Designing digital books for serendipity

Many discussions surrounding the evolution the book revolve around the impending doom of the bricks-and-mortar store as it loses out to the online experience — where our measure of “online bookstore” is unmistakably Amazon, followed by mega-bookstores like Barnes and Noble. A new brood of e-readers recently released at CES heats up the conversation that began with Stanza, the Sony e-Reader, and of course, the Kindle. Then, there is a whole lot more talk around the changing role of the publisher.

However, in this post, I just want to discuss what kind of world around books we can design for ourselves so we don’t lose the romance of serendipitious moments (whether with other books or readers), or the delight of the chance encounter, as books — and our experience of buying, reading them — evolve towards being primarily digital.

When we discuss the online/offline store experience, we often talk about convenience vs. instant gratification, or factors of searchability, choice and cost. When we talk about devices, the discussions tend to circumnavigate what’s the acceptable cost of an e-book, whether it’s a good reading experience, and now, whether it should be a device for reading only, or a do-it-all platform.

It strikes me that we’ve forgotten a very simple thing about the book that lends itself to be such an irreplaceable object: how the design of the book lends itself to serendipity.

The case for serendipity

From Bob Stein’s article: “A clean well-lighted place for books“:

“Brick and mortar bookstores are much better for (un-directed) browsing than online stores. This is probably mostly a function of bandwidth, i.e. I can see so much more in a bookstore than I can on my 2D screen. This will change as the web and its attendant hardware/software develops over time, but my guess is that a satisfying browsing experience of the order i can get in a great bookstore is many, many years away from practical. On the other hand if you know what you’re looking for, online shopping excels at simplifying the process of making the transaction. In fact, in every sense except immediate transfer to the buyer of the object they’ve purchased, online buying is vastly more efficient. When the bulk of our book purchases are in electronic form, and therefore delivered instantly, the significant advantages left to the bookstore will be the superior browsing experience, the help desk and the cafe.”

There is value in that browsing experience that is liberating: the ability to walk through a bookstore until something catches your eye and calls out to you out of the blue. It’s about the delight of finding something that you weren’t intentionally looking for. What about chance situations where you may meet someone walking along in the street with a book that you’ve read before tucked under their arm? Or someone reading a favourite book of yours on a bus? Do you get a flutter of excitement, despair, a wander down literary memory lane? Random situtations like these provide the opportunity of a human connection that wasn’t sought, hence provide a level of delight or emotion that digital guess work will not easily replace. Not only does it connect us to other people, but it also allows us to reconnect with our past selves.

While we have begun to emulate these kinds of connections in the social network space with projects like Shelfari, Library Thing or BookGlutton — it’s not yet something amazing that just happens to you as you are off picking up some milk at the corner store.

In the bookstore

We are familiar with how Amazon has done a very clever thing by reusing the analysis of their sales statistics to enable them to make associations such as “Customers who bought this item also bought …” However, Amazon tailors to the fuzzy reader profile that they create around what books you have bought and what you are interested in: that is, it is still based on your previous buying, rating and perhaps browsing decisions. If you create an Amazon.com account afresh today, it asks you to rate things you care about until it manages to get enough data to set you up with recommendations. (It takes just about 2 items to start profiling you. Scary, huh?)

There’s an interesting statistic tucked in the middle of a post last year at Follow the Reader on book-buying patterns: “31% of all book purchases are impulse buys”. These numbers appear to be US-only, but this is undeniably an astounding figure for any market. Of course, impulse buys can mean sales resulting from Amazon recommendations — or as avid book-buyers know, it’s quite likely to also mean what catches your eye in a physical bookstore.

Serendipity amongst the shelves

So, thinking about it for a moment: the physical bookstore is usually categorized, so that you are likely to find books you like in a space common to the sort of books you already like. However, unless you know the entire layout of the shelves, chances are, a good book may be never in your direct range of sight. This is where we are compelled to make a journey from point A to point B that may lay your eyes on an interesting title that you may not have otherwise come across before.

How could this fit into where we are headed digitally? Take 10 mins to watch this video (in French), which cleverly shows a way a content creator or writer can use reading devices as much as a reader can. At 1:41, the writer walks into a bookstore, picks up some books he wants to purchase, downloads them by touching his device onto the back of the books — one presumes there’s a unique identifier, whether enhanced ISBN or book-specific RFID technology. After a conversation with the bookstore manager who recommends him another book, they go to the cash register where the writer confirms he’s buying everything, and the manager verifies his selection and finalises his purchase.

