How to Age Gracefully

Dear 91 year olds,

Don’t listen to other people’s advice. Nobody knows what the hell they’re doing.

Signed a 93 year old


Privacy: Take Three

Take 1: Recently I was added to a group on GroupMe whose size quickly grew to over 100 members. Naturally, people felt the need to create a more intimate sub-community for sharing information specific to a smaller number of people. Members gave ideas to start a Facebook group. But some did not have Facebook accounts. Others mentioned starting a LinkedIn group for discussing professional endeavors. Yet, LinkedIn was seen as being too formal for free-flowing communication. Should there be mechanisms for sharing and creating communities across platforms? Should there be one platform for all preferred actions? What to do when a platform doesn’t meet privacy and sharing expectations?

Take 2: I used to be friends with my favorite younger cousin on Facebook. My cousin grew up near Atlanta. He created his Facebook account when transitioning from middle school to high school. Late nights out in high school soon turned to late nights out during his first year of college. Since teenage boys don’t necessarily reveal their actions to their mothers, it was natural for his mom to turn to Facebook for help in understanding her son. What she soon found, she did not like. It was the typical partying, perhaps some hints of illegal substance use. Naturally, she approached him about his activities which, of course, resulted in him unfriending her on all social media platforms. Unknowingly I began to make comments about his activities online, thinking she could see his posts. She did not know that he had blocked her and my comments led to myself being blocked as well. When do contexts collapse? Are existing simplified privacy mechanisms simplified enough? When and/or how should third-parties (e.g. parents) have agency over someone’s (e.g. their child’s) information?

Take 3: As I scroll down my Instagram account, I am instantly presented with 5 photos of my friend’s son. The kid is 3 years old and I am being shown cute baby bum pictures and outfits that would be quite embarrassing to him in ~10 years. How will he recover from such photos? Who will have control over the information when he gets older? How can we manage privacy from actions that happened in the past?

Snapchat, Facebook, Twitter, GroupMe, LinkedIn –

All are different examples of platforms for sharing information. The above vignettes highlight challenges of existing online social platforms. How can industry professionals and academics begin to solve these problems? Essentially, social  networking sites think of the individual as the unit of analysis. However, an individual’s actions online may affect the perceptions, expectations, and privacy of larger groups of people AND these actions may affect people different over time. This problem is one I tried to tackle with other researchers in the Networked Privacy workshop at the ACM conference on Computer-Supported Cooperative Work and Social Computing (CSCW 2015) in Vancouver. In my opinion, I think researchers need to step beyond studying privacy of college students in terms of actions and opinions and delve more into solutions to problems of context collapse and boundary turbulence. Also, incorporating different age groups, non-Western cultures, and people with different abilities into the privacy space is important.

Who will start to address the questions above, both conceptually and technically?

thank you to Michael Dickard, Priya Kumar, and Dr. Anne Marie Piper for their contributions and great ideas during the breakout sessions at the workshop

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Wearables with Digitally-Isolated

At the moment, Fitbit reigns supreme in the wearable computing arena. But Fitbit is a device. Other forms of wearables could be more embedded into one’s environment, more ubiquitous. While this may seem creepy to some people who aren’t frequent users of technology, I propose that wearables could lower the barrier of entry to technology for those who are digitally-isolated. This isolation could be attributed to a disinterest or satisfaction with current lifestyles, or it could arise from lack of access or mobility. For people who can’t afford a $1400 laptop or unable to walk to the library/computer lab, wearable computing is the solution.

But what would wearables look like for such populations? As I hinted above, ubiquity is key. Undershirts could measure heart rate and notify a physician when there is an irregularity. Socks could include GPS sensors that can connect to kitchen appliances. They would be aware when someone is cooking but not in the kitchen, vibrating to signal that food has finished cooking.

Life Happens. Designing for It

This weekend I attended the Designing Technology for Major Life Events workshop at CHI. Although I didn’t get the one slide introduction memo, I still enjoyed the discussions that took place. The attendees had a variety research areas that related to major life events – retirement, pregnancy, cancer diagnosis, natural disasters, gender transition and more. The major theme that resonated across the topics was that of transition. Transitions into different living environments can cause stress for college students and isolation for older adults. Grandchildren who move away from their grandparents lead to adopting new forms of communication technologies. Gender transitions can trigger reflection and the need to change one’s identity. Moving from a primarily offline world to digital culture can spark concerns of privacy and control. Cancer diagnosis changes routines, awareness and participation of patients. All of these are important life events, but what makes something important? Facebook’s attempts to decide importance with its News Feed algorithm. Can such algorithms be used to force memory to remember good major events vs. bad ones? Could this idea of forced memory be used to make transitions easier?

Life course theory posits study one’s experiences over time. The study of the lifespan is unique because, although it affects everyone, it does so differently for each person in the world. That’s what makes doing research in this area so challenging.

