To improve our communication skills as designers, we’ve been tasked to go through an entire client process from brief to deliverables. This is helpful not only for us to see the entire design process from start to finish, but it also provides us with another opportunity to externalize the value of our work and the methods we employ. To get started, we were given a 2-page document that outlined the business situation and landscape, project objective, and challenge for a design project for the University of Texas system.
After researching more into competency-based learning, the foundation of the project, we were tasked with creating a project brief. The goal of this brief is to provide a jumping-off point for working with our client, the UT system.
The brief should include:
The purpose of the work: the business situation that drives the need for the work
The outcomes: the desired effect of the work and how success will be measured
The problem to be solved: a problem statement that succinctly synthesizes onboarding material and initial secondary research
The approach to the solution: an explanation of the methods we will employ – including a project plan
Explanation of deliverables: the artifacts we will make and how they will be used
Assumptions: Any commitments from the client or data that is relevant
I entered this project assuming that the brief would be simple and easy to compile. After all – we were given such a clear template. I was proven wrong very quickly. A key role of a designer is to tame complexity — and that takes time, energy, and a lot of effort. With pages and pages of notes from secondary research, a transcript from our Subject Matter Expert interview, and endless questions about the project, the real work began. Distilling all of my thoughts, questions, and suggestions into 12 digestible slides that I could read in 10 minutes was challenging.
One of my key takeaways from this process is to focus on the complexity of the specific problem at hand. Rather than asking myself questions about the success of education overall, I needed to focus on questions related to progress tracking. It’s easy to get caught up in the meta, but focusing on one area and the hidden complexities is where we can truly provide value as designers.
One of the best ways to make sense of your data is to visualize it. Make an artifact. This week our team (Allison, Michelle, and Laura) did just that as we further synthesized interviews with gig economy workers. You can learn more about our research with on-demand gig economy workers here and here. Through visualization, we add additional analysis, context, and understanding that will serve us as we head into our next phase: design ideation. We used several visualization techniques including temporal and semantic zoom to approach our data from a new perspective.
Our concept models range from a wide view of the landscape of gig work to a personal look at how gig experiences can impact your emotional resiliency.
Gig Worker Lifecycle
We created several iterations of this temporal zoom because it was a data-rich area. Rather than looking at this through a marketing lens of pre-acquisition (-2) to lapse (+2), we chose to view this from the worker’s perspective to get a better idea of what actions, strategies, and emotions they may experience at different stages.
In the US today, there are only two worker classifications: 1099 and W-2. In Texas, there is a 20-point test to determine independent contractor compliance — and it is clearly not designed for on-demand work. As on-demand gig work continues to grow, we strongly see a need for a third category to help manage the nuance of these company / worker relationships. This semantic zoom quickly shows the different hierarchy of on-demand gig apps and the broad range of gig work as a whole.
Gig App Features
We saved every utterance where a participant explicitly talked about their in-app experiences. These helped us get a good understanding of which areas of the app are top-of-mind for them as they consider when, where, and how often they work. Through this, we also saw strong connections between key app features. Most notably, earnings, assignments, and status are highly interconnected.
While many of our concept maps deal directly with the gig worker experience, there were common trends that transcended solely the gig worker mindset. One interesting theme we observed was the power of gig work to make individuals more emotionally resilient. Many people expressed anxiety or hesitation about doing gig work. From having people in their cars to constantly making a first impression, there were unexpected emotional challenges associated with the work. By acknowledging this discomfort and working through it, these workers developed a new sense of confidence. The cycle of gig work is so fast, workers were able to have several growth experiences in a short amount of time.
Short, Medium, Long-Term Goals
One of our core insights has been:
“Shifting focus to long-term dreams helps us cope with the reality of the immediate, especially when the weight of short- and medium-term goals is too great.”
To illustrate this, we went through our interviews and visualized all of the short, medium, and long-term goals that were expressed by our participants. A key insight when developing this map was that there are common bridges that help shift focus to medium- and long-term goals. For example, a car was often mentioned as both something that required additional focus and a way to “level-up”. Similar attitudes were expressed around education or growing your social and professional networks.
In addition to visualizing our data, we also pushed to create more insights that can serve as inspiration for future design ideas. Questions we hope to answer this week are:
How are we organizing ideas on our wall to be more efficient? Can we shift to prioritizing insights and concept maps without having to keep all of our themes up?
How can we surface our best quotes to inspire us through design ideas?
How can we continue to push ourselves to create provocative insights?
