Conclusion

Survey results from 900 college students across universities in the Northern, Western, Southern and Eastern parts of Taiwan highlights the concern among young adults regarding environmental degradation. However, my survey results acknowledges the barriers these individuals face, including a lack of tools and clear information, which hinders their ability to contribute effectively to environmental sustainability.

Their preferences and attitudes.

In interaction design, it doesn’t matter how the system works in the background. What’s important is understanding the mental model, the user has of the system and tuning the design to fit that model.

College students are concerned with environmental issues but lack tools to affect systemic change. This research introduces an AI companion to help young adults engage in sustainable shopping, saving, and investing.

College students can set their Intention and the AI companion can help them fulfill that intention in a variety of financial situation from shopping to saving and investing.

“enabling data-driven decision making”

When will Bolt show CO2e emissions per every trip?

Sustainable finance data platform:

As long as humanity is a mono-planetary species, we have to come to terms with the limitations of our home, Earth, which is becoming increasingly urbanized.

“The study employed a mixed-methods approach, starting with a , followed by . A survey of 900 college students across 21 universities in Taiwan was then conducted to understand . The major contribution is the interactive AI-assistant prototype, informed by the design research findings.

Prototype informed by design research aims to empower young adults to make informed decisions that align with their environmental values, whether through sustainable shopping, saving, or investing.

In-person face-to-face testing with 32 students at 7 universities provided additional changed in the app design. It allowed to better understand the struggles students face with technology: old laptops, slow wi-fi, lack of power plugs and dieing batteries.

Foster environmental stewardship through financial activism.

Finding green products and supporting companies making them

Supporting legislative changes

Track you consumption, saving, investing. Shift balance towards saving and investing.

mixed-methods

Designing AI systems that are capable of translating complex environmental data into actionable insights.

In conclusion, this research addresses the need for convenient tools to enable college students to take sustainable financial actions in their daily lives. By leveraging advancements in AI and data-driven interaction design, the proposed AI companion aims to act as a translation layer between complex environmental data and human-comprehensible language. The prototype demonstrates how thoughtful design can empower the next generation to align their consumption and investment behaviors with their concern for the environment, driving positive change through their financial choices.”

Drive companies to be more transparent with ESG data

Increase ESG accessibility

RQ1: What design considerations should be addressed when designing an AI companion for college students integrating sustainability and finance?

From Literature Review, User Survey, Expert Interviews, and User Testing the Prototype.

A comprehensive literature review in the interconnected economic behavior and ecological sustainability underscores the critical role that financial decisions play in impacting the planet’s health.

Design for Visibility & Simplicity Testers often overlooked the AI analysis feature, thinking it was part of the website, not a 3rd party service. The interface must make key actions obvious. Use prominent announcements to announce new features (e.g. a pop‐up tour highlighting what’s new). Minimize extra clicks: as one expert (Huang) noted, “people are lazy… if it’s easier to get the information that I don’t have to click a button, I will pay attention”. In short, design a streamlined UI with clear one-step interactions and in-context prompts.

Design for Intuitive Visuals & Feedback Replace dense text with clear graphics and simple ratings. Huang observed that users tune out long reports but immediately grasp an icon or “eco score” (e.g. a polar bear or 0–100 scale). Similarly, testers noticed numeric eco-scores more than textual features. Thus, represent sustainability metrics as concise visuals or scores, with brief tooltips explaining meaning.

Design for Engaging Tone & Fun Elements Use approachable language and interactive cues. Experts advised avoiding jargon: e.g. change button text from “Continue discussion” to a playful prompt to spark curiosity and intriguing to capture user interest. Gamification (e.g. progress bars, “unlocking” sustainable tips) may sustain engagement, given users’ limited patience for lengthy explanations.

Design for Trust and Transparency Students expressed moderate trust in AI (survey results show many neutral-to-skeptical responses). To build credibility, the companion must cite verifiable data (certifications, carbon labels, etc.) rather than vague claims. For example, testers distrusted offsetting alone (“I still feel like I’m not really doing it right” when just buying carbon credits.), so the app should provide concrete evidence of impact. Avoid taking ESG scores at face value – include context (e.g. B Corp or supply-chain data) as advised by literature. In practice, feature designs should highlight third-party credentials (green certifications) and explain methodology to counter skepticism.

Design Mobile-First For technical reasons the prototype testing was done using laptop computers (Apple does not allow adding 3rd party overlays on iOS apps the same way Google allows with Chrome Browser Extensions). However, given 96% of students use smartphones (majority iOS), mobile-first is a must, even given all the technical limitations. The design should favor a mobile app or browser extension that integrates with their existing shopping/payment tools. Survey clustering suggests leveraging daily habits (shopping/savings apps) as entry points. Ensure compatibility (notably, iOS imposes browser restrictions) and consider platform-specific design (e.g. integrating with Momo app interface as envisioned). Shopee was consistenly mentioned by testers and could serve for the next round of testing instead of Momo.

RQ2: How can AI companions support college students with sustainability knowledge in the context of financial decisions?

From Literature Review, User Survey, Expert Interviews, and User Testing the Prototype.

