Here are some of those items from the article that I found particularly interesting, along with just a few thoughts.
2. Let’s think about how to do a better job of recommending “related” stories. Many search engines reveal items that are generally popular – that are highly ranked. Certainly we should design better filters, but we should also design better automatic information sniffers and surfacers that seek out stories of interest. Can we design better relational models so we can surface relationships between stories that are actually meaningful instead of the “also see” hyperlink that takes me to a story from five years ago that somehow got linked to the current one? Can we do a better job of making explicit the relationship between events at the local, national, and global levels? Can we design better tools for following story developments over time – even those stories that have non-sensational endings?
A lot of smart companies are working in that space. (At Sphere, we are providing related-content solutions, too.) I am also spending lots of my personal time thinking about this lately.
Related content is an area of increasing importance and the computational methods are likewise becoming more sophisticated, as research and understanding progresses.
News is becoming more personal, too, for better or worse. It is entirely possible to customize news in a way to only focus on certain types of news (local, sports, etc.) and ignore others. We may well start seeing something similar for related content suggestions. If a website understands a user’s preferences, they can be used to make decisions regarding related content. These preferences would not just be in terms of freshness vs. authority, but also preferences regarding topics/aspects of interest. Given a popular news item involving a person, their Web company and favorite vacation spot, is the user interested in the person, their company, other companies like it, that vacation spot, similar spots, a combination of some of those, etc.?
In this case, users should ideally be able to see, how the site arrived at their related content suggestions and alter those suggestions by changing their preferences, globally or just for that story.
3. Design for time-appropriate reading, and for use and reuse. Can we design a better way to earmark content than the current, simplistic URL bookmarking? What are better ways to support different temporalities of information and different consumption paces? Can we design ways for slow-burn stories to linger, while fast-burn stories are updated with new content?
Indeed, some stories develop over long stretches of time, while others move at a very fast pace. Here is a frustrating experience: Subscribe to a few news feeds and go away for a few days. Revisiting the content in a feed reader presents this challenge: Where to start reading? Beginning with the old content may be reasonable so nothing is overlooked, but a breaking news item may have completely resolved with the most current article.
Given a story, particularly one with an ending, smart ways are needed to visualize the story’s unfolding. Step-by-step timeline views are useful here. So are smart, automated summaries.
There are lots of opportunities for useful changes here.
Traditionally, the focus of HCI has been designing for people who actively use applications or interactive products. These individuals, commonly referred to as users, may be bank tellers operating a banking application, pilots setting parameters of an autopilot system, or customers using ATM machines. This viewpoint neglects a vast number of cases in which human interactions with computerized systems are less active and often unplanned, yet still meaningful. People’s needs are routinely ignored in these situations and the effects of information systems on their lives often go unnoticed. We term these people “incidental users.”
Examples include the customer at the checkout lane in the grocery store, who cannot make sense of the quickly scrolling item list on the screen (if that is visible at all) or airplane passengers, who realistically have no good idea about the state of their luggage or the condition of the plane.
The Web is full of incidental users and scenarios of incidental use, too. Here are some examples.
If a document is published online, it will likely be picked up by search engines. Furthermore, people may link to it, make copies, etc. Most publishers will have no good idea, what services access their document or how they use it.
URL shortening services have gained importance in real-time messaging services, such as Twitter. Every character counts, so it can make sense for the sender to conserve space by shortening URLs. The receiver of the message however has to determine whether the URL is trustworthy. Software plugins that expand the shortened URL are available which simplify the problem just a bit. More on this here.
Personalization is an important feature of many modern websites, particularly e-commerce sites. Personalization is achieved based on usage patterns as well as the user’s value judgments, such as product ratings. That process often ends up being less than transparent to the user.
The general public have become passive users of Google Map’s Street View.
Important lessons can be learned by examining whether one may be the incidental user of a service (or services) at a given time. Only being able to see the back side of a computer display may be a good indicator, but other cases are probably more subtle. Check out Ohad Inbar’s blog for more examples.
It is also noteworthy that some businesses profit by using scarcity of information as competitive advantage. The Web has served as a platform for companies that break into those industries and make previously scare information more openly available. The Redfin story comes to mind here as an instructive example.
The following video clip (found via Techcrunch) shows a Google employee conducting a brief survey with passersby at Time Square. It turns out less than 8% of the people were able to correctly tell what a browser is.
Graphical browsers have of course contributed significantly to the success and growth of the Web and I bet a lot of the participants routinely use a browser. I thought it was particularly interesting that a lot of them did not seem to distinguish between browsers and search engines though.
Search has become the main method of navigating the Web. Users have learned to rely on it. Maybe for some of those interviewees, browsers have mentally mostly disappeared then, as part of creating simplified abstractions of online tasks.
Usability can no longer keep up with computing: The products are too complex, too pervasive, and too easy to build. And in our absence, users and engineers are beginning to take over the design process. Five trends demonstrate the growing gap between usability theory and commercial practice – the “new realities” of computing haven’t been truly embraced by the usability community. The trends are, at a minimum, making traditional usability more difficult, if not irrelevant in the new paradigm.
I am certainly no usability expert, rather just curiously interested in the field.
Modern software, particularly social web and/or mobile applications definitely appear to pose new and different challenges – in many respects. The example of a location-dependent web service that incorporates user-contributed data seems particularly well chosen. It involves many different aspects, each of which could make or break the user experience.
As these new classes of applications are developed, researched and understood better, software development approaches also change, incl. introduction of new tools, algorithms and practices.
I don’t see, why the same couldn’t also happen for usability work. A lot of basic usability information has become near-common knowledge. According to the author:
[...] with the growth of the Web and usability, clients are likely to know the underlying usability principles, be familiar with the core heuristics, and have already solved the obvious “gotchas” in their products. They may even have in-house usability departments, labs, and protocols. Fewer and fewer clients need to be reminded of the basics. The heuristics we test for and baseline against are pervasive; at some level, we’ve put ourselves out of business.
On some level, I am inclined to take the above quote from the article as an encouraging sign of a maturing field. System administrators often strive to automate as many of their tasks as possible. Similarly, developers come up with automation tools and essentially means to achieve more in less time. Examples from other fields could easily be provided.
This can often result in people being able to start focusing on more advanced problems, which may not have been practical or feasible before. I bet a lot of people find it refreshing to focus less on educating their clients about the needs for basic work and rather focus on addressing harder problems.