How can we not constrain our ideas to just the gig perspective while still making use of our data?
The exercise of going through our blog prompt was helpful and we are committing to using that as a check-in guideline every Wednesday moving forward.
This week, we were given the challenge to research competency-based learning to ultimately develop viable concepts for the University of Texas as they test modular learning. Our brief suggested:
“As the amount of student debt reaches extraordinary levels, and public funding diminishes, many students are questioning the value of the traditional college degree. Many potential students simply can’t afford to dedicate four years exclusively to attaining a degree, and must instead somehow both work and study. Furthermore, the traditional model itself is not particularly successful. Less than forty percent of students that begin a four-year degree finish at all.”
With more than 70% of students being categorized as non-traditional, it’s vital for universities like UT to maintain relevance by providing solutions that can meet the needs of working students who may have dependents or schedules that are less flexible than a “traditional student.
What is a non-traditional student?
According to the National Center for Education Statistics, nontraditional is not defined by age or other background characteristics but focuses on behavior. Three sets of criteria were used to identify nontraditional students:
Delayed enrollment. Students who delayed enrollment in postsecondary education by a year or more after high school or who attended part-time were considered nontraditional.
Financial and family status. Students who have dependents other than a spouse, being a single parent, working full time while enrolled, or being financially independent from parents.
High school graduation status. Students who did not receive a standard high school diploma but who earned some type of certificate of completion.
What is competency-based learning?
There has been a shift away from traditional learning towards more flexible, student-led learning that is focused on competency. Competency-based education has largely been popularized by MOOCs (Massive Open Online Courses) that allow nearly unlimited participation on the web.
CompetencyWorks updated their definition of competency-based education to include:
Students are empowered daily to make important decisions about their learning experiences, how they will create and apply knowledge, and how they will demonstrate their learning.
Assessment is a meaningful, positive, and empowering learning experience for students that yields timely, relevant, and actionable evidence.
Students receive timely, differentiated support based on their individual learning needs.
Students progress based on evidence of mastery, not seat time.
Students learn actively using different pathways and varied pacing.
Strategies to ensure equity for all students are embedded in the culture, structure, and pedagogy of schools and education systems.
Rigorous, common expectations for learning (knowledge, skills, and dispositions) are explicit, transparent, measurable, and transferable.
Major players for competency-based learning include Coursera, edX, FutureLearn, Udacity, and Khan Academy. Most of these MOOCs have traditional institutional partners like MIT, Harvard, or Berkeley, but are able to offer courses at a fraction of the price.
I’m excited by the potential of competency-based education, particularly it’s goals around equity. Competency-based learning aims to dismantle systemic barriers to opportunity (time, geographical access, funds, etc). It also breaks down seemingly nonsensical testing schedules and allows students to work at their own pace.
However, the barriers to adoption are great as we have to adopt a new model for learning, and for some — learn digital tools entirely. In 2015, 52% of adults were relatively hesitant to use digital tools for learning. Only 17% of adults are considered digitally ready. So while MOOCs can encourage equity for some, these learning models can create even greater divides for those unprepared or cautious of digital learning.
Because of the easy access to MOOCs, I fear that students will feel less invested and ultimately, less likely to finish. Traditional institutions with open admissions policies only graduate 25% of students within 6 years, but institutions with acceptance rates of 25% graduate 87% of students within 6 years.
Without a significant level of investment, either emotionally or financially, I am concerned student churn rates will be too high. The most successful will likely be a model with a low barrier to entry and a high stickiness. If anyone will download your app — how do you keep them around? DuoLingo seems to be the most successful at this because they have gamified streaks so effectively.
The second biggest challenge will be to get people in a flow state – matching their skills with their work perfectly, so they are not either too frustrated or too bored. Being able to test learners so that curriculum is well-matched is key.
Additional questions as I continue researching:
How can you encourage students to adopt a growth mindset so they are inspired when they reach difficult concepts, rather than quit?
How can we bring celebration into the learning experience?
Without traditional timing models like semesters, how should we design courses? Hours? Weeks? Months?
Do these models change based on a domain? Or can the apps and service models be interchangeable for an arts degree and a computer science degree? Most services are focused heavily on the popular tech skills of today. Is that based on demand, or are those topics better to learn in a competency-based model?
When we started this Ethics class, I was really thankful for the opportunity to explore not only existing ethical frameworks but also my own values. I’ve never taken space to really think about what I value as a person and how those values impact my decisions. I’m a logical reasoner and a gut-check verifier — so I definitely (over)think my decisions often, but those are mostly rooted in facts rather than values.