I’ve been buying predominantly digital books for over a year — I now only buy paper books only when they are richly illustrated books that I know I will refer to time and time again. Recently in bookstores, I’d begun the habit of picking up books that look interesting, then using my iPhone to check reviews online. If I liked the reviews, I would proceed to see if the books are available digitally. Right now, neither books nor digital devices allow me to perform this decision-making and purchase process seamlessly. (After looking up my fifth book, my iPhone began to get hot…) There’s plenty of scope to explore in terms how we want to use a physical bookstore as something that helps your buyer make decisions based on the richness of information and data available online.

(A related statistic from the aforementioned Follow the Reader post: “67% of readers say they find reviews online vs. in traditional print media”.)

Serendipity on the street

Consider that serendipity around modern books are established on the basis of its portability and the visibility of the cover that you can’t just “turn off”. (That is, unless you’re Japanese, in which case, you’re likely to have a polite-looking cover over it anyway). Can this characteristic be easily duplicated with digital devices? Imagine if you could peek at what book someone is reading on the Kindle because the title is visible somewhere external on the device. What if there’s a possibility of devices that can display a digital cover? What if there’s a possibility of devices broadcasting (with users’ permission, of course) what they are currently reading, or what’s in their library? This is not a new concept, remember Nintendogs’ “Bark Mode”? This would be similar to an iTunes shared list on a network, except in this case the network is everywhere.

(Aside: in the evolution of the book, book covers have not always been the most important, therefore not the most attractive. In early display of books, spines were treated as functional as a door hinge and therefore, books were displayed with their spines inward. How did you find out if a book existed? Presumably, you asked a librarian, and presumably, you’d have to be monk or a scholar of some kind, as these books weren’t available to just anyone. Just gives you an idea of how lucky we’ve been in recent decades.)

Making it human

Whenever I visit someone I don’t know well — whether at their home or their office — I have a somewhat possibily irritating and nerdy habit of doing a quick browse of their bookshelves. For a book fanatic, someone’s bookshelves tells you plenty about a person and their interests, it also tells you what topics you can connect on.

This is similar to how the musically-obsessed connect over what’s in their iPods. On a recent trip to Paris, over an awkward group dinner, I suddenly noticed my fellow dinner-mate’s t-shirt as being that of a favourite band. Before too long, three of us on this end of the long table looked like we were having the time of our lives connecting over indie music, with our iPods out and browsing each others’ collections, with every recognition of a band name becoming a new talking point and an inherent measure of how closely your taste related to someone else’s. For us, iPod swapping was only necessary because we couldn’t see each other’s lists any other way. A digital book device that enables us to electronically share our book lists publically would result in a very similar conversational connection.

Obviously, there are many more unexplored scenarios. Considering that digital reading and book-buying are becoming a reality as the market expands, yet our needs are always partially constrained by physical contexts, how can we continue to create designs that delight, surprise, that enable serendipity?

This article is cross-posted at “Begin With An Idea“.

Published:
January 19, 2010 – 2:49 pm
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By steph
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The Master of Many, Part 2

Firstly, a (belated) Happy New Decade to all!

Before the holiday season, I wrote about how poly-expertise was possible. In particular, I did some basic arithmetic: if we kept at something — say, working at a particular job — for 5 hours a day, 5 days a week, that it’d take us just over 8 years to become an “expert” if we were to follow the Gladwellian 10,000-hour rule. That is, assuming we have an 8 hours’ work day but are actually effective for 5, and a few other assumptions. Best read all of that here.

So, what I’m going to is to show how, in practice, it’s possible to be a poly-expert over some time, even if you don’t try very hard. If you don’t have time to follow all the numbers and scheduling, feel free to skip right to the bit on why I think the numbers don’t actually matter.

Where did the time go?

When I started making these calculations, it occurred to me that I played a lot of music when I was little. Could we perhaps look at poly-expertise as a manifestation of habits that developed over time, that contributed towards being good at something?

From 7 years old to 21, including performance time, I averaged a couple of hours of practice a day + maybe 1 hour performance a week. (Mind you, that doesn’t mean I practiced every day or performed every week, it’s just an average.) The math: ((2 hours’ practice x 7 days) + 1 hour weekly performance) x 50 average weeks x 14 years = 10,500 hours. On paper, I was apparently already an “expert” musician before I had my first full-time job. In reality, given my age, I wouldn’t have been mature enough then to be a full-fledged musician.

