Social Media Clones: Exploring the Impact of Social Delegation with AI Clones through a Design Workbook Study
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866908527332687872 |
|---|---|
| author | Liu, Jackie Shirvani, Mehrnoosh Sadat Hong, Hwajung Kim, Ig-Jae Yoon, Dongwook |
| author_facet | Liu, Jackie Shirvani, Mehrnoosh Sadat Hong, Hwajung Kim, Ig-Jae Yoon, Dongwook |
| contents | Social media clones are AI-powered social delegates of ourselves created using our personal data. As our identities and online personas intertwine, these technologies have the potential to greatly enhance our social media experience. If mismanaged, however, these clones may also pose new risks to our social reputation and online relationships. To set the foundation for a productive and responsible integration, we set out to understand how social media clones will impact our online behavior and interactions. We conducted a series of semi-structured interviews introducing eight speculative clone concepts to 32 social media users through a design workbook. Applying existing work in AI-mediated communication in the context of social media, we found that although clones can offer convenience and comfort, they can also threaten the user's authenticity and increase skepticism within the online community. As a result, users tend to behave more like their clones to mitigate discrepancies and interaction breakdowns. These findings are discussed through the lens of past literature in identity and impression management to highlight challenges in the adoption of social media clones by the general public, and propose design considerations for their successful integration into social media platforms. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_07502 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Social Media Clones: Exploring the Impact of Social Delegation with AI Clones through a Design Workbook Study Liu, Jackie Shirvani, Mehrnoosh Sadat Hong, Hwajung Kim, Ig-Jae Yoon, Dongwook Human-Computer Interaction Social media clones are AI-powered social delegates of ourselves created using our personal data. As our identities and online personas intertwine, these technologies have the potential to greatly enhance our social media experience. If mismanaged, however, these clones may also pose new risks to our social reputation and online relationships. To set the foundation for a productive and responsible integration, we set out to understand how social media clones will impact our online behavior and interactions. We conducted a series of semi-structured interviews introducing eight speculative clone concepts to 32 social media users through a design workbook. Applying existing work in AI-mediated communication in the context of social media, we found that although clones can offer convenience and comfort, they can also threaten the user's authenticity and increase skepticism within the online community. As a result, users tend to behave more like their clones to mitigate discrepancies and interaction breakdowns. These findings are discussed through the lens of past literature in identity and impression management to highlight challenges in the adoption of social media clones by the general public, and propose design considerations for their successful integration into social media platforms. |
| title | Social Media Clones: Exploring the Impact of Social Delegation with AI Clones through a Design Workbook Study |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2509.07502 |