As a conflict-avoidant person, I also rarely debate issues and this class has challenged us to confront risks and challenges of ethical issues. It’s by recognizing this tension that I’ve been able to get more clarity on my stronger values and motivations.
Below I’m going to walk through the process of arriving at my ethical framework along with tools and resources that I regularly referenced.
Identifying My Values. Before we threw ourselves in the deep-end of ethics, we took the time to meditate on what matters most to us. Through a Personal Drivers exercise from Pivot (a delightful activity for an afternoon), I uncovered a few values that matter most to me: gratitude, growth, collaboration, courage, mindfulness, independence, and grit. These drivers served as a foundation for the rest of the course.
Understanding foundations. We also took the time to understand popular existing ethical frameworks and why those resonate. Understanding the basics of consequentialist, non-consequentialist, and agent-centered theories also primed us to understand both what a framework is and different modes of thinking about ethics.
Applied ethics. Over the last 6 weeks, we’ve continued to apply these existing ethical frameworks to issues of today. As we read about issues like dark patterns, privacy and consent, and technology addiction, I took note of the ethical questions that arose. For example, when reading about technology addiction, this quote from B.J. Fogg, the father of behavioral design, really stuck with me:
“What I always wanted to do was un-enslave people from technology.”
I asked myself: how can I work this into my framework? How can I ensure that as a designer I am fostering relationships, connection, and giving power to the user?
Synthesizing inspiration. With dozens of questions in the margins of my readings and notes from class, I tried to make sense of what ideas have been resonating with me over the past quarter.
I also referenced existing designer’s ethical frameworks to see if there were any blind spots in my thinking. Examples from Design Ethically, Artefact, and Kat Holmes provided inspiration and expanded my view to consider the system in which I operate as a designer, not just my personal values.
I paired down my questions to key ideas, affinitized those, and ultimately came up with a framework that leans on usage, power, and equity as the main 3 pillars with history and ecosystem as a foundation.
This graphic is a digestible abstraction of my ethical framework. Each of these themes has corresponding questions, and all of those questions are also considered through a lens of time and scale.
One of the core values reflected in my framework is the idea of promoting shared experiences. How can we create products and services that counteract filter bubbles, polarization, and disconnection?
With this foundation of connection in mind, my most important task moving forward is to be able to weave these ethical questions throughout my every day to help create a shared language with my network. I don’t want to be in a high castle of ethics. I want to make artifacts that can be easily shared and consumed to promote more of these conversations. I still feel like I’m at the peak of the complexity curve with my framework, so my challenge to my future self is to continue distilling these ideas into something I can quickly reference and share.
For a city with a culture so devoted to fitness and green spaces, Austin parks are surprisingly underfunded. APF attempts to bridge the gap between what park users need and what the city is able to provide through fundraising, volunteering, and events.
APF’s strategic vision includes increasing awareness of their organization in the community, diversifying funding streams, and improving the ranking of Austin parks nationally. We worked with them to develop design criteria that would support these goals in ways that were aligned with their mission, “People + Parks,” and supports their organizational commitment to equity.
Censorship is no longer a discussion of the prohibition of content. With the massive democratization of publishing platforms, the influx of content has created a new opportunity for censorship: information overload and attention redirection. 500 hours of video are uploaded to YouTube every minute, The New York Times posts 250 pieces of content every day. Our president tweets over 4,000 times per year. It’s a lot to manage. The curation of content is the biggest threat to censorship.
Personalization of content creates filter bubbles that amplify existing biases and essentially forces us to live in different realities. This personalized reality decreases the quality of information we consume, lowers the likelihood that we will consider (or even hear) opposing viewpoints, and ultimately ruins civil discourse. After the 2016 presidential election, the polarization and manipulation of content have been widely discussed around the globe.
Curation of content is not simply a taste issue or an entertainment issue. The curation of content is at the core of a productive democracy. For something so important, we must ask: could we give users the power to curate the content they consume?
Ultimately, the goal of effective curation would be to develop an unbiased understanding of the world that is free of fractured realities or perspectives. Differences of opinion are welcome – but those conversations should be able to exist on the same plane. If curation continues to polarize, there will be no equal ground to stand on.
Risks and Benefits of User Curation
To first understand this question, I wanted to clearly debate the risks and benefits associated with user-controlled curation.
What are the risks associated with giving users the power to curate?
