“Generative art” is a blanket term for any creative work produced in part through programmatic or algorithmic means. “Playful generative art” makes use of highly technical disciplines—computer programming, statistics, graphic design, and artificial intelligence—to produce chat bots, digital poetry, visual art, and even computer-generated “novels.” These pieces may be motivated by serious social or political issues, but the expressions are decidedly unserious, often short-lived or quickly composed. Creators working in this medium are rarely artists first—as programmers, designers, game developers, and linguists, they use the tools of their trade in unexpected and delightful ways. Generative art also has much to teach us about issues at the intersection of ethics and technology: what is the role of the artist in a human/machine collaboration; what is our responsibility when we design programs that talk with real people; how do we curate and study ephemeral digital works? Digital artists, writers, technologists, and anyone interested in media studies are invited to attend.
"Your margin is my opportunity" ~ Amazon CEO Jeff Bezos
Last week while on a day trip to Seattle, I decided to make a stop at Amazon’s first“Brick and Mortar” store, in the University of Washington neighbourhood of University Village.
I had two goals in mind. I wanted to see if I could get a personal book recommendation from an employee and I wanted to purchase a book without leaving any data. I am not averse to providing personal information, but I like to have the choice.
Now the company was moving into the physical space. How consumer-centric would it be?
As I wandered into Amazon’s first physical book store, I was struck by nostalgia for the small independent bookstores. Amazon has gone full circle. The small independent bookstores were decimated by massive, multi-city block stores such Chapters in Canada and Barnes and Noble in the US. In turn, Amazon’s entry into the online bookselling business in the late 1990s had, by the early 2000s, badly bruised the competition. Books began to take a back seat to lifestyle merchandize, kitschy cards, stationary and stuffies. Amazon grew bigger, squeezed publishers on pricing, and further backed the physical bookstores into a corner. Books were longer realizing a sustainable margin for the big chains. By 2010, Amazon dominated book selling through online sales of print books, and leading the way in eBook sales and its proprietary electronic reader – the Kindle.
The Seattle storefront reminded me of a modest neighbourhood book store in a great community setting. There was a cupcake shop and kids toy store nearby, and kids were playing on an outside playground. People were coming out of Amazon chatting and smiling, heading off to get a coffee and talk books.
An employee greeted us inside the store. She held an electronic gadget in her hand and smiled warmly as she beckoned toward the inside of the 7400 square foot store. In the very centre of the room, sat a huge flat screen TV. I am not sure if it was 4K, but the three kids sitting in front of it sure looked happy. They were playing the iOS-born Crossy Road using Amazon Fire TV.
Next to the TV was a table bedazzled with Kindles of all makes and models. A salesperson was talking to a customer about Amazon’s Digital Assistant Alexa (allegedly named in tribute to the Library of Alexandria). “Alexa” is actually the wake-up word used to activate Amazon’s Echo, a voice command device for the “smart home”, which answers questions, reads audio books, orders pizza, and becomes increasingly better at offering suggestions and choices the more data “she” has to analyse.
The more questions you ask of Alexa and the more you interact with it, the more it can “help make your life easier”, assures the salesperson. The customer is clearly unsure as to how all this works and suggests that it might make too much personal information freely available.
The salesperson quietly tells him that the information collected by Alexa is used to enhance the customer experience; to make shopping easier. Developed for the voice-activated “smart home ecosystem”, Alexa also personalizes search results for pretty much anything: books to vacations and, of course, helps the user order or restock items through Amazon.com.
Not having access to Alexa in Canada, I was completely enthralled, but I was getting data-saturated.
I refocused on books and decided to ask the nice employee who greeted us at the door if she might be able to help me find a book. She whipped out her device and asked me what title I wanted. I said I was looking for a recommendation of some titles. I told her I wanted to buy something for a friend who was interested in sports writing, more specifically, newspaper sports writers’ work outside of their journalism work.
She frowned and said she was sorry. She could only search by title and that she did “not know all the books in the store.” She suggested I try the Sports, Entertainment, Biography and Reference sections. She assured me that all the books in the store were 4 or 4.5 stars. I asked what that referred to and she said all the books in the store were curated according to the reviews at Amazon.com.
