An appealing aspect of the video was the deferential “digital assistant,” a bow-tied avatar that “understood” your schedule, your current projects, your trusted colleagues and their work, plus a myriad of information sources that might be relevant to your needs. (Yes, it also looked like a younger version of Bill Nye, but without the sense of humor.) It added a human touch, of sorts, creating an interface that simulated human interaction—freeing the actual human to ponder, speculate, and apply himself to actual problems.**

Let’s leave out the cosmetic issues for the time being. Voice recognition, voice and visual synthesis are not small problems, but they are gradually becoming mainstream. What intrigues me is the filtering or “tuning” of data that such a digital assistant would need, in order to carry out the tasks in the video.

First of all, the data—and its related metadata—would have to be standardized to a high degree. Statistics on rainfall, land use, and the like would have to be not only accessible but recognizable at a high level of abstraction—in this case for a world map simulation that allowed for various “what if” scenarios. This kind of visual rendering can be done today, but at the cost of many, many programming hours.

Second, there needs to be a more flexible, human-like approach to varying conditions or assumptions in the data. Computing today is by nature linear and logical, while human thought—at least the kind we value most—is intuitive, spontaneous, and able to reach conclusions with incomplete data. While it may often be flawed, the human process is decidedly non-digital.

Technophobes fear the competition of a computing process that competes with our own intuitive process. After all, back in 2001, we all shivered when HAL decided we were expendable, right? (Come to think of if, how do you know this blog wasn’t written by a cyber agent, softening up humanity for the takeover?)

Just kidding. Computing that transcends today’s linear model will eliminate more mundane jobs, to be sure, but it will also open up new ones. If digital assistance is truly that—giving us time to do the important stuff—then we’ll be better off.

– John Parsons

Now that I’ve mixed way too many metaphors, the question still remains: How can we pull back from the urgent needs of each day long enough to consider what it all means—to come up with wise, long-term, and sustainable plans for our life on earth?

We could blame the pace of information and its technology, the global economy, or the alienation of postmodern society. (For that matter, we could also blame reality TV, fluoride in the water, or the Mayan calendar.) The point is that blame will not actually solve the problem. Even those with good intentions, and a resolve to go “back to basics,” must still function in today’s real world. Unless cave dwelling is the plan, we are all faced with far too much information, and far too little time and resources to deal with it.

One of the standard replies to this dilemma—one that I actually believe—is that technology can actually be part of the solution. The danger, however, is in believing that technology is the whole solution. Neil Postman observed** that all technology has unintended consequences, and that we are too often blinded by the promise of technology—or by the fear of what technology will take away. (Does my smartphone’s GPS help me find my destination, or is it destroying my natural awareness of place and direction?)

So, what does the information overload solution look like? How do we actually stop wielding the mop long enough to look for the faucet?

I would start by consciously doing what my instincts already do: set a higher standard for immediacy and relevance. If I have not actually read a particular e-newsletter in, say, three weeks, then unsubscribe. (If another three weeks passes, and I haven’t done a search for something among my back issues, then I should feel great about unsubscribing.) Do the same for RSS feeds, Google Alerts, ad nauseum. Consciously choose what you’re looking for; don’t let others choose for you.

More important than adjusting and turning off noise-laden channels is the choices we make on whom to listen to. Someone who is thoughtful, insightful, and considerate of your needs is always a better source for relevant, actionable information—even if he or she is trying to sell you something. Intuitively, you know who these people are. Apply that intuition to your choice of trusted sources.

Now, if there were only a better way to apply this intuition to the myriad of information sources that overwhelm your day. Wouldn’t it be great if there was a reliable, universal “trust index” of some sort? If such a thing actually existed, and was really tuned to my needs and desires, then perhaps I could take a breath and start living my life in this digital chaos.

– John Parsons

The explosion of democratic, non-curated content—largely from social sites and the blogosphere—has come at the cost of credibility. The study found that 51% of users believed that only a small portion (or none!) of such content is reliable. This fits with a finding later in the study. Americans believe that the Internet is of critical importance in politics, and yet (paradoxically?), “that it is not yet considered a tool that voters can use to gain more political power or influence.” Clearly, more information and more accessibility do not mean actionable or useful knowledge.

Applying old paradigms is not the answer. Traditional media companies have tried to gain traction with new media, only to garner ridicule. Witness CNN’s ongoing Twitter/YouTube fetish—glibly treating the medium as if it were a live feed to a known, reliable source. The laughable results underscore the real problem: social media is a giant party line* with no operators, facilitators or, frankly, a mechanism for promoting self-restraint.