Users prefer echo chambers. These filter bubbles offer the reassurance of your opinion, reinforce existing biases, and keep you engaged with content that you’ve been proven to enjoy. This could worsen divides.
Curation requires prior knowledge. To truly curate a truly broad and representative view of a topic, proper knowledge is helpful. How can you represent multiple viewpoints on a topic if you don’t understand it?
Information overload could cause opt-out. If users aren’t fully empowered to curate content effectively, they could be overwhelmed and opt-out completely. Is biased information better than none at all?
Do they want power? If not given the proper tools to curate effectively, the cognitive load associated with decision-making could be too great. What if you don’t want to think?
Will misinformation worsen? Are users informed and engaged enough to fight social control and propaganda?
What are the benefits associated with giving users the power to curate?
Creates awareness of biases. By actively engaging in content curation to counteract bias, you will become more acutely aware of existing biases.
Rebalances power dynamics. In the most extreme cases like content bans in China to nipple bans on Instagram, the ability to curate is the hands of the powerful. By giving control make to users, we can work to redistribute power.
Respects user autonomy. In addition to rebalancing power, giving control back to the user also respects their autonomy, intellect, and ability to choose.
Teaches to combat misinformation. This is an area that is becoming increasingly urgent. As deepfakes and AI-assisted content creation become more popular, it’s vital for citizens to continue to fine-tune their filters for real content and misinformation. Relying completely on platforms to filter content trains users to be complacent over time. We must continue to ask ourselves: is this a credible source? Is this content logical? Can I fact-check this before sharing?
Applying My Ethical Framework
With these benefits and risks clearly displayed, I ran this problem through my framework. With individual autonomy and respect as core tenants of my ethical framework, I strongly believe that we should design products and services to give users more power to curate their content. The strongest argument for me lies around teaching helplessness. If we never give users the power to curate, how will we ever learn how to identify biased, false, or misleading information?
This artifact helped me understand where existing platforms lie, and where there are areas for opportunity. Escape Your Bubble, ConsiderIt, and Balancer were all tools we read about to counteract bias and create a more informed user. Despite the effectiveness of these tools, most of our day-to-day consumption exists in the echo chamber section. Because these platforms are personalized, it gives us a false sense of control and showcases content that feels resonant. This false sense of control keeps us from seeking more autonomy and keeps us complacent with the content that is given to us.
How can we actually give users control while still keeping them engaged?
“Which leads to daily frustrations with countless usernames, forgotten passwords, ID documents and time wasted waiting to be verified and authenticated to complete a task such as gaining access to a building, boarding a plane, getting a job, etc.”
He also details the importance of a singular identity for humanitarian and legal reasons. In order to have a voice, “a verifiable and trusted identity is necessary to interact and transact with others.”
While I agree, I think we need to distinguish between identifying information like our birthdate, social security number, and nationality and more adaptable pieces of our identity like behaviors, values, interests, and emotions.
In many papers we’ve read, both aspects of identity are used somewhat interchangeably. As computers spread into everyday objects and consumer tracking continues to get sneakier, the potential for data misuse, manipulation, and power imbalances becomes greater. This is magnified if we are then also subject to one, singular identity that is connected to all of our interactions. Davos-Klosters recognizes this as a risk, and said we need “options for those not wanting to have a digital identity or those that want to share only parts of their identities (e.g. different personas in a different context) or only share relevant identity data for specific purposes must be considered.”
Moving forward in discussions about identity, I argue there should be a clearer distinction between fixed parts of identity (things that might go on an ID) and adaptable parts of our identity.
Until we have more control and transparency over our data, I don’t feel comfortable arguing for unified identities. I don’t trust that corporations won’t use a humanitarian angle to ID people as an opportunity to sneak in data tracking on more adaptable, personal parts of our identity.
Imagine a future where all aspects of your identity were observed, noted, and stored — forever. From the moment you’re born, every aspect of your physical presence, interests, relationship, use of language — everything — was captured and stored.
As ubiquitous computing and the Internet of Things (IoT) popularizes, this future is possible. Right now, our digital behavior is meticulously monitored and stored in connection with our device ID, email address, or social media login. Our nondigital actions are not far behind. The distinction between our physical and digital presence is waining.
Without control of our data, a fractured identity is one of the few protections we have.
Right now, it’s possible for me to sign into my YouTube account with one email and watch certain videos and switch to a different browser for others (something I do regularly when watching work-related content like tutorials vs. entertaining videos about food or cultures). I consciously keep those pieces of myself separate, because I want to stay in a different mindset. I want to target different sides of myself.