I walked to the Sports section and browsed some titles. I found an anthology of sports writing. It looked good. I checked the price on the back – $14.95. Knowing that Amazon would use the online price, I walked back to the employee and asked what the barcode on the cards attached the shelf was for, pretty certain it was a way to get the online price. She told me it was for internal inventory control.
On my way back to the shelf I ran into another employee. I showed him my book and asked if I could find the online price. He led me to a price checker. And there I discovered the book was listed at $11.99. Perfect, I thought. I did not have to give any personal data and I will get a nice discount. As I turned to leave, the employee suggested I also download the Amazon app. All I had to do was click the tiny camera icon on the app I could scan any price by using the bar code on the shelf to get the lowest price.
I said I was told the barcode was for internal inventory control. He looked baffled and told me they use the code to allow customer access to the most up-to-date online discounts. He noted that the online prices were always fluctuating “for various reasons” and that instead of changing the physical cards on the shelf, they just do it electronically. Makes sense.
I download the app and head to the children’s section. Already I knew by even using Amazon’s WiFi on my phone my data footprint was becoming visible, but I was not planning to log in to the app, just use it to check prices.
I scanned one children’s book and I got the prize in Canadian dollars – more than the American cover price. Not good, but not too surprising given the current exchange rate.
I scanned another title. This time, I was instructed to log in. I would just go buy my books. I did not HAVE to log in anyway, I could always use the scanner, but if I did log in would I get a better price based on my own shopping habits? Would I get a “personalized” price? I did not see how they could be that customized (yet) since the sales person was scanning the book itself. And as I did not log in to the app, I have no idea what steps I would have been taken through on my phone.
Ha, I thought. Minimal data breadcrumbs and I have two books, an enjoyable shopping experience (for the most part – still wondering about the internal inventory control comment – and I have US cash so I don’t have to worry about the weak Canadian dollar in the purchase.
“You have saved 35%!” the beautifully-dressed salesperson told me. Great, I think, and hand her my two American twenty-dollar bills. Her brow wrinkles and she says, “I am sorry. We are a cashless store.”
What?? I have no US credit card on me, and using my Canadian Visa is going to wipe out my discount and probably even add to the list price. I ask why in the world Amazon doesn’t take cash.
She smiles and says, “We want to replicate the online experience as much as possible.”
“But, you’re a physical store with physical books and I have physical money.”
She was sorry, she said.
I handed her my credit card. I could almost feel my data downloading into the Amazon vortex as my card slid through the machine. So much for avoiding the data trap…
“Have a wonderful day!” I heard from behind me as I headed out the door and thought about the rumoured expansion of Amazon’s physical stores into everything, not just books…
 The location opened in the fall of 2015, with plans for a second one for San Diego, and according to some industry experts, as part of rollout of hundreds more.
 (Just last week Amazon released two new “siblings” for Alexa: the Echo Dot and Tap).
Design a usable website. This is undoubtedly a lofty goal, but one that is increasingly crucial to business success in publishing. Web usability is really a form of mind reading. First ask: what do users want and need to do on a website, and then follow those answers toward designing content that presents information in a way that guides users to the appropriate end goals. The International Organization for Standardization (1998) defines usability under the following metrics:
Efficiency: the level of resource consumed in performing tasks
Effectiveness: the ability of users to complete tasks using the technology and the quality of output of those tasks
Satisfaction: users’ subjective satisfaction with using the technology
These focus areas provide a simple place to start when evaluating any website. If a business goal of a certain company is to have a visitor sign up for an email newsletter, the web design must address the process the user undertakes to do this.
1. Is it efficient: does it exclude unnecessary steps like entering a phone number or other irrelevant information?
2. Is it effective: once they complete the online form, have they actually been signed up for a newsletter they want to receive?
3. Are they satisfied: does the user feel like they accomplished a task?
Asking these questions about efficiency, effectiveness, and satisfaction of experiences is the first approach to usability. Let’s take a look at each of these factors in more detail.
