iiinova — where your digital self keeps evolving

Simona Liao @simonaliao.bsky.social · 08/01/2026

LOL are you taking a CHID class this quarter? 👀

Simona Liao @simonaliao.bsky.social · 22/10/2025

If you are at CSCW 2025, come check out my work this morning! I will present in Salong Nina room on Level 3 during the 9-10:30 session. :)

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Simona Liao @simonaliao.bsky.social · 18/10/2025

Finally, many thanks to my advisor @axz.bsky.social 💖 and @socialfutureslab.bsky.social for all the guidance and support, to the second author Evan (Hanwen) 👨🏻‍💻 who is a VR expert, and to UW Reality Lab for the VR devices 🕹️!

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Simona Liao @simonaliao.bsky.social · 18/10/2025

3 (continued) instead of automating the process for convenience, which could be a potential pitfall for proactive protection.

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Simona Liao @simonaliao.bsky.social · 18/10/2025

3. Safety needs are dynamic and can sometimes be contradictory, both between players and even for the same player over time. Thus, features should (1) focus on supporting players in making choices and (2) provide players with multiple ways to make that choice effortlessly.

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Simona Liao @simonaliao.bsky.social · 18/10/2025

2. Safety features should center marginalized players’(those with higher risks of encountering harassment) experiences and not conflict with the existing safety practices they have developed.

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Simona Liao @simonaliao.bsky.social · 18/10/2025

1. Proactive safety features could improve overall social and gaming experiences. Even experienced players not concerned about harassment praised these features, highlighting the potential for safety designs to enhance general gameplay, moving away from solely damage-focused.

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Simona Liao @simonaliao.bsky.social · 18/10/2025

Three key takeaways for designing future proactive and instant reactive strategies✍🏼

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Simona Liao @simonaliao.bsky.social · 18/10/2025

Puffer 🐡 is our safety system prototype, including four proactive and instant-reactive features, and built with Meta XR All-in-One SDK. See our prototype demo video: youtu.be/Nr-X7fps2xc

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Simona Liao @simonaliao.bsky.social · 18/10/2025

3. We empowered bystanders to intervene in harassment, since they are more accessible than moderators. Lowering the barrier to intervene fosters mutual support and encourages positive player behaviors. 👭

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Simona Liao @simonaliao.bsky.social · 18/10/2025

2. We sought to clarify the ambiguous social norms in VR, making it easier for players to understand how to interact with one another appropriately.

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Simona Liao @simonaliao.bsky.social · 18/10/2025

We explored three approaches: 1. We improved the design of personal bubble, an existing proactive safety feature available in most social VR games. We made it more usable, learnable, and context-aware.

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Simona Liao @simonaliao.bsky.social · 18/10/2025

Embodied harassment is also harder to remedy with delayed reactive strategies that respond only after the incident occurred (e.g, reporting) How can we create more proactive and instant reactive strategies that prevent harassment or stop it immediately, to reduce its damage? 🤔

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Simona Liao @simonaliao.bsky.social · 18/10/2025

Excited to share my first research paper on social virtual reality✨🎮 (for #cscw2025 )! Social VR provides an immersive gaming experience that builds closer relationships. However, this same immersiveness also makes embodied harassment in social VR more traumatizing :(

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Simona Liao @simonaliao.bsky.social · 04/12/2024

Thanks for your question, Sung! Here is a pie chart representing the racial identities of non-native English speakers. White folks take up ~50% (most are from European countries) followed up by ~20% Asian folks

Pie chart representing the racial groups, with count in brackets
51.4% White/Caucasian (127)
17.8% Asian (44)
8.9% Prefer not to disclose (22)
8.1% Prefer to self-describe (20)
8.1% Hispanic and Latino (20)
3.6% Black or African American (9)
2.0% Middle Eastern (5)

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Simona Liao @simonaliao.bsky.social · 02/12/2024

5. Researchers in computer science fields are more comfortable disclosing their LLM usage and have lower ethical concerns compared to researchers in other disciplines (see fig 4).

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Simona Liao @simonaliao.bsky.social · 02/12/2024

4. Women and non-binary researchers have greater ethical concerns, as do those with more years of research experience (see fig 4).

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Simona Liao @simonaliao.bsky.social · 02/12/2024

2. Researchers who are non-White, non-native English speaking, and junior researchers both use LLMs more frequently and also perceive higher benefits and lower risks (see Fig 4). 3. Equity was a large theme in respondents’ discussions of the benefits of LLMs.

Figure 4: A collection of 36 heatmaps. The y-axis or each row represents a demographic breakdown (from top to bottom: Race, Gender, Langauge, Experience, Field of Study, and All participants). Each column, from left to right, represents LLM usage frequency, perception of risk, benefits, ethics, the comfort level of disclosing to peers, and of disclosing to reviewers. For each individual heatmap, the x-axis includes the six types of LLM usage (from left to right, information seeking, editing, ideation & framing, direct writing, data cleaning & analysis, and data generation.).

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Simona Liao @simonaliao.bsky.social · 02/12/2024

Our Key Takeaways: 1. 81% of researchers we surveyed have used LLMs in one or more places in their research pipeline, with the tasks of Information Seeking and Editing reported most frequently and Data Analysis and Generation reported least frequently (see fig 2).

Fig 2: Overview of Usage Frequency Divided by LLM Usage Type (N=816). The left diverging bar chart displays the distribution
of usage frequency across different types of LLM usage, with each type represented by a separate row. The frequency levels, from left to right, are: Very Rarely, Rarely, Occasionally, Frequently, and Very Frequently, with the midpoint of the chart centered at "Occasionally."
The grey bar chart on the right indicates the percentage of responses that report "Never" using LLMs for each corresponding type. From this plot, we can tell that researchers report using LLMs for Information Seeking and Editing most frequently, and for Data
Cleaning & Analysis and Data Generation the least frequently.

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Simona Liao @simonaliao.bsky.social · 02/12/2024

Hi everyone, I am excited to share our large-scale survey study with 800+ researchers, which reveals researchers’ usage and perceptions of LLMs as research tools, and how the usage and perceptions differ based on demographics. See results in comments! 🔗 Arxiv link: arxiv.org/abs/2411.05025

arxiv.org

LLMs as Research Tools: A Large Scale Survey of Researchers' Usage and Perceptions

The rise of large language models (LLMs) has led many researchers to consider their usage for scientific work. Some have found benefits using LLMs to augment or automate aspects of their research pipe...

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