If I were to have only one unified identity across all services, I would lose this control. All of my actions could be cataloged and attributed to me.
I remember when I was younger and adults would threaten me not to make bad decisions because “they would go on my permanent record.” I now know that no such permanent record exists. But in a world with a single identity that is made up of your digital and real-life actions, that permanent record could be a reality. And systems could start gathering and attributing data to you before you even have the capacity to consent.
Imagine a day where every interaction you have is personalized to who the system thinks you are.
Your alarm wakes you up at just the right time with news articles that have been curated entirely for your interests, storefronts or vending machines could adapt to only show you things you’re interested in, your doctor could only give you recommendations based on previous behaviors from the system. Everything could be built around your singular identity of how the system views you.
But what if you wanted to make a change? Imagine trying to combat a world that has been entirely personalized for who you’ve been. You would rarely have challenges or catalysts to inspire change. Even if you did, you’d have to combat a lifetime of data that informs your current state. It’s a self-fulfilling prophecy. If the algorithm thinks you are this way, maybe you’ll just always be that way. And who gets to write the algorithm? (That’s a whirlwind question for a later date.)
This already happens on a certain level with media consumption and social media habits. We create an echo chamber that is nearly impossible to escape. The only way I can (somewhat) escape is by changing my email or signing up for a new account and retraining the system. But if we had a unified identity, we’d lose that control too.
Discrimination & Manipulation
Another concern of unifying our digital identities is the potential for misuse. While fixed pieces of our identity are subject to discrimination, adaptable pieces of our identity are subject to manipulation.
Right now one of the only safeguards I have to combat constant tracking is through a purposefully fractured identity.
And finally, even if we are given more agency, I am concerned that information avoidance will keep us from truly being in control of our digital identities. So while we continue on this thread of the importance of digital identities, let’s be careful to not lump in data that may only lead to misuse.
At AC4D, we’re constantly being challenged to push ourselves. In Quarter 1, we started honing our presentation skills. In Quarter 2, our Ethics in Design class challenged us to facilitate. As designers, it’s a vital skill to be able to engage team members (both fellow designers and non-designers alike) in discussions about the ethical implications of our design decisions. We need to be able to spark a thought-provoking conversation that opens minds and allows for nuanced introspection while also staying focused and action-oriented.
Privacy & Consent in Practice
In this section, we are discussing privacy and identity — two quickly evolving issues that will undoubtedly affect us as working designers. From more top-of-mind issues like the Cambridge Analytica scandal to more niche discussions around using blockchain to decentralize identity, we got a whirlwind view of the biggest issues affecting the privacy sector today.
“There is a widespread intuition that people are inconsistent about protecting their privacy. People are angry about corporations collecting their data but often do not change simple default settings in their apps.” – Svirsky
But why? Svirsky suggested participants were behaving inconsistently in part because of “information avoidance” and that when it comes to privacy, “some people might be willing to spend some money to avoid thinking about it in the first place.”
With this in mind, I wanted to dive deeper into information avoidance, our relationship with privacy, and the consequences of information avoidance for my 30-minute facilitation.
We started with a simple prompt: what information are you currently avoiding? I asked my classmates to silently write one item per post-it, then present their topics to the group and we collectively grouped them. Immediately, trends emerged around finances (401k, savings), health (insurance, longevity), global inequalities, and even our cars (maintenance, what?).
This free flow of ideas we avoid helped set the stage for the next exercise — a quiz that asked you to consider “how much would you pay to avoid knowing certain information?”. When researching information avoidance, this prompt came up as an exercise to help identify if you are “ostriching” — or sticking your head in the sand to regularly avoid information.
While there was no unanimous agreement on everything, we all generally agreed we like to avoid information about our health, finances, and future state — especially if they are outside of our control. (Like the day we die, the balance of our 401k after a market crash.) From that prompt, we talked about trends in our information avoidance and tried to recognize patterns within ourselves.
Now that we had a thoughtful grasp on information avoidance, I asked everyone if there was a time when they had transitioned away from information avoidance. Are there things you use to avoid that you now can handle? What changed for you? How did you make that switch?
I tried to follow that thread and see if there were any ways that we could apply those previous learnings to how we relate to privacy. Are there universal coping mechanisms or tricks we could apply to bring privacy to the forefront?
