<
Personal insights
User experience
名站套图
克拉女神
头条女神
头条女神合集
Robots and digital humans
A2: Although it is generally believed that the explanatory nature of the model helps to improve user trust, the experimental results show that this enhancement is not significant and not as effective as feedback. In specific cases, such as areas of low expertise, some form of interpretation may result in only a modest increase in appropriate trust.
舞蹈生日记
艺图语
The results show that feedback has a more significant impact on improving users' trust in AI than explainability, but this enhanced trust does not lead to a corresponding performance improvement. Further exploration suggests that feedback induces users to over-trust (i.e., accept the AI's suggestions when it is wrong) or distrust (ignore the AI's suggestions when it is correct), which may negate the benefits of increased trust, leading to a "trust-performance paradox". The researchers call for future research to focus on how to design strategies to ensure that explanations foster appropriate trust to improve the efficiency of human-robot collaboration.
青豆客
秀人系列
秀人网
A1: According to research, feedback (e.g. result output) is a key factor influencing user trust. It is the most significant and reliable way to increase user trust in AI behavior.
The Interpretability of Artificial Intelligence and the Impact of Outcome Feedback on Trust: A Comparative Study | Xue Zhirong's knowledge base
Xue Zhirong is a designer, engineer, and author of several books; Founder of the Design Open Source Community, Co-founder of MiX Copilot; Committed to making the world a better place with design and technology. This knowledge base will update AI, HCI and other content, including news, papers, presentations, sharing, etc.
Xue Zhirong's knowledge base
The researchers conducted two sets of experiments ("Predict the speed-dating outcomes and get up to $6 (takes less than 20 min)" and a similar Prolific experiment) in which participants interacted with the AI system in a task of predicting the outcome of a dating to explore the impact of model explainability and feedback on user trust in AI and prediction accuracy. The results show that although explainability (e.g., global and local interpretation) does not significantly improve trust, feedback can most consistently and significantly improve behavioral trust. However, increased trust does not necessarily lead to the same level of performance gains, i.e., there is a "trust-performance paradox". Exploratory analysis reveals the mechanisms behind this phenomenon.
To assess trust more accurately, the researchers used behavioral trust (WoA), a measure that takes into account the difference between the user's predictions and the AI's recommendations, and is independent of the model's accuracy. By comparing WoA under different conditions, researchers can analyze the relationship between trust and performance.
Original address:
模范学院
糖果画报
花の颜
Conference
蜜桃社
语画界
魅妍社
薄荷叶
二次元专区
二次元目录
神楽坂真冬
blog
Kitaro_绮太郎
Cien恩恩
izumi泉桃子
Tina很妖孽呀
w百合欧皇子w
喵喵的喵吖
喵糖映画
安食Ajiki
文章资讯
是一只熊仔吗
森萝财团
Q2: Does explainability necessarily enhance users' trust in AI?
Chinese Traditional
贝儿酱Miki
雪琪SAMA
风之领域
香草喵露露
小容仔咕咕咕w
苏嫣嫣阿姨
沧霁桔梗
芋圆侑子
小和甜酒
NinJa阿寨寨
Xue Zhirong, Designer, Interaction Design, Human-Computer Interaction, Artificial Intelligence, Official Website, Blog, Creator, Author, Engineer, Paper, Product Design, Research, AI, HCI, Design, Learning, Knowledge Base, xuezhirong, UX, Design, Research, AI, HCI, Designer, Engineer, Author, Blog, Papers, Product Design, Study, Learning, User Experience
AISS爱丝
高丝女子图鉴
梦丝女神
MIT Licensed | Copyright © 2024-present Zhirong Xue's knowledge base
网红Coser
The researchers found that although it is generally believed that the interpretability of the model can help improve the user's trust in the AI system, in the actual experiment, the global and local interpretability does not lead to a stable and significant trust improvement. Conversely, feedback (i.e., the output of the results) has a more significant effect on increasing user trust in the AI. However, this increased trust does not directly translate into an equivalent improvement in performance.