Efficiency: Better Make it Quick
Soothsayers and divining rods were once used to understand the world and human behaviour, but thankfully, modern science provides other more reliable solutions. Neuroscientists have come up with different ways of actually reading the human mind. The most common mind reading device in the field of web usability research is eye-tracking, which involves a camera following the eye as it moves around a display (science 1, soothsaying 0). Sirjana Nahal (2011) measured first impressions of websites using one of these eye tracking programs, and Nahal reported the following conclusions. The first is that users spent less time on websites deemed “unfavorable” (Table 4.8). Perhaps this is not a shocking revelation, but it underlines an important principle of web design and usability. People know what they are looking for, and if a website does not offer it, they will go elsewhere (and quickly, no more than the time it takes to hit the back button). The conclusion that users spend less time on “unfavorable” sites also reinforces the importance of connecting people with the content they are looking for. This idea will be further explored in the following section on effectiveness in web designused commercial water slides for sale.
Nahal also looked at the ways users prefer to view web content, and these preferences are broken down by design categories. The following table outlines those conclusions.
The information in the above table is in keeping with basic principles of design that apply to print materials like magazines, newspapers, and others. Where those print technologies have traditionally had barriers to access that require a relatively sophisticated knowledge of print production to make a viable product, the online world is a democratized, open-source environment that encourages access for all. This generalization is certainly debatable, but at the same time, how useable a website is can be directly correlated with how much attention is paid to these principles of design.
Another resource from Dahal (2011) is an assessment of how much time users fixated on different areas of a simple website during the visit. That information is summarized in the table below.
There are two things worth paying particular attention to in this information. The first is just how little time is spent on any one element of the webpage. 6.48 seconds is the most time a website can expect to hold the attention of an average visitor. 6.48 seconds. Given this minuscule window, it is crucial that websites are built with absolute efficiency in mind.
Effectiveness: Help Me Help You
Steve Krug offers a very succinct guide to best practices for web design in his 2006 book, Don’t Make Me Think: A Common Sense Approach to Web Usability (2nd Edition). The underlying argument Krug makes is that users will not do things on a website that take extra mental effort. Krug offers that users like obvious, mindless choices. A big part of what makes some choices more obvious than others is how they are labeled, and how the navigation of the site is laid out. Krug (2006) argues that the lack of physicality on the internet makes a webpage’s navigation system absolutely crucial to a user’s experience.
Website navigation should:
Help us find whatever it is we’re looking for
Tell us where we are
Give us something to hold on to
Tell us what is here
Tell us how to use the site
Give us confidence in the people who build the site
(adapted from Krug, 2006, p. 59-60)
With so many important tasks placed on the shoulders of navigation, a great amount of attention should be paid to how the elements of navigation (menus, sections, and utilities as a start) are designed and communicated. The application of conventions that communicate physical space and direct user actions is a major factor in how effective a website is from a usability standpoint.
Krug’s model also suggests that users scan websites instead of reading them. He compares them to the billboards we pass on the highway at 100km per hour. If it the information on the site can’t be read at that high speed, it is not an effective communication tool. One way to achieve quick and effective readability is to reduce the number of words on the page to focus user attention on exactly what you want them to do.
Krug describes how users interact with instructions on webpages: “The main thing you need to know about instructions is that no one is going to read them—at least not until after repeated attempts at ‘muddling through’ have failed. And even then, if the instructions are wordy, the odds of users finding the information they need is pretty low” (Krug, 2006, 42). Anyone who has tried to sift through an online help or FAQ page (here is an example of a wordy instruction page from the SFU Library) knows that this is absolutely true. It is a lightning-fast scan of the material, a quick attempt to click around and see if you can intuit your way out of your particular issue, and then a jump back to the help page for another nugget of information to try. Krug’s emphasis on the speed in which users can access the information they need mirrors the findings of Dahal, and many other usability experts and researchers. Milliseconds will dictate whether or not a person is going to use a website to do a task.
Satisfaction: Ahh. That’s the Stuff
The subtitle of Seth Godin’s 1999 book Permission Marketing: Turning Strangers Into Friends And Friends Into Customers has become almost cliche in the internet marketing canon. The principles laid out in Godin’s book still hold, and point to a fundamental shift in marketing that came about because of how the internet changed how we talk to each other. Godin argues that in order to make a sale online, a company must ask permission using accepted web practices. If a business is serious about making an impact on their bottom line through a website (this impact is not restricted to sales of goods, and should be thought of any way that an online presence can enhance customer experience), serious attention to design and web usability is a good place to start. Providing a satisfying customer experience is about more than just giving them the product they want. Now, more than ever, it is about getting people involved in a community (that lives online, primarily), asking them to participate in the community, and having them help build a brand reputation on behalf of the business. This ability to engage in and with a community should absolutely be considered when designing a usable website.