Ultimately, we all agreed that information that was out of our control or that could not be changed were things we were more likely to avoid. Information like how much money we’ve spent on alcohol in our lifetimes or how many animals we’ve eaten were things I thought folks might want to avoid, but there was some interest in knowing because that information could help shape future behavior.
With control and agency being a key component in not practicing information avoidance, how can we better integrate this into how we talk about privacy? What control do we have currently?
Ultimately, we did not come to one singular conclusion, but there was more space to follow a thread of information avoidance and start to see patterns in ourselves.
This was a great learning experience for me, as I’ve never facilitated a group discussion like this before.
What went well? It was helpful to start the group with a solo thinking exercise and then transition to a group discussion to allow for individual ideas. Getting folks out of their seats always helps with energy, and having a balance of limited activities allowed for deeper discussion.
What would I modify? If I were to recreate the information avoidance worksheet, I would have made a sliding scale of 0-10 (0 being information you’d want to know, 10 being information you’d never want to find out) because applying a monetary number was abstract and differed greatly from person to person.
Most importantly, I would set a very clear agenda from the start with a clear goal. There were times when I was trying to lead a conversation and I would have liked to have been able to point to a whiteboard or presentation and remind folks of the goals of the conversation.
Since August, our team (Kyle, Michelle, Laura) has been working with Austin Parks Foundation (APF) to help them better understand the feelings of ownership over green spaces; specifically how those feelings of ownership can develop and drive behavior.
WHERE WE ARE IN THE DESIGN PROCESS
Through contextual inquiry and the sense-making process of theme-finding and service slice creation, we’ve developed a better understanding of how Austinites at multiple levels interact with the park system. Up until now, we’ve been in observation mode — interviewing participants, finding patterns in behavior, and mapping complex systems.
Earlier this month, we presented our themes and service slices to APF, which sparked a deep conversation around these themes and behaviors. While APF has a deep understanding of their stakeholders, presenting this data in a way that was both new and visual helped open communication around their blind spots of the problem space. As specialists in the arena, they were also able to help guide our insights by providing additional context and allowed us to gain empathy with their unique challenges.
Now we start to apply a critical lens to develop insights and a problem statement that will be the foundation for our design criteria.
WHAT ARE INSIGHTS?
An insight is a definitive, provocative statement of truth about human behavior. It is a bridge between research and design. An insight should include both an inferred observation and a provocation — a “should” statement. Good insights reflect our data (it should be true) while also sparking conversation (it can be debated).
To get to an insight we:
Start with a theme.
Rewrite our theme as a “why” statement.
Individually, we each create a provocative, definitive and complete answer to this “why” question.
Then together, we review each answer and combine into a single statement — and dial up the provocation. The more provocative, the more unique (and challenging) our design ideas can be.
We applied this process to 64 themes and created 119 why statements. With such a high volume, we gravitated towards insights that continued to spark conversation and provocation and chose those as our primary focus. From here, we developed a core problem statement.
WHAT IS A PROBLEM STATEMENT?
All of this sensemaking and insight development culminates with a problem statement — a succinct statement that describes the core opportunity area.
Oftentimes businesses jump right to an assumed problem. They focus on the same metric or the same process or goals — when the biggest problem area is yet to be uncovered. Simply put, they can’t see the forest for the trees. That’s where design research comes in. It allows us to take a step back, revisit the system with fresh eyes, and find latent needs or unmet expectations.
A problem statement is a succinct description of the issue that’s worth solving. It provides a foundation for ideation. For APF, our problem statement is:
People need Austin Parks Foundation to provide leadership, not just create consensus.
LACK OF DEFINITION RESTRICTS ACCESS
In many ways, APF acts as an extension of the city. Where Austin Parks and Rec Department (PARD) lacks funding and manpower, APF seeks to fill that gap. Because of APF’s close ties with PARD and the city, they use many of the same community-focused initiatives to come to a consensus among park adopters, visitors, neighborhood associations, conservancies, city departments, and their own goals as a nonprofit. All of these groups look to the community to drive their strategy — rather than one leading the charge.
While, in theory, this community-led strategy should encourage access and opportunity for all, we found that often this lack of focus creates confusion and, paradoxically, feelings of being left out or ignored when an opinion is expressed, but not brought to life. We also saw that despite massive investments of time and energy in communicating with the public, most park users didn’t have awareness of those efforts. The rarified few that were aware were small politically connected subsets of the population such as leaders of neighborhood organizations or people active in non-profit work. To those not involved, these processes do not seem inclusive or transparent.