It’s not hard to fit in 2 hours in a day even if you’re already working a full day’s work. There are 24 hours in a day after all, right? Even if you sleep 8 hours, there is technically still time to fill. So, I’d like to explore what happens to the time outside of sleep and work by looking at how I spent my “free time” throughout late high school, university, etc.

Let me give you an approximate breakdown of my schedule when I was in late high school:

  • 8:30am – 3:30pm: Classes. I often took the lunch hour to play with the music computer in the lab
  • 3:30pm – 5:30pm: Music rehearsal. (2 hours — not every day, but usually 2-3 days a week)
  • 6:00pm-8:00pm: Cook, have dinner, wash-up etc. (2 hours)
  • 8:00pm-midnight: Say, 2 hours for homework (I doubt I ever did that much), and 2 hours for something else, usually some kind of writing or reading. I was a nerd.

(For the curious, the “music computer” was Notator on an Atari. This was what it looked like. Come to think of it, that might have been what got me interested in usability in the first place…)

In my university years, my schedule was totally erratic, but I spent 10 hours a week either teaching or doing tech support over the course of 2.5 years. University weeks are shorter, we’re looking at around 43 weeks. That clocks up 1075 in preparation for my career in tech — that’s like 10% towards being an “expert”.

In my first few years of working full time as a tech-then-webby-sort of developer, my daily schedule looked something like this:

  • 8am – 9pm: Commute to work. Write on the tram/train. (1 hour)
  • 9am – 5pm: Work. (8 hours)
  • 5pm – 6pm: Commute home. Read. (1 hour)
  • 6pm – 8pm: Cook, dinner, wash-up. (2 hours)
  • 8pm-midnight: Something webby, I was bored with work. At that time, I did a lot of writing, say 2 hours.

Let’s say I kept this writing up for 4 years. Let’s be conservative and not count weekends and minus a few weeks for vacations, laziness etc. 3 hours x 5 days x 49 weeks x 4 years = 2940 hours. Without counting in the time I started writing in my late high school years, this figure doesn’t yet make me a very good writer, but I’m apparently (numerically at least) about a third of the way there.

Checking in on my “tech career hours” in the course of these 4 years: 8 hours x 5 days x 49 weeks x 4 years = 7840 hours. Add that up to my tech work during university year gives us 8915 hours. That was around 2002, a good 7 years ago, I’ve clocked up about the equivalent since.

How you use your time is how you get good at something

Okay, I think we’ve had enough of the arithmetic and the schedules. What’s my point here? My point is that anyone can be a poly-expert, and chances are all of us are experts in more than one thing. If you break down how you’ve spent your time in your youth, you might figure out how you got good at something over time if you’d kept at it.

I made a couple of important life choices very early. I stopped watching television regularly since I was 12 years old. Instead, I chose to spend my time filling my brain with stuff (usually books), playing music and making things. (I only became interested in television again in the last year or two.) Secondly, I don’t have children — it was a conscious choice, and a completely different topic of discussion for another time. But this means even after a long day of work, I have 2-3 hours at my disposal. That’s 15 hours a week, not counting time on weekends.

Let’s say I’ve made good use of my 15 hours a week over the last 10 years, and let’s give that the full 52 weeks a year: I could have easily become fairly accomplished in a completely different field.

If you spend just 3 hours a day, 6 days a week, and every week for 10 years, you’d hit your 10,000-hour mark. But is that really necessary?

The non-linear runway

In certain fields that are emerging (such as new disciplines on the web) where the field is not any older than 10 years at a stretch, logically it takes a shorter amount of time to become an expert. However, I’d argue that no innovation is an island, and for old hands, our expertise in related fields bring a lot of value. If you are now a social media expert or a user experience designer, work in anthropology or ergonomics would’ve been an amazing asset. If you are a DOM/Javascript hacker, a painful university year or two coding in C probably helped you out. It’s also worth noting that to be really good at something may not require you to be an “expert” — you have to know enough to solve problems that arise in that domain of knowledge.

