Posts Tagged socialnetworking
Infographics: How reliable are they?
With the social media flood comes a torrent of infographics, most of which focus on presentation instead of information. It reminds me of the “mediaglyphics” in yet another Neal Stephenson novel: The Diamond Age. In the futuristic novel, mediaglyphics are used by corrupt governments and broadcast media to inform and entertain a mostly illiterate population. Infographics aren’t much different: they blast the reader with colorful line graphs, maps, and pie charts to present an implicit and oversimplified argument.
I’ve found many of these infographics to be packed with spelling and grammatical errors. For example, try to find the error in this visualization of U.S. debt holders. With enormous font sizes and few words, any spelling or grammatical error really stands out. Such easily identifiable problems make me question the integrity of the statistics (and implicit arguments) these infographics present. Where did the data come from and how reliable are the sources? Many infographics do not provide references, so how am I to know that it isn’t just some ten year old kid making this stuff up? What if multiple sources produce conflicting results? In such cases, it’s almost guaranteed that the infographic creator just picked the result/data that best furthered his or her argument. Lastly, what information is not presented? When reading an infographic, I always wonder if I am seeing the whole picture. With so little information actually presented, I have no doubt that most of these infographics leave out plenty, especially stuff that hurts the creator’s argument.
I admit that infographics pique my interest in a subject to which I haven’t given much thought. However, with minimal content and questionable integrity, they may be no more than chartjunk.
Fixing the frustrations of the digital nomad
Current computing technology consists of a mishmash of devices, ranging in size, portability, usability, and design lifetime. Users are tied to their desks no longer: the future lies in mobile devices, and improvements to increase mobility and usability are key in the coming years. Without the following improvements, I think most users’ computing experience will become very frustrating. I’m hoping we’ll see:
A holistic computing solution
Everyone splits their computing time between a whole pile of devices: cell phones, media players, laptops, netbooks, desktops, and gaming consoles. Even typical cable TV boxes have a hard drive and user interface. The purposes and capabilities of such devices is becoming increasingly diverse and will probably continue to do so in the short term. However, it’s becoming a real pain to use a standalone device for a different task. Carry a cell phone for voice and text messages. Carry a laptop or netbook for working on the go. Carry a media player to listen to music. When at home, many people switch from a laptop to a separate desktop PC. It would be great to see some consolidation in order to reduce frustration with dragging around multiple devices and learning the quirks of each.
Since most people aren’t running weather prediction simulations, a single small mobile device would be sufficient for most people’s computing needs. Ideally, something the size of a cell phone would combine the functionalities of a phone, camera, media player, laptop/netbook PC, and even desktop PC. No longer would people with multiple devices need to synchronize information or become familiar with multiple interfaces. A single device would provide a user with most of the computing power and capability that he or she would need without the hassle of dragging around a separate phone, media player, and laptop. The device would be designed such that it could easily support and interface with different user input and output methods.
Improved user interfaces
Improved interfaces in mobile devices would make for a better user experience and improve productivity. With multiple gadgets to haul around, each comes with a different interface with varying levels of usability. For the most part, the smaller the device, the worse the user experience becomes. A desktop computer with a keyboard, mouse, and giant monitor provides a solid experience for most, with both ease of input and output. A netbook, however, may satisfy a user’s computing needs, but may cramp usability and productivity with its tiny screen and uncomfortable keyboard. Even worse, web browsing and writing emails or text messages on some cell phones can be nearly impossible. Personally, my experience with multi-touch phones has been horrible, since most of the time the phone selects something other than what I intended. Rethinking and improving the physical and software interfaces would permit a shift to a cell phone-sized holistic computing device.
Improvements to both physical and software interfaces would provide huge benefits for the end user. With respect to physical interfaces, improving multi-touch surfaces would be a big step in the right direction. Input methods that are simple and accurate would make phone calls, text messaging, and web browsing on mobile devices much more enjoyable. Output methods should extend beyond a tiny three inch screen, such as a wearable HUD or projector similar to that used in MIT’s SixthSense. With regards to software interfaces, most cell phone operating systems provide horrible user interfaces which make the simplest tasks a real pain. Most of these software designs inherit from heavyweight PC interfaces where input is made easy with keyboard and mouse. Mobile developers should focus on increasing usability by making tasks require the fewest amount of user inputs possible.