Research into the factors that contribute to user satisfaction on websites helps point the way toward what a business should do to keep their customers. Kincl and Strach (2012) studied user satisfaction on 44 different educational institutions’ information-based websites by documenting satisfaction levels before and after the use of the websites. The researchers found that content and navigation were key areas in determining overall satisfaction, and that “users perceive high-quality websites if they achieve what they visited the site for. This success in user activities is subconsciously reﬂected in website assessment” (Kincl and Strach, 2012, p. 654). In short, people are satisfied when the website they visit does what they expect it to do. A simple sentiment that is anything but simple to implement. Another interesting finding from this study is the fact that users care less about what the researchers term “trivial” data like the colour of the site than “non-trivial” data like the content (Krug and Strach, 2012). That is to say, an average user would still rate their satisfaction of an unpleasantly-coloured site highly if they found the information they needed. This serves as a reminder that while attention to the look of a website is certainly important, in the end, users want substantive content (and to be able to find it).
The 3 Most Important Things to Remember about Usability
If you were scanning this article like a billboard, this is where your eyes should stop scanning and start reading.
1. Your website needs to communicate really, really quickly. In under 7 seconds.
2. Your website needs to be easy to use. It should be obvious where a user should focus, and then what action they should take at each step (and there shouldn’t be many steps).
3. Your website needs to give a user exactly what they think they need. A website is a promise, and it is up to you to define that promise and then to deliver on it.
Dahal, Sirjana. 2011. “Eyes Don’t Lie: Understanding Users’ First Impressions on Website Design using Eye Tracking.” Master of Science, Missouri University of Science and Technology.
Garrett, Sandra K., Diana B. Horn, and Barrett S. Caldwell. 2004. “Modeling User Satisfaction, Frustration, and User Goal Website Compatibility.” Human Factors and Ergonomics Society Annual Meeting Proceedings 48 (13): 1508-1508.
Godin, Seth. 1999. Permission Marketing: Turning Strangers into Friends, and Friends into Customers. New York: Simon & Schuster.
Green, DT and JM Pearson. 2011. “Integrating Website Usability with the Electronic Commerce Acceptance Model.” BEHAVIOUR & INFORMATION TECHNOLOGY 30 (2): 181-199. doi:10.1080/01449291003793785.
International Organization for Standardization (ISO). 1998. Ergonomic Requirements for Office Work with Visual Display Terminals (VDTs), Part 11: Guidance of Usability. Geneva, Switzerland.
Kincl, Tomas and Pavel Strach. 2012. “Measuring Website Quality: Asymmetric Effect of User Satisfaction.” Behaviour & Information Technology 31 (7): 647-657. doi:10.1080/0144929X.2010.526150.
Krug, Steve. 2006. Don’t make Me Think: A Common Sense Approach to Web Usability. Berkeley, Calif: New Riders.
Morris, Terry (Terry A. ). 2012. Basics of Web Design: HTML, XHTML & CSS3. Boston: Addison-Wesley.
Snider, Jean and Florence Martin. 2012. “Evaluating Web Usability.” Performance Improvement 51 (3): 30-40. doi:10.1002/pfi.21252.
Somaly Kim Wu and Donna Lanclos. 2011. “Re-Imagining the Users’ Experience.” Reference Services Review 39 (3): 369-389. doi:10.1108/00907321111161386.
Other things to consider and discuss:
There are many institutions that attempt to categorize the “Top Websites” in the world at any given time, and Alexa is one of them. In addition to statistics on the most visited pages, Alexa provides information on category-specific website usage. For 2012, the top websites under the category “Publishing” were:
This top ten list show varying degrees of attention to design and usability. The standouts are the two Wiley websites, which both have a clean look and a clear path for users to follow, and the Audible website, which does works well to present a product, give key information about the product, and direct the user to an action (to “Get Started” using the product). Audible is a subsidiary of another company that is very good at directing user flows in a publishing environment (Amazon, of course).