Of course, this thought experiment is somewhat too linear, and probably much too literal. In my essay I argued that it’s possible that poly-experts are likely learn faster because we constantly throw ourselves into new and unknown fields, and we have a skill that’s finely honed: the ability to learn. Along with the ability to learn comes the ability to analyse, synthesise and evaluate — abilities that make someone good at what they do, and this matters when we look at someone who does different things and have the skills to switch context, or borrow cross-contextual concepts very fast. This makes the ability to arrive at an “expertise” a much less linear matter than just accumulating 10,000 hours.

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Published:
January 7, 2010 – 5:09 am
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Faking it real

At TED back in 2004, Joseph Pine talked about what consumers really want is “authenticity” in the experience economy. Yet, even now at the tail end of 2009, we’ve barely moved beyond the basic goods industry. We only have to walk into any shop to realise we’re still suffering from the hangover of the industrial economy that has never really gone away: the cheap supply of goods in order to have things available to the masses. What may have changed are shops for highly branded goods like the Apple Store. However, these are edge cases, not the majority.

Something that has fascinated me for awhile is how merchants choose to display or sell their goods. Talking about a recent trip to Melaka, I was wondering why our shops always have to look chock-a-full of stuff. When in our history did it happen that our shops need to be full of things? Was it meant to convey a successful business? Wouldn’t it have just shown many things remained unsold? Was there a point in the psyche of selling and buying where we realised no one would ever walk into an empty shop?

Pick a shopping district in your town or city, and you’ll see what I mean. This need to fill a shop means we had to get the goods from somewhere, the cheaper the better, for a fatter profit margin. But rather than waxing about economics, I’m probably much better placed to talk about craft, or maybe just about jewellery.

In my travels, it has become obvious to me there’s no longer such a thing as “ethnic jewellery”. If you’re looking for something locally handmade, firstly, be prepared to be lied to about the origin of what’s in the shop, Secondly, expect to only be able to find things similar to what you’ve already seen elsewhere. Most jewellery on the market seem to come from around Tibet, India, Pakistan, China and South America, and on rare occasions, Eastern Europe. Note that this doesn’t necessarily dictate the quality of what you can buy — I’ve seen stuff that has obviously been made cheaply, but also very high quality work. Looking carefully though, it’s not easy to tell the origin of the piece by its design. What then, is authentic, if “authentic” local handmade craft is apparently imported? Is tourism to be blamed for the market for “authentic” souvenirs to bring home?

The real consequence in this is not just whether we find value in authentic experience or not, but in our bid to seem authentic but commercially competitive, we have sacrificed regional identities and uniqueness through giving in to cheaper production costs of goods.

Published:
December 30, 2009 – 4:07 pm
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Visual language detection (sketch)

Whilst at StatusCampMontreal today, a few of us in the Internationalization session were discussing interfaces for switching to another language. I hit upon a possibly rather silly idea where you can use something visual to help predict someone’s language. This is only a rough sketch, so it’s probably not much use as it is to anyone right now, but perhaps this might come in handy for a better idea or become something that someone else can build upon. Note: this looks at a general problem and does not necessarily solves issues for status.net.

So, generally, there are two problems to overcome when a user encounters a multilingual site (imagine many languages) that may or may not be serving the correct language to them by default:

  1. a user needs to know how to switch to a different language
  2. a user needs to choose the correct language (their preferred language)

Bear in mind they are likely to be looking at the site in a language they don’t understand at this point.

My idea is more inclined towards solving the 2nd step. What if you could serve an image of a common object, and let the user type in the word they have for that object? The “common object” example I have here is an apple, but you may conceivably use images of the sun, the moon, a tree, etc.

The interface could look something like this:

Visual language detection

(In the top right corner I’m using a language selector that I’ve used in past designs, using the presence of different languages — in this case, Chinese, French and English — to convey that there are further language settings, an attempt at addressing problem #1).

Basically, we provide a way for the user to type into a textbox the name of the object they see. The idea is that they would do this in whatever language they are already comfortable in. (In my example sketch, I’m writing “epal”, the word for “apple” in Malay.) There are languages where some nouns are similar, so this may need to be repeated a few times for an accurate detection.