Behavior and activity recognition
Computing systems of tomorrow could predict a user’s intentions and act upon these predictions. With the introduction of accelerometers, GPS receivers, light sensors, cameras, and microphones in cell phones, plenty of research has provided ways to recognize user behavior and activities. Such research can help provide an augmented reality for users, pointing out suggestions as to what a user could do based on his or her surroundings, current activity and learned preferences and behavior. For example, a user traveling in an unfamiliar city could get instant suggestions as to where to eat when he or she normally takes a meal, with a mobile device providing directions to restaraunts that match the kinds of foods the user normally eats. A HUD would allow the device to paint a path directly on the streets to take without the user staring down at his or her phone. A device could automatically perform Internet searches and return data relevant to what a user is doing, whether it be retrieving a weather report before a user heads to the beach or providing real-time flight delay information as a user drives to the airport. Such intelligent systems could interact with the physical world and turn on the lights or adjust the temperature at a user’s home before he or she arrives. Also, behavioral and activity recognition would eliminate the need for user-generated Twitter and Facebook posts, performing automatic updates whenever a user changes activities or does something unusual.
Better inter-device collaboration
Figuring out how to get cell phone pictures off the phone and onto a computer can be a monumental task. It’s even more enjoyable to get a projector to correctly display a presentation on a laptop. Nearly every slideshow presentation I’ve witnessed, in classes and in conferences requires each presenter to wage war with his or her laptop and the projector to get the presentation to display properly. Improving inter-device communication would make everyday computing more seamless and a lot less frustrating. For example, a slideshow presentation could be loaded on a mobile device and a user could walk into a room with a projector, with the mobile device automatically connecting wirelessly to the projector and displaying the presentation. There would be no cables to plug in, no display settings to modify, and no buttons and inputs to fidget with on the projector. Synchronizing and moving data between different devices stands to gain significant improvement, for people are constantly upgrading their cell phones and laptops as well as sharing their data with others.
Longer design lifetimes
I’m guessing I’m not the only one with a pile of old hardware that’s worn out from too much use or discarded due to obsolescence. More robust devices with longer expected lifetimes would reduce the pile of useless junk in the closet. This would be especially helpful for mobile devices, which often wind up in mud puddles, toilets, or under someone’s steel-toed boot. Modular construction would allow for periodic upgrades without throwing away the whole device. An effort towards longer lifetimes and upgradeability would also significantly cut down on the amount of toxic e-waste.
Longer battery life
Most cell phones don’t last past a couple days of standby or two hours of talk time. Most laptops don’t make it past three or four hours. With an increased focus towards mobile and ubiquitous computing, improvements in battery technology, power savings, and battery recharging would do wonders. Apple has a new battery design in its latest laptops that double battery life, but more strides in this direction are needed. Efforts on power-conscious radio communication and CPU utilization will contribute to power savings through better software. Lastly, harnessing available energy sources such as motion, body heat, and the sun will also allow mobile devices to run unplugged for longer periods.
In general, these issues are what I think mobile computing needs in order to really take off. The current experience is haphazard and lacking, requiring a mobile user to carry multiple devices with poor interfaces and short battery life. With future applications, mobile devices will do a lot more than allow phone calls, web browsing, and text messaging. They will further the integration of the cyber and the physical world, helping a user interact with the environment and the Internet in ways currently unimaginable.
“When you control the mail, you control information”
Newman had the right idea: with a communication infrastructure, the end users aren’t alone in leveraging control over the information they communicate. Intermediaries have just as much control as the creators and the intended recipients. This might be true for mail, and it’s increasingly becoming an issue with the internet.
The most visible privacy issues have been raised with the introduction of social networking: Facebook’s Beacon being one of the most infamous, with Facebook secretly collecting your online activities to generate targeted advertisements. More recently, software designed to control and monitor children’s internet usage was revealed to actually transmit all internet activity, including instant messages, back to the companies that designed the programs. The list of abuses and potential abuses goes on and on and will only get worse. The introduction of cloud computing and the shift to thin clients mean that third parties are handling more and more personal data. The more opportunities others are given to handle our personal information, preferences, photos, browsing habits, and documents, the more opportunities exist for the abuse of that control.
Social networking and the monitoring of internet habits is only the tip of the iceberg. The social networking concept is quickly moving beyond the confines of the Internet and integrating itself with the physical world. The concepts of participatory sensing, body sensor networks, and smart homes/offices will see the introduction of internet-linked sensors placed everywhere. Cameras and microphones will soon be on every street corner. Temperature, humidity, and other energy monitoring sensors will be commonplace in every home, all linked to the internet. Even now, most cell phones come equipped with GPS, accelerometers, and microphones, allowing for activity recognition and localization. This “information saturation” will allow any developer to design an application that makes all kinds of weird discoveries: with body sensor networks and smart phones, rush hour traffic can be monitored in real time, local nightlife hotspots can be easily discovered, and suggestions can be made on how to save energy based on water and electricity usage in your home.
While the integration of the internet into the real world sounds cool, imagine what someone could do if your sensing information got into the wrong hands. Would you really want your health insurance company to know your heart rate or blood pressure at any time of day? Would you really want everyone to know that you waste the most water out of everyone who lives on your block? Would you want a crazed stalker to know where you were at any moment or to learn your daily activities or routines?