Keeping in mind that we are publishers, and not math people, what is an algorithm?
At first glance, the algorithm sounds like a concept out of a particularly frightening chapter of a calculus textbook, but there is no reason to fear the concept. In Kevin Slavin’s TED Talk, “How Algorithms Shape Our World”, he defines algorithms as “basically, the math that computers use to decide stuff”. This simple definition is an easy way to think about the algorithm, but what “stuff” are computers using to make the decisions?
Wikipedia summarizes algorithms as the following:
An algorithm is an effective method expressed as a finite list of well-defined instructions for calculating a function. Starting from an initial state and initial input (perhaps empty),the instructions describe a computation that, when executed, will proceed through a finite number of well-defined successive states, eventually producing “output”and terminating at a final ending state.
To make this a little easier to understand, think of an algorithm as a program that is capable of going through a huge pile of information and making sense of it. The logical output that comes from this process is defined by the user at the beginning, according to the things they need it to do, and the order and way in which it is asked to do those things.
Jeff Hunter (2011) provides this helpful list of what commonly used algorithms do:
Searching for a particular data item (or record).
Sorting the data. There are many ways to sort data. (Simple sorting, Advanced sorting)
Iterating through all the items in a data structure. (Visiting each item in turn so as to display it or perform some other action on these items)
Understanding the basic idea that an algorithm is a function that allows for categorization of large amounts of information, it is easy to see where an algorithm has value in the digital world. Computer information is no more or less than a big pile of data, and algorithms give us shortcuts to processing these enormous data sets.
A basic type of algorithm is a sorting algorithm, which can take a set of data (let’s say, 100 books of different sizes), and sort those books in a specific way (according to their weight, for example). The Computer Science Unplugged website for children gives a good example of how a couple different algorithms could work for a weight sorting task, time- or space-complex task. There are many other types of algorithms commonly used daily, such as the search algorithms that display Google results, and each in their own way is display results or classifications based on how the algorithm works with the data.
Ok, so besides basic sorting tasks, what can algorithms really do?
Searching, Prioritizing, and Providing Biased Content:
Very complex algorithms can accomplish an endlessly diverse number of tasks. The Google search function is one example that we are familiar with, and now that you know what a basic algorithm does, this makes sense. Google search is sorting through an enormous amount of information, and using various functions to come up with the “best” end product—the exact website you were looking for. Seomoz.org has a an entire section devoted to understanding the Google search algorithm, including an interesting timeline that tracks all of the changes to that algorithm beginning in 2000 and cataloguing each year’s changes up to the present. While some of the language on that site is technically advanced (and intimidating), it is interesting to see the huge number of changes every year (Seomoz estimates that Google changes its algorithm up to 500-600 times a year), and to guess at what those changes mean for how we receive content.
Another implication of algorithm technology that is related to Google searching is found on Facebook. There, algorithms determine what content appears on a News Feed based on what content the user has previously “liked”. Eli Pariser, president of MoveOn.org talks about the danger of this kind of filtering in another TED Talk that is also embedded below. Pariser argues that people have to be careful about letting algorithms decide what news they see based on their likes, because a healthy news diet consists of both the things they instinctively like (chosen with the gut), and the things that could enrich an understanding of the world by pushing people to discover things outside of a current sphere of knowledge. Pariser goes further to say that algorithms are taking the place of traditional news editors (who were human, of course). Where the human editor acts as a gatekeeper and guide to information based on what they know about the audience and what they think the audience needs to know about, the (current, as of his talk) algorithm is only making judgments based on the most superficial, instinctual, and hedonistic of our online habits.
Assessing physical space, stealing jobs from humans:
Algorithms are also used for measuring and accessing physical space by robotic machines. The Roomba vacuum cleaner is able to clean a room because of an algorithm that works out the dimensions of the room and then sends it to each part of the room, systematically. The 60 Minutes feature that is embedded at the end of this paper gives another example of this kind of algorithm. There, robots are programmed to pick up warehouse shelves and bring them to workers at the moment they need to access the materials to pack them. These two examples show that algorithms are capable of computing physical space, and then making an assessment of a complex set of data to make a certain “choice” about a desired outcome.