In our breakout sessions, we brainstormed design challenges of technology as it relates to major events and opportunities resolve these conflicts. A few of these challenges are,

  1. technology can be seen as a negative influence,
  2. we unintentionally design for exclusion, and
  3. building systems is risky business

While researchers face these challenges, we can also begin steps to solve them. One solution is to treat technology as a playground. As the plenary speaker, Margaret Atwood, stated – “First we imagine it, then we make it.” Researchers could benefit from a few improv or creative design classes. Often we are concerned about methodology and following the correct process that it limits the scope of our work. Do research for research sake.

Because we want to design for the majority of people who will use our systems, we often design to exclude other people either based on access, financial abilities, skills, trust, and language. However major life events happen to everyone, no matter their abilities. Therefore while our excuse to not building technology for outlier populations may be a cost-benefit reward, we must remember that low tech and no tech options can still be used to study technology use.

Lastly, building stuff is risky. It’s much easier to observe existing human behavior because no device is perfect. And, major life events typically do not happen every day. Therefore there are much higher stakes if the technology doesn’t work as expected. However, we must develop something that is functioning “enough” because no work will ever get accomplished if we build solely on what currently exists. While I am in the process of struggling with this, I have to remember that the first version will probably not be perfect and iteration will happen.

Thanks to Lana, Madeleine + Tilman for their thought-provoking discussions in the small groups and everyone else for their challenging research questions in the workshop overall.

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Home Automation 3.0

Home automation is nothing new. Hobbyists have been connecting gadgets into their appliances and fixtures for decades. But now, home automation is becoming more accessible to the amateur and a lot more aesthetically-pleasing, in terms of design. Google’s Nest allows people to control their thermostat using their cell phone. Its simple circular design most likely appealed to Google since not all of their designs are as clean.

Belkin’s WeMo allows users to control their lighting and view the cost for using each appliance with a simple phone app. Clearly the concept of ‘quantified self’ (viewing data about yourself to inform future behaviors) is extending to ‘quantified space’.


Years ago researchers at Georgia Tech began the Aware Home initiative began to think abut smarter spaces, specifically for older adults, mainly using sensors. How can we push the boundary beyond simple sensors to track presence or appliance usage, and towards innovative solutions that are easy for people of all ages to use. The added challenge is that older adults may have a higher chance of disability, and no two disabilities are alike. Universal usability, in general, may be as difficult as an NP complete problem. But, universal usability for quantified living spaces sounds feasible.

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You must believe me when I say that I have the utmost respect for HCI people. However, when HCI people debug their code, it’s like an art show or a meeting of the United Nations. There are tea breaks and witticisms exchanged in French; wearing a non-functional scarf is optional, but encouraged. When HCI code doesn’t work, the problem can be resolved using grand theories that relate form and perception to your deeply personal feelings about ovals. There will be debates about the socioeconomic implications of Helvetica Light, and at some point, you will have to decide whether serifs are daring statements of modernity, or tools of hegemonic oppression that implicitly support feudalism and illiteracy.

I found this to be entertaining. 

via James Mickens @ MSR

You must believ…

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movie-inspired adventures

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Why U No Want Facebook?

Why do people resist sites like Facebook and Twitter so much? Part of me thinks it’s because they want to be different and are afraid of actually liking it.  The other part of me thinks it’s a marketing problem. Often these sites are promoted as helping you make new friends. What if you like your current group of friends? Or, they’re advertised as letting you keep in contact “all the time”. Frankly this “always on” idea is a) annoying or b) creepy in today’s age.

How can social media be re-marketed to groups who resist the change so much? Calling all parents, political figures, highly-restrictive companies, older adults! For those who use Facebook, Twitter, Pinterest, Linked in, G+ – why do you? What do you think would make your stubborn friends sign up? For those who don’t – why don’t you? What would need to happen to encourage you to participate?

-a frustrated social media  + accessibility researcher/graduate student

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Physical Predictive Analytics


Big data. It’s the buzz word used everywhere, usually thought of for use by tech companies such as IBM and Intel, but is now making it’s way into a variety of other companies – even Wal-Mart!

An recent article discusses the next big thing in big data. When dealing with a wealth of data, there’s:

  1. descriptive analytics – explains what has happened in the past
  2. predictive analytics – predicting future events
  3. prescriptive analytics – will predict the future, explaining why and “prescribing” some solution for what will happen

The article mentions self-driving cars as an example and how prescriptive analytics allows cars to handle left and right turns to happen in the future. However, I can see this playing a larger role in ubiquitous computing related to physical devices and sensors that control behavior in other ways. For example, take a thermostat which can use weather forecasting data to predict how weather will affect future A/C usage and issue bill ahead of time. The thermostat uses future forecasting and makes some decision (specifying a bill) based on household use. In what other ways can an abundance of big data and sensors play a role in the future of prescriptive analytics.

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A Nation Divided on Snowden


inspired by:

I typically don’t take sides in political matters but I don’t think Snowden should be prosecuted at all. I understand the there-must-be-consequences-for-breaking-the-law rationale, but I think he made a contribution to the good of humanity. Now people might actually listen to what computer scientists have been saying for years in that all information is public somewhere and to be more conscious of what they’re putting online. 


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