Privacy and security is going to be an increasing concern as sensor networks become more commonplace and integrated with the internet. While I was at UVA two weeks ago, Prof. John Stankovic mentioned that security and privacy in sensor networks is a huge problem and unfortunately, little is being done in this area.
A recent article by a UCLA student illustrated some of the problems with participatory sensing and presented some general solutions. Disclaimer: as part of the lead-in on her article, she says: “the developers I work with might say [my research area] is about telling them what they should be doing—which I must admit is the goal of this article.” When someone says they know better than you, it’s time to run, not walk, to the nearest exit. That said, I do agree with some of the things she says. The author argues that a general framework should be designed for all participatory sensing applications that allow for user privacy management. The frameworks should allow a user to easily understand how the systems work and how to control the release to the outside world of personal sensor data and inferences. Ultimately, the author argues that data generated by a sensor network that you own is yours to control and distribute. Third parties must respect the wishes of the content generators.
The author doesn’t go into fine-grained detail about how to ensure the preservation of an end user’s privacy wishes. I could imagine some kind of CA could help verify that those third parties which access a user’s content/sensor data are who they say they are. Some kind of feedback mechanism could allow a user to see where his or her sensor data went and how it was used. If a third party abused a user’s data, the CA certificate could be revoked, effectively tarnishing the reputation of that third party. Most likely, encryption would have to be introduced to ensure nobody but the permitted third parties could access a user’s data. Unfortunately, encryption is very energy and bandwidth heavy for low power wireless sensors.
We all know the wrong way to go about privacy with the experiences of Facebook and its tacked-on privacy measures. Initially, Facebook provided little privacy controls with no framework at all to allow a user to control access to his or her information. Even now, the privacy controls for Facebook are hard to access and even harder to understand what they do. A user has no fine-grained control over adjust who can access what content and exactly how your information is being shared with third party applications and advertisers. A comprehensive and user-oriented privacy framework installed from the ground up would help stop the mishaps that are common with social networking. Such a framework would come into its own with the increase in participatory sensing.
On that note, it’s time to get a few cell phones and start a participatory sensing application of my own to provide motivation for some research problems. The possibilities are limitless and I can throw privacy to the wind (for now). Unfortunately, as the author of the ACM article mentioned: researchers and developers don’t think about privacy, they think about research problems and cool applications. In a small-scale research environment, the information is mine to control since I control the sensors, the application, and the release of any data or inferences from the data. But, if anything were to be released into the wild and become popular, a framework for end user privacy control would be indispensable. I certainly don’t want some nutcase knowing when and where I’m sleeping.
Pandora Radio: Mixed bag
I’ve decided to branch out from my usual Internet Radio fix and experiment with Pandora. There’s been a lot of rave reviews out there, and I recall reading a Slashdot article about the data mining algorithms that go into determining your preferences (or maybe that was Last.fm). I’ll probably mess around with Last.fm to see the differences, since Pandora definitely has its highlights and drawbacks.
The interface is great since I just have to fire up a web browser and cookies automatically log me in. There’s no messing around with a software mp3 player and picking out the correct format so the player can interpret the stream. Sound quality is okay, but it seems that some tracks are better than others.
Nearly all the reviews I read said that Pandora was excellent in picking out songs they liked. I don’t entirely agree with this. In the web-based interface, you name an artist or song you like and Pandora plays music based on particular musical qualities of the artist or song. It seems that for me, when I name an artist or song in my existing mp3 archive, one of three things happens, each with about equal probability:
1. Pandora plays a song I’ve already got in my mp3 collection. Many times it isn’t even the same artist of the initial artist/song I specified, which makes it kind of weird. It would appear as though the preferences/data mining engine is almost too good, but this definitely isn’t always the case.
2. Pandora plays something that seems almost completely orthogonal to what I specified. For example, I put in Bruce Springsteen and it played something from Megadeth with lots of screaming and out of control percussion. I’m not sure how this relationship was determined, but it definitely didn’t give me what I wanted.
3. I actually hear something new that sounds similar to the artist/song I put in. In these cases, there definitely seems to be a relationship between the original song or artist I specified and what Pandora plays. This is the case I would prefer.
Pandora definitely doesn’t live up to all the hype — its preference/similarity determination seems to be either spot on or way off. Most of the time it seems to work, but I would rather hear something new than something I’ve already got in my mp3 collection (of course Pandora doesn’t know this). That’s one of the reasons I’ve been listening to Radio Paradise — they play all kinds of stuff I’ve never heard before and a wide enough variety to keep me coming back. One of the big features of Last.fm is that it can determine your preferences from your existing collection, so I may have to give that a try to see the differences. It seems that like most of these “Web 2.0″ apps, the data mining and social aggregation algorithms sort of work, but not enough to be really cool.
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