就是阿朱啊
合集打包
合集下载
丝模合集
二次元合集
名站套图合集
秀人系列合集
VIP介绍
永久地址
Q3: How does result feedback and model interpretability affect user task performance?
解压说明
开通会员
开通赞助会员
解锁浏览全部图片
推广代理佣金30%
客服QQ927022719
若支付后未开通请联系客服
开通赞助会员
开通钻石会员
解锁浏览全部图片
全站资源免费下载
推广代理佣金50%
客服QQ927022719
若支付后未开通请联系客服
开通钻石会员
简体中文
English
日本語
한국어
Việt Nam
About me
Translation
Personal insights
User experience
名站套图
克拉女神
头条女神
Robots and digital humans
A2: Although it is generally believed that the explanatory nature of the model helps to improve user trust, the experimental results show that this enhancement is not significant and not as effective as feedback. In specific cases, such as areas of low expertise, some form of interpretation may result in only a modest increase in appropriate trust.
舞蹈生日记
艺图语
The results show that feedback has a more significant impact on improving users' trust in AI than explainability, but this enhanced trust does not lead to a corresponding performance improvement. Further exploration suggests that feedback induces users to over-trust (i.e., accept the AI's suggestions when it is wrong) or distrust (ignore the AI's suggestions when it is correct), which may negate the benefits of increased trust, leading to a "trust-performance paradox". The researchers call for future research to focus on how to design strategies to ensure that explanations foster appropriate trust to improve the efficiency of human-robot collaboration.
青豆客
秀人系列
秀人网
A1: According to research, feedback (e.g. result output) is a key factor influencing user trust. It is the most significant and reliable way to increase user trust in AI behavior.
The Interpretability of Artificial Intelligence and the Impact of Outcome Feedback on Trust: A Comparative Study | Xue Zhirong's knowledge base
Xue Zhirong is a designer, engineer, and author of several books; Founder of the Design Open Source Community, Co-founder of MiX Copilot; Committed to making the world a better place with design and technology. This knowledge base will update AI, HCI and other content, including news, papers, presentations, sharing, etc.
Xue Zhirong's knowledge base
The researchers conducted two sets of experiments ("Predict the speed-dating outcomes and get up to $6 (takes less than 20 min)" and a similar Prolific experiment) in which participants interacted with the AI system in a task of predicting the outcome of a dating to explore the impact of model explainability and feedback on user trust in AI and prediction accuracy. The results show that although explainability (e.g., global and local interpretation) does not significantly improve trust, feedback can most consistently and significantly improve behavioral trust. However, increased trust does not necessarily lead to the same level of performance gains, i.e., there is a "trust-performance paradox". Exploratory analysis reveals the mechanisms behind this phenomenon.
To assess trust more accurately, the researchers used behavioral trust (WoA), a measure that takes into account the difference between the user's predictions and the AI's recommendations, and is independent of the model's accuracy. By comparing WoA under different conditions, researchers can analyze the relationship between trust and performance.
Original address:
模范学院
糖果画报
花の颜
Conference
蜜桃社
语画界
魅妍社
薄荷叶
二次元专区
二次元目录
神楽坂真冬
blog
Kitaro_绮太郎
Cien恩恩
izumi泉桃子
Tina很妖孽呀
w百合欧皇子w
喵喵的喵吖
喵糖映画
安食Ajiki
文章资讯
是一只熊仔吗
森萝财团
Q2: Does explainability necessarily enhance users' trust in AI?
Chinese Traditional
贝儿酱Miki
雪琪SAMA
风之领域
香草喵露露
小容仔咕咕咕w
苏嫣嫣阿姨
沧霁桔梗
芋圆侑子
小和甜酒
NinJa阿寨寨
Xue Zhirong, Designer, Interaction Design, Human-Computer Interaction, Artificial Intelligence, Official Website, Blog, Creator, Author, Engineer, Paper, Product Design, Research, AI, HCI, Design, Learning, Knowledge Base, xuezhirong, UX, Design, Research, AI, HCI, Designer, Engineer, Author, Blog, Papers, Product Design, Study, Learning, User Experience
AISS爱丝
高丝女子图鉴
梦丝女神
MIT Licensed | Copyright © 2024-present Zhirong Xue's knowledge base
网红Coser
The researchers found that although it is generally believed that the interpretability of the model can help improve the user's trust in the AI system, in the actual experiment, the global and local interpretability does not lead to a stable and significant trust improvement. Conversely, feedback (i.e., the output of the results) has a more significant effect on increasing user trust in the AI. However, this increased trust does not directly translate into an equivalent improvement in performance.
