid cognitive dissonance.They seek comfort and emotional safety by staying in familiar views. → They reduce the effort needed to find information that matches personal interests.They reduce the effort needed to find information that matches personal interests. → Algorithms prioritize familiar, agreeable content to keep users spending more time on their platforms.They reduce the effort needed to find information that matches personal interests. → People feel good when information confirms what they already believe is true.They reduce the effort needed to find information that matches personal interests. → People prefer comfort and familiarity in their information.They reduce the effort needed to find information that matches personal interests. → People feel safe and secure in their own personal information bubbles, shielded from opposing views.They reduce the effort needed to find information that matches personal interests. → People crave confirmation of their existing beliefs.They reduce the effort needed to find information that matches personal interests. → People want to feel validated and avoid cognitive dissonance.They reduce the effort needed to find information that matches personal interests. → They seek comfort and emotional safety by staying in familiar views.People want to avoid conflicting views to feel more comfortable. → Algorithms prioritize familiar, agreeable content to keep users spending more time on their platforms.People want to avoid conflicting views to feel more comfortable. → People feel good when information confirms what they already believe is true.People want to avoid conflicting views to feel more comfortable. → People prefer comfort and familiarity in their information.People want to avoid conflicting views to feel more comfortable. → People crave confirmation of their existing beliefs.People want to avoid conflicting views to feel more comfortable. → People want to feel validated and avoid cognitive dissonance.People want to avoid conflicting views to feel more comfortable. → They seek comfort and emotional safety by staying in familiar views.People want to avoid conflicting views to feel more comfortable. → They reduce the effort needed to find information that matches personal interests.People feel safe and secure in their own personal information bubbles, shielded from opposing views. → Algorithms prioritize engagement over diverse viewpoints.People want to avoid conflicting views to feel more comfortable. → Algorithms prioritize engagement over diverse viewpoints.They seek comfort and emotional safety by staying in familiar views. → Algorithms prioritize engagement over diverse viewpoints.Algorithms prioritize engagement over diverse viewpoints. ① Platforms should update recommendation algorithms to ensure every user feed includes a mandatory quota of high-quality content from opposing viewpoints, decoupled from engagement-based ranking. ② Algorithm developers to prioritize viewpoint diversity in the design process. ③ Social media platforms will reshuffle their algorithms to promote diverse viewpoints. ④ Require social media platforms to include a viewpoint-diversity metric in their content ranking algorithms so that exposure to diverse perspectives is weighted alongside engagement metrics.Algorithms prioritizeengagement over diverseviewpoints.①②③④표시된 대책이 이 근본 원인에 미치는 영향대책 4개로 줄어듦People want to avoid conflicting views to feel more comfortable.People want to avoidconflicting views to feelmore comfortable.표시된 대책이 이 근본 원인에 미치는 영향직접 작용하는 대책 없음Algorithms prioritize familiar, agreeable content to keep users spending more time on their platforms.Algorithms prioritizefamiliar, agreeable contentto keep users spending moretime on their platforms.되먹임 고리의 일부⟳People crave confirmation of their existing beliefs.People crave confirmationof their existing beliefs.되먹임 고리의 일부⟳표시된 대책이 이 근본 원인에 미치는 영향직접 작용하는 대책 없음People feel good when information confirms what they already believe is true.People feel good wheninformation confirms whatthey already believe istrue.되먹임 고리의 일부⟳표시된 대책이 이 근본 원인에 미치는 영향직접 작용하는 대책 없음People prefer comfort and familiarity in their information.People prefer comfort andfamiliarity in theirinformation.되먹임 고리의 일부⟳표시된 대책이 이 근본 원인에 미치는 영향직접 작용하는 대책 없음People want to feel validated and avoid cognitive dissonance.People want to feelvalidated and avoidcognitive dissonance.되먹임 고리의 일부⟳They reduce the effort needed to find information that matches personal interests.They reduce the effortneeded to find informationthat matches personalinterests.되먹임 고리의 일부⟳They seek comfort and emotional safety by staying in familiar views.They seek comfort andemotional safety by stayingin familiar views.되먹임 고리의 일부⟳표시된 대책이 이 근본 원인에 미치는 영향직접 작용하는 대책 없음People feel safe and secure in their own personal information bubbles, shielded from opposing views.People feel safe and securein their own personalinformation bubbles,shielded from opposingviews.
지도의 각 번호는 그 대책이 줄이는 근본 원인을 표시합니다.
① Platforms should update recommendation algorithms to ensure every user feed includes a mandatory quota of high-quality content from opposing viewpoints, decoupled from engagement-based ranking.
② Algorithm developers to prioritize viewpoint diversity in the design process.
③ Social media platforms will reshuffle their algorithms to promote diverse viewpoints.
④ Require social media platforms to include a viewpoint-diversity metric in their content ranking algorithms so that exposure to diverse perspectives is weighted alongside engagement metrics.
⑤ Create an anonymous, opt-in 'Diverse Viewpoint' section in online forums where users can share conflicting views without fear of judgment.
⑥ Implement a weighting system in algorithms that assigns higher priority to diverse viewpoints to ensure balanced content exposure.
대책에서 계획으로
격자에서는 대책을 하나씩 따로 판정했습니다. 계획은 방이 함께 실행할 대책들의 모음입니다.
멤버들은 근본 원인을 줄이는 대책으로 계획을 짜고, 방은 다른 모든 것을 판정할 때처럼 던진 표의 4분의 3을 기준으로 계획을 두 개씩 비교합니다. 각 계획에는 어떤 근본 원인에 직접 작용하는지, 어떤 것에는 그렇지 않은지, 어떤 것을 더 나빠지게 하는지가 표시됩니다.
진행자가 계획 비교를 열 수 있습니다.