Because the medium is so democratic, a Yale scholar has equal standing with the shouting madman—at least in the eyes of the average user surveyed in the Annenberg study. Most of us can tell the difference between these extremes, but when the sources are less extreme, the burden of filtering out noise and retaining useful information increases. Since we’re only human, we give up, and label the medium as inherently unreliable.

So, how can we add reliability and credibility to Internet-based information? How can we fine-tune all our searches and collected heaps of data, to extract the necessary needles from our virtual haystacks.**

Software innovation is surely part of the answer, as I’ll explore in future posts. Surely, there must be a way to harness all that computing power to find reliable, creditable, and meaningful information, based on each user’s needs and preferences. Let’s not neglect the human element, however. Intelligently harnessing the collective intuition of billions of humans (yes, with their permission), could be a way to make the Internet a more credible source for actionable information.

– John Parsons

One of the report’s main points—“E-Nuff Already” (a phrase coined at Annenberg)—is well taken. To the information overload from texts and emails has been added a host of new communications streams. I can now be tweeted, re-tweeted, poked, updated, liked, tagged, invited, posted, and notified on dozens of platforms and programs. New programs have been hatched to unify and organize these (letting me blast one message over multiple social channels, for example, or sorting all my tweets and DMs into separate lists. All this does is make my drowning more organized.

What makes the message flood worse is that social media removes an already shaky filter on content. What was once a stream of irresponsible emails has grown to a torrent of unqualified noise. The Annenberg study found that only 14 percent of users found that information from social sites was reliable. To be sure, wise users of social media select their circle of followers with care, but often at the cost of limiting access to new information. When the flood of messages and related links becomes too great, the affluent and/or famous simply hire assistants—human “filters” of content. Welcome to the 20th Century.

The Annenberg report asks how long it will be before Americans say “E-Nuff” to social message proliferation. This is easier said than done, however. Social media is highly addictive—especially the simulated feeling of connection that it generates. Rather than view tweets and updates as email run amok, let’s look at what social can do to restore some sanity to the unfiltered mess.

In theory, one’s social network is the ideal medium for fine-tuning content to meet individual needs for knowing the data’s importance and relevance. If those who recommend/forward/comment on information share your values and priorities, then messages from within your circle are worthwhile. Right? In practice this breaks down, due to limitations in our perception or our friends’ character—or both. The principle is still a good one, though.

What if messages could br rated not only by content (basic search), and by social proximity (from someone in or near your circle), but also by the sender’s “trustworthiness index”? (A different label would be the sender’s “bullshit index” or BSI.)

Under this scheme, if your best friend sends you reams of lolcat images, bad jokes or political rants, he or she could still remain your friend, but you’d have the option of raising his or her BSI, which would in turn keep such messages at bay—perhaps notifying you that Larry sent 22 such messages, but also one or two serious ones, and a few in between. Who knows? Maybe Larry’s input could even help you make critical decisions on some future datum.

Messaging—email, text, or social—is not a black-and-white, all-or-nothing proposition. Intelligent “tuning” (using more sophisticated rankings of content, users and trustworthiness) has the potential to make us its masters, rather than its slaves.

There’s way more in the Annenberg announcement, which I’ll discuss in my next post.

- John Parsons

In the early 1980s, I heard a story—apocryphal, maybe—that scientists had barely begun to examine the data collected during the six manned Apollo moon missions. In fact, it was thought unlikely that we’ll ever finish sifting through all that information, much less the mountains of space exploration data collected before and since.

More recent examples come to mind. Tradeshows generate detailed information on hundreds of potential customers, but we’re barely able to develop meaningful relationships from that data. (Generating a mass email follow-up doesn’t count; it just shifts more data and responsibility to someone else.) We’ve all been there. Collections of business and personal information—articles to read, graphs to ponder, images to appreciate—increasingly fills space in dusty virtual filing cabinets, all labeled “ROUND TUIT.”*

We have far more data than we can possibly convert, unaided, into wise, meaningful action. With each new technology development, we humans are falling further behind. Just setting up and maintaining our various knowledge management widgets takes more time than we actually have—never mind reading the results. As I said at the beginning: Help!

What can mere mortals do? Is there a process, a discipline, or even (whisper it) a technology that can help us tame the beast, and really turn the flood of data into meaningful, actionable information—and also leave room for us to live our lives?

This blog will be an ongoing exercise in discovering just such a path—hopefully with humor and practical insights. I’ll try not to go all Andy Rooney (God rest him) on you, with curmudgeonly comments about the good old days. Ultimately, the good new days of information technology are worth pursuing.

In the coming months, I’ll explore new possibilities—ranging from purely academic and speculative projects to practical commercial developments. The answer to information overload will not be simple, but is ultimately achievable—especially if we stop cursing the darkness and explore our greatest strengths.

– John Parsons

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