就是阿朱啊
合集打包
合集下载
丝模合集
二次元合集
名站套图合集
秀人系列合集
VIP介绍
永久地址
Q3: How does result feedback and model interpretability affect user task performance?
解压说明
开通会员 尊享会员权益
About me
Translation
找回密码
性感女郎
Interactive
summary
outcome
thesis
Interview
The Interpretability of Artificial Intelligence and the Impact of Outcome Feedback on Trust: A Comparative Study
[TouTiao头条女神]2019.11.18 性感女郎王紫琳[20P／27.1MB]
头条女神
Dissertation Summary
1.1W+
703
Q1: How does feedback affect users' trust in AI?
speech
蠢沫沫
神楽坂真冬
杨晨晨sugar
artificial intelligence
ElyEE子
Based on large language model generation, there may be a risk of errors.
interview
就是阿朱啊
奈汐酱nice
The Interpretability of Artificial Intelligence and the Impact of Outcome Feedback on Trust: A Comparative Study
Draw inferences
合集下载
Chinese Traditional
Misamisaaa_a
芝芝Booty
香草喵露露
模特合集
左公子666
柳侑绮Sevenbaby
Momoko葵葵
Problem finding
The content is made up of:
Natsuko夏夏子
tool
是三不是世w
大大卷卷小卷
许岚LAN
solution
A3: The study found that the feedback of the results can improve the accuracy of the user's predictions (reducing the absolute error), thereby improving the performance of working with AI. However, interpretability does not have as much impact on user task performance as it does on trust. This may mean that we should pay more attention to how to effectively use feedback mechanisms to improve the usefulness and effectiveness of AI-assisted decision-making.
徐莉芝Booty
在手机上浏览此页面
点击任意地方关闭
About me
没有账号？立即注册
用户名或邮箱
登录密码
记住登录
找回密码
About me
Translation
已有账号，立即登录
设置用户名
设置密码
重复密码
Translation
点击任意地方关闭
秀女吧，请君欣赏
一个专业欣赏美图的网站
开通赞助会员，全站美图即可在线浏览
开通永久VIP即可全站原图下载
推荐都使用 Edge、Chrome浏览器
www.xiunvb.com
УкраїнськаName
Norge
color name
nederlands
しろうと
Pilipino
English
ກະຣຸນາ
తెలుగుQFontDatabase
Română
नेपालीName
Français
Kreyòl ayisyen
český
Svenska
Русский язык
Malagasy
ဗာရမ်
پښتوName
คนไทย
Արմենյան
简体中文
Persian
繁體中文
Kurdî
Türkçe
हिन्दी
български
Malay
Kiswahili
ଓଡିଆ
ÍslandName
Íris
ខ្មែរKCharselect unicode block name
ગુજરાતી
Slovenská
ಕನ್ನಡ್Name
היברית
magyar
मराठीName
தாமில்
eesti keel
മലമാലം
ᐃᓄᒃᑎᑐᑦ
بالعربية
Deutsch
slovenščina
বেঙ্গালী
اوردو
azerbaijani
português
lifiava
afrikaans
汤加语
ελληνικά
IndonesiaName
Español
dansk
amharic
ਪੰਜਾਬੀName
albanian
Lietuva
italiano
Tiếng Việt
한국어
Malti
suomi
català
hrvatski
bosnian
Polski
latviešu
Maori
支付宝
微信支付
￥
正在生成订单，请稍候
![[TouTiao头条女神]2019.11.18 性感女郎王紫琳[20P／27.1MB]-秀女吧 XIUNVB.COM](https://www.xiunvb.com/wp-content/uploads/2024/08/20240809154836952-803_001_qv0_1600_2400.webp)