Contextualized Information at Point-of-Decision Embed sustainability data into shopping and investment flows. In prototype testing, participants valued seeing hidden product info (ingredients, manufacturing “history”) that they normally don’t encounter. For example, revealing that a facial mask contained problematic chemicals led a student to switch to an aloe-based alternative. This suggests the AI should surface concise ecological/health facts (e.g. “contains X chemical linked to…”) whenever users view a product. Similarly, in the investment context the AI showed company ESG scores and stock info. Users reacted positively: one noted, “Buying things is also an investment… I can help you analyze if the money spent is good or bad”. Thus, frame purchases as “investments” in sustainable companies to link finance and ecology.

Sustainable Alternatives and Comparisons Provide actionable recommendations. Testers frequently clicked a “Find Alternatives” feature, and Cathy Wang confirms that students want alerts on “the most dangerous products” to avoid. Accordingly, the companion should automatically flag high-impact products in the user’s list and suggest greener options or categories. In finance mode, it should compare companies’ performance (e.g. “Company X is high-ESG, Company Y is not”) so students can weigh investment choices. Survey data underscores this: roughly one-third of respondents want pre-investment checks of company eco-credentials (31% for certifications, 26% for consumer reviews) and comparisons (26%) of environmental performance. The AI can fulfill these by summarizing third-party eco-reports or consumer sentiments on companies.

Personal Sustainability Dashboard Many students expressed interest in tracking their own impact (25% wanted a monthly “eco-score” of spending). Building on this, the app can maintain a simple personal report (e.g. “Your spending this month saved X kg CO₂” or “you’re now 20% greener”). This aligns with providing “carbon score” feedback that testers noticed. The dashboard should be succinct, using visuals (progress bars, infographics) rather than verbose text, so students quickly grasp progress (Huang’s scale idea).

Educational Nudges & Explanations Use the AI chat (or chat-like prompts) to elaborate on sustainability concepts as needed. Although few testers clicked the “Chat with AI” button during prototyping, it can serve as a fallback for curious users. For example, when a student sees a product’s green score, they could ask “Why?” and the AI could briefly explain (“This brand was rated low because it uses high-carbon packaging”, sort of like in ther earliest prototype). Encouraging exploration without overwhelming users aligns with Audrey Tang’s insight that youth are eager to engage but need clear, relatable contexts (e.g. connecting a bubble-tea straw ban to personal habits). Overall, the AI should act as an informed guide: contextualizing data, answering “what-if” questions, and helping students internalize how their financial choices affect sustainability.

RQ3: What AI companion features do college students prioritize as the highest?

From User Survey, Expert Interviews, and User Testing the Prototype.

Eco-Impact Product Filters: The highest-priority feature is product-level sustainability comparison. In the survey, 63% of students wanted to “see which products are most polluting so I can avoid them,”” far above other categories. This aligns with testing observations: Cathy notes “the main feature…was to avoid the most…dangerous products” via an alert on the shopping list. Accordingly, the companion should prominently offer “sustainability filters” (e.g. sort products by carbon footprint or toxin content) and alternative suggestions, just as users clicked the “Find Alternatives” button in our prototype.

Supply Chain Transparency: Other top features relate to sourcing. About 41% of respondents want to check product origin (e.g. local vs. imported) and 40% want to know how eco-friendly the production process is. Designing a simple icon or tag for “local” or “certified eco-friendly factory” (as Chen‑Ying Huang recommends using recognizable symbols) would meet these needs. Similarly, one-third favored an “organic” product search. The prototype’s green-colored “Analysis” tab (showing carbon emissions by product type) was also used by testers, indicating interest in seeing how choices impact emissions cumulatively.

Personal Eco-Score and History: A quarter of students (25%) expressed interest in a monthly report of their own eco-score. In testing, participants took screenshots of the carbon-reduction analysis, suggesting value in recording progress. We should include a lightweight “eco-dashboard” feature: an overview of past decisions, scores, and tips. Crucially, it must be eye-catching and concise (e.g. a single visual per month) so students will actually review it.

Sustainable Investing: Many students expect the AI to support green investing. Roughly 26–32% of respondents wanted to see company eco-scores, certifications, or performance comparisons before investing. Testers saw company ESG ratings and stock info (they asked “what is this company’s stock code?”) and even got recommendations for similar sustainable companies. Thus, the feature set should include an investment tab with clear “sustainability ratings” for companies alongside stock data, and suggestions of alternative stocks aligned with the student’s values.

Lower-Priority Features Give the high usage of social media in Taiwan, I was surpised community-related and social features ranked low in the survey. Only around 12% of the respondents wanted social networking with eco-peers, and indeed testers rarely engaged even with the AI’s chat option to ask more questions. These findings suggest focusing development effort on concrete decision aids (filtering, scoring, recommendations) rather than social networking or open-ended chat.

Final Takeaway

I have integrated quantitative survey trends with qualitative insights from testing and interviews. For instance, strong survey interest in product comparisons (63%) is consistent with testers clicking the “Find Alternatives” feature and experts (Huang, Wang) emphasizing clear eco-indicators. By aligning the AI companion’s design closely with the above patterns: favoring concise visual info, high discoverability of features, and actionable eco-insights, I can better meet student needs, providing sustainable financial decision support exactly at the right context and the right time.

Even if college students don’t have enough money to affect companies directly, they can demand financial tools work better (higher baseline for sustainability) to galvanize and encourage institutional investment into sustainability and encreasing ESG accessibility. Influencing business governance is the main point of leverage. G->S->E, not E->S->G. Aggregating Consumer Demand, Amplifying Consumer Influence, Enhancing Market Standards. Design is Political Action, Eco-Design Democratizes ESG Accessibility.