Algorithms in conflict: crashes, glitches. What happens when this stuff breaks down?
The most frightening thing about algorithms concerns their volatility, and their ability to “speak” to one and other and inform the decisions that another algorithm makes. In “How Algorithms Shape Our World”, Kevin Slavin talks about the potential harm that can be done when these algorithms work outside of human control when he references the Crash of 2:45, or the “Flash Crash” that happened on the U.S. stock market on May 6, 2010. The “black box trading” that algorithms execute, in conjunction with “High Frequency Trading” contributed to the second largest point swing, and the largest point decline, on the Dow Jones Industrial Average in history (Lauricella and McKay, 2010). On how and why this happened, Slavin (2011) explains that in these algorithms, “We’re writing things that we can no longer read. We’ve rendered something illegible”. The term “black box trading” highlights the fact that some of the code works behind a wall of understanding that even the people who wrote the original formula no longer have access to.
When it comes to algorithms that build on each other and change outside of human oversight, the cause for concern is slightly larger. There are many art forms that talk about this potential problem. A lot science fiction literature and pop culture deals with this fear we have about creating things that outpace humanity and then turn on it. Think of Isaac Asimov’s I, Robot, Cory Doctorow’s Down and Out in the Magic Kingdom, The Matrix, and Battlestar Galactica. The fact that these messages pervade popular culture (and have done so for hundreds of years) speaks to an understanding that humans might just be too smart for their own good. And while algorithms represent a truly fascinating and powerful tool, extreme caution is wise when implementing automatic systems, particularly when those systems control finances, social lives, access to information, or any other frightening prospect.
A basic understanding of what an algorithm does, of what it has the potential to do, and of who is controlling the technologies that rely on these equations to make decisions about our lives gives us the power to ask critical questions and make sure that humans are in control of the technologies created.
At least, that is the hope.
There are a number of fun web videos on the topic of Algorithms. Please enjoy those below, and feel free to share others you know about in the comments section here.
The TED Talk that started it all: How Algorithms Shape our World by Kevin Slavin.
60 Minutes Feature: “Are Robots Hurting Job Growth?”. Alarmist title aside, this is a video that shows some very cool uses of algorithms in the manufacturing and production sectors in the United States.
Eli Pariser’s TED Talk: Beware Online “Filter Bubbles”
Another TED Talk, this time about the algorithmic editing of the web and how that editing function affects the content we see online, and thus the reality of the internet we experience. Because these algorithms are now our editors, Pariser argues that we need to make the algorithms focus on a balanced news diet, including some junk food and some of vegetables.
At PopTech 2012 Jer Thorp gave a presentation on Big Data. This is a visually gorgeous look at different types of data being displayed in very interesting ways.
Thorpe looks at how that data trails (think of yourself as a data slug that leaves behind a trace of everything you do in an electronic form) we leave can be examined, visualized, and ultimately understood. He also breaks down the “architecture of discussion” by mapping Twitter conversations that happen around a New York Times article.
He also warns that data is the new oil, and that the fragmented microorganisms that compose oil are not dissimilar to the fragmented pieces of our souls that make up public data.
And finally, from The Onion: Are We Giving The Robots That Run Our Society Too Much Power? This is just one of my favourite robot-related videos of all time. My apologies, it doesn’t have embedding code, but it is worth clicking the link.
Green, Scott A., Mark Billinghurst, XiaoQi Chen, and G. J. Chase. “Human-robot collaboration: A literature review and augmented reality approach in design.” (2008).
Hunter, Jeff. “Introduction to Data Structures and Algorithms.” December 28, 2011. http://www.idevelopment.info/data/Programming/data_structures/overview/Data_Structures_Algorithms_Introduction.shtml Retrieved January 13, 2013.
Lauricella, Tom, and McKay, Peter A. “Dow Takes a Harrowing 1,010.14-Point Trip,” Online Wall Street Journal, May 7, 2010. Retrieved January 15, 2013.
Pariser, Eli. The Filter Bubble: What the Internet Is Hiding from You, Penguin Press (New York). (2011).