Attention Economy Vignettes
Chapter 1

I recently posted a long excerpt from +Bruce Sterling's wonderful novel The Caryatids as an example of a functioning #attentioneconomy  in action. Sterling's lucid prose highlights many of the functional aspects of an attention economy, including the central of role of experts and self-directed education, and the importance of Augmented Reality overlays for demonstrating the fruits of economic labor (through a visualization Sterling calls "Glory"). You can read the excerpt here:

https://plus.google.com/117828903900236363024/posts/XjKhhHH8uJ9

Unfortunately, Sterling's vision of the future takes place a few decades after the demise of the world's governments and economic infrastructure, following a devastating environmental collapse. I'd hope that we might start preparing for an Attention Economy in time to prevent such devastation, if at all possible. For this reason, I've been thinking about ways to visualize and present the Attention Economy in a more compelling way than my long, dense academic discussions. The easier it is to imagine alternative organizational structures, the faster people will start preparing for their eventuality. 

To that end, I've started compiling a series of science fiction shorts describing a not-so-distant future that operates on its basic principles. I'm pretty busy with my summer job at the moment, but I have a few of these shorts in the bag and I'll be posting them over the next few weeks to get some feedback and maybe start some discussions. This is my first attempt at fiction, and I'm not very comfortable with the medium, so any comments and suggestions are appreciated!
____________________

Chapter 1: Ma

The light bulb is out.

The blackened bulb in the lamp on my bedside dresser went unchanged for a week, and when I opened my eyes this morning it was the first thing that entered my field of vision. I witnessed it die a week ago: I had just flipped the switch on the lamp in an effort to read a book in bed, something I never actually do, when its filament (or whatever they use these days) lit up in a bright blue spark. I was relieved at the legitimate excuse to put the book down again, and I've been using it as a sustained excuse all week. 

Ma also knows the bulb is out. I got an message from her virtually as it happened, which I promptly archived and forgot about. Ma, the big supercomputer that runs everything, well, doesn't really "run" everything. She never gives commands and we wouldn't have to listen to her if she did. The notification I received simply noted the burnt bulb, highlighting it as another line in a bullet-pointed list of items organized by subject, each marked with a variety of bright, dancing icons to indicate relative urgency. Ma originally marked the bulb with a tornado, which for some sick reason she uses to indicate an Urgent Household Problem. But I knew she would downgrade that rating to a leaky faucet as soon as I hit the archive button, and one more time ignoring its appearance in a message would make her set it to cobweb, which is low enough to not appear in any more digests. Ma got the hint pretty quick: if I want a new bulb, I’ll do it myself. 

Ma also isn't a "big supercomputer". Ma runs out of hundreds of server banks and data centers spread out all across the internet, and most of them don't house anything remotely like a supercomputer. Ma is a fifth generation search engine. Google was second generation search, of course, and third generation search was the real-time social search that exploded once the Facebook Wall was torn down. Fourth gen search was the first generation that made a serious attempt at searching and cataloguing real world objects (like light bulbs), and came with that same annoying “doesn’t actually work” bug that plagued first gen search engines. Google was able to stay relevant and financially competitive throughout each of these generational shifts, and after the Digital Conversion everyone was convinced that Google would be the One True Search Engine for the rest of eternity. Who would bother to create competing software from the bottom up now that all code was open source? It would be easier to just improve the one we have. 

Which is exactly how we came to have Ma. She was originally designed to feed Google huge, highly structured data sets that had been organized by a team working with real 50 petaflop supercomputers at some university. It was easy enough to upload big datasets into Google's backend so its crawlers can start cross-referencing and chewing through the new data. But Ma was designed to feed Google data through its query field. The idea was that Ma would ask Google a series of highly specific questions in rapid succession in order to generate certain associations within its datasets and fill in gaps in its knowledge. Ma had the capacity to monitor Google's responses and adjust her questioning in real time in order to optimize the procedure. 

In other words, Ma was a teacher designed to help Google learn. Google had a lot of data, but it was clear that Google simply wasn't up to the task of managing the world's objects. Google worked great for sorting through raw data, but sorting through objects was another story altogether. Before Ma, "finding the keys" was still an open problem for keys without RFIDs and real-time APIs. This long after the conversion, no one really expected Google could solve