This is seen clearly among the largest, yet least engaged stakeholder group for Austin Parks Foundation — park visitors — which leads us to our first insight:
Not defining how a park should be used leads to assumptions about who belongs in a park. APF should actively foster interactions across geography and demography to reduce negative judgments between users.
We heard many times from park leaders that there’s no “right way” to use a park — parks are for everyone. Yet park users did feel there were “right ways” to use a park — and oftentimes those “right ways” are conflicting.
Amanda, a new eastside resident, enjoys when families from outside of her neighborhood use her park throw events. In direct opposition is Daniel, a longtime park advocate, who felt that his neighborhood park was for his neighbors — and expressed judgment about outside visitors throwing events in his park. Because “ideal park behavior” has not been defined, visitors create their own expectations which lead to conflict.
We saw this pattern across park users of different types (cyclists versus dog walkers), with each group making negative assumptions about the impacts of the wrong types of use. Most glaringly we saw this problem manifest in attitudes and behaviors about park users perceived to be homeless.
This misunderstanding continues to the next most engaged cohort, park volunteers. We saw a wide range of volunteerism in our interviews, from physical labor to park advocacy to community organizing and event planning. All manifestations of the Austin Parks Foundation mission, People + Parks. We also heard from people who had talents and passions they wanted to share, such as web development, outdoor activity instruction or environmental education, but either didn’t believe that there was support for their contributions, were unaware of the entry points to volunteering, or even perceived parks as a hostile environment for their type of volunteerism. APF has not clearly defined and supported roles for the myriad types of volunteerism that park users feel inspired by. This led us to our second insight:
People believe that volunteering in parks must be physical, which limits the potential impact of volunteer efforts and restricts APF’s ability to engage the community. APF should diversify its support for volunteer engagement beyond current programming.
Sally, a retired disability advocate and active forager, values her neighborhood preserve and wants to help maintain it but her back injury has kept her from volunteering. She told us “You know what I would love to do? Organize neighborhood cleanups or put up signs to identify trees.” She also wanted to lead nature hikes and teach ethnobotany, but given her current understanding of park volunteerism, she didn’t believe it was possible.
INEQUITIES MUST BE CONFRONTED MORE DIRECTLY
Several park visitors and adopters felt that their park was underserved and blamed this on funds being diverted elsewhere. This tension was most often seen as a battle of “old Austin versus new Austin” or an “East versus West” mentality. Because park users felt funds weren’t being divvied correctly, it made them less likely to contribute at all.
Park users want to hoard resources for their park rather than contribute equitably to funding parks across Austin. APF needs to build more robust safeguards into their systems to counteract this tendency.
Wes, a regular user of Austin basketball courts, wanted to improve his park rather than Austin parks as a whole.
“I really want to know: how can I make a difference? Does my money … really make a difference where I want it to? Is that me being selfish by wanting to improve one park that’s close to me versus improving the parks in Austin as a whole?”
While APF and the city want to see all parks improve and park users shared this sentiment in theory, ultimately park users want to see their park improve the most. This was seen at a heightened level among park adopters.
The Park Adopter program amplifies existing inequities by matching highly privileged adopters to parks in their own affluent neighborhoods. APF should proactively manage this program to deconcentrate existing social capital and ensure equal access to funding and support.
The Park Adopter program turns citizens into advocates for their parks, so it’s a logical step that they would feel their park is most deserving of limited resources, whether from APF, the City of Austin or other grant-making organizations. But in this scenario, educated, wealthy and well-connected park adopters in affluent neighborhoods have the time, experience and access to divert funds to their park in creative ways.
10+ year park adopter Daniel skillfully maneuvers using his neighborhood association, city representative and lobbying methods to get funds for his neighborhood. Meanwhile, new park adopter Rico has less time, funds and access, which leads to his park receiving less over time.
While APF wants to serve historically underserved areas of North, South, and East Austin — the “Eastern Crescent”, they still have adopters and systems that have been in place for nearly a decade that continue to reinforce power for the already powerful. Everyone feels they deserve more, and the current model for grant approval favors the squeakiest wheels. And the folks with the most time to squeak are often the most privileged.
Now that we have a clearer focus of the problem area, we will work to provide recommendations and design criteria. These design criteria should empower Austin Parks Foundation to be able to develop its own programs, services, or even products that truly answer the problem area we uncovered.