There are obvious flaws with this visual language detection method:

  1. if you can’t see the image — if you’re not a sighted user or if you’re using a device that cannot render an image — this cannot be used
  2. choosing culturally-neutral images might not be trivial
  3. there needs to be some way of indicating (with little or no text) that you’re supposed to type in the name of the object you see, and that’s a hard concept to convey
  4. from a user flow perspective, this could be very confusing to be suddenly served an image of an apple…

Some good things about this:

  1. you can conceivably make a decent language guess if you have a few images, and you only need a fairly limited corpus to search through
  2. a user won’t have to wander through a big list of languages they don’t care about in order to find the one that matters to them

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December 19, 2009 – 12:54 am
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The Master of Many, Part 1

This conversation really began a few months ago, from my self-reflective rambly essay on hippiesque, followed by my friend Stephanie Booth’s investigation into the idea of the “poly-expert”. The question arose over an informal chat: what can multi-talented or multi-skilled people call themselves that do justice to their poly-expertise, when the market seems only interested in specialisation and 3-word long job titles? How do we even go about self-branding?

How do poly-experts become who we are?

Today I’d just like to mull on what it means to be a poly-expert, and how you could have arrived at being one. I’m going to pretend to forget about the “what we call ourselves” question for a moment, and look at it through doing some basic arithmetic around how a polymath, poly-expert or generalist can possibly spend their time. If you don’t have the time right now (hah!) to read these two rather long pieces, let me synthesise here a couple of ideas that I want to expand on by pulling out some key quotes.

From my post:

Somewhere in the way we view what we, as respectable members of society, should do with our lives, we lose out the moment we think of ourselves as a cogwheel that can be good at only one thing. So many of the skills we possess in one discipline translate to another, it seems ridiculous to limit ourselves and fool ourselves into thinking that we were each designed for only one thing.

It’s a little like mastering languages. When you begin to know a couple of languages, the third, fourth and fifth language comes easier, because suddenly you have a much more flexible model of the world through which you can adapt what you see and interpret. As you encounter new things, they either fit into something you already know, or you create a new mental model.

Doesn’t it stand to reason that if we could pick up very different skills, that we should be able to be more efficient learners, and be more adept in more of the things we do?

From Stephanie Booth’s post:

The mono-expert builds his expertise on digging deeper and deeper and acquiring an exhaustive knowledge of his subject. He runs the risk of becoming blind to what is outside his specialty, or viewing the world through the distorted glasses of excessive specialization.

The poly-expert builds his expertise on digging again and again in different fields. In addition to being an expert in the various fields he has explored, the poly-expert is an expert [at] digging and acquiring expertise. By creating links between multiple fields of expertise, he avoids the pitfalls of excessive specialization — but on the other hand, he is often recognized as a superficial generalist rather than a kind of super-expert (because “you can’t be an expert in all those things, can you?”)

On a related note, Hunter Nuttall changed his blog tagline just two days ago to “personal development for polymaths”, and in a corresponding blogpost, he highlights some main points about polymaths and who they “are”.

Calculating “career time” as an expertise

I happened to have read Malcolm Gladwell’s Outliers, and maybe so have you. I’m sure you’ve at least heard about the 10,000 hours it takes to be an expert. I’m not saying I agree with him on the figure, but it’s an interesting guideline to abide by. There are many more points in the book about the secret(s) of success, but I’d just like to think about what this means for poly-expertise by getting it down to a simple practical matter — what do we do with our time? I’m going to start with the most obvious calculation: let’s take this apart and look at it from a “professional day-job” standpoint.

Assuming 40 hours a week make a full time job, to be an expert we’d need 250 weeks. (10000/40-hour week = 250 weeks.) Time off work for vacations and holidays and such ranges from 2-5 weeks on average a year, so let’s say it’s about 3, as an average of an average. With a “career time” of 52 minus 3 weeks, we’re at 49 weeks per year. 250 weeks/49 would give you just over 5 years, not 10, if you stuck at working in the same field of knowledge all day. (Side note: There’s interesting history about where the 8-hour work day comes from, but that’s out of scope of this discussion.)

However, anyone who’s tried to estimate how long something takes (let me put my project manager hat on) will know that most people are really effective for no more than around 5 hours a day. So let’s make that a more conservative estimate: 10000/(5 hours x 5 days a week) = 400 weeks. Let’s divide this again with our average number of weeks worked (49): and we’re at 8.16 years. That gets us a little closer.

But wait. Aren’t there 24 hours in a day? Is it correct to assume that an 8 hours’ work day is where we’re all at?

In my follow up post, I’m going to explore some basic arithmetic around the other 16 hours in the day. Let me just go away for a bit and make sure I got my numbers straight.

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Published:
December 16, 2009 – 6:22 pm
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