Initially, our focus was simply to look at how gig economy workers are making financial decisions with fluctuating income streams. After a few initial interviews and feedback from our team, we’ve shifted our focus to better understand how the gig economy is supporting a new “American Dream” — one that values flexibility and freedom over stability.
Why the Gig Economy?
The gig economy is experiencing incredible turmoil as lawmakers, unions, workers, and companies all struggle to find common ground. Despite nearly a decade of growth in the on-demand economy, few unions exist and labor classifications are largely still in a traditional 1099 vs W2 model.
While the gig economy offers a low barrier to entry and access to fast cash, it is also ripe for worker exploitation. Less than 5% of on-demand gig economy workers use apps as their primary source of income and retention rates among platforms are low, which leads to a highly transient workforce that is difficult to mobilize.
Despite these pitfalls, the gig economy continues to grow as Americans search for ways to supplement their income, pay debts, or meet earnings goals.
Assumptions to Guide Research
With all of this in mind, we started our project with assumptions that helped guide our script and exercises.
We believe that on-demand gig workers largely overestimate what they receive from platforms — money, freedom, and control.
We believe that on-demand workers will be more likely to cut corners and assume greater risks to achieve their goals, like not purchasing commercial auto insurance or preparing for taxes in advance.
Because of quick access to cash that is difficult to track, we believe that on-demand workers will likely consider their goals in terms of time (hours, days, months) rather than clear dollar amounts. For example, a worker may set goals to work 3 hours a day, 5 days a week rather than setting a strict dollar amount goal.
As a result of this easy access to “instant cash”, we also anticipate that gig-economy workers will loosely budget resources in the short term (days/weeks) rather than long-term (months/years).
We talked to 14 on-demand gig economy workers with current and previous experience with Uber, Lyft, Shipt, Instacart, Favor, Postmates, Amazon, Task Rabbit, Bird, and Rover. Roughly half of our participants used the gig economy as their main source of income with the other half using the gig economy to supplement their primary job.
With our focus statement and assumptions in mind, we developed a script and exercises to help guide our research.
First, we start the interview to get a foundational understanding of our participants’ backgrounds and involvement with the gig economy. Then, we ask participants to engage in a series of activities designed to uncover the mindset and behaviors people have related to gig work, decision making, and personal value systems.
We give participants cards with words commonly used to describe work like flexible, money, community, on-the-job training, and more. Then, we ask participants to organize these cards in a way that is meaningful to them to help us uncover what aspects of work are important and affect their decision-making.
Nando, an Amazon worker and previous Favor Runner, ordered cards from most important to least important. He placed most of his emphasis on a fulfilling, stable career with strong growth potential.
To help us consider how participants consider their current or future potential, we had them map out a dream web. Starting with them in the center, they mapped specific goals and we probed on if they had timelines or clear paths towards achieving those goals.
Brittany, a single mom of 4, drew that her main goals were to own a home, put her children through college, get married, and start a nonprofit. She was very focused on providing a better future for her children and her community, so they don’t have to overcome the same difficulties she went through as a single parent.
Stressed vs Stable Timeline
Next, we had participants map out a recent time in their life when they were feeling financially stressed or stable. This exercise helped us understand how participants have navigated moments of financial stress or stability. We also were able to better understand what specifically made certain situations stressful or stable and what strategies were employed in either state.
Holly, an ex-software developer and Lyft driver, mapped out the last year of her life — starting with getting laid off in January until now. A major theme we saw was that stressed periods are not always a result of finances. In Holly’s case, one of her strongest periods was when she was not working at all.
Why contextual research?
You may be asking: why sit with people and map their dreams when you could send out a survey? Why start with people at all? Oftentimes, we think we understand the problem space and spend the majority of our time on solutions. But our method forces us to take a step back and first look for the right problem.
By spending time with the people we seek to help, we can get a better idea of their values, needs, and behaviors. Surveys often point you to what people already know they want. Through contextual research and probing, we are able to find latent needs: problem areas that our users may not be aware of yet.
By the end of this quarter, we hope to present JUST with a succinct problem statement so they can move forward — confident that their solution solves the right problem.
Now that we’ve compiled all of our interview data, we are in synthesis mode — making sense of this data by finding themes and creating visual representations of the system (service slices and concept maps). From there, we’ll use those themes as the foundation for insights — which will help lead us to our primary problem statement. This problem statement will ultimately serve as the catalyst for all of our design ideas in Quarter 3 and Quarter 4.
Have questions about our research? Are you in the gig economy and want to design with us? Email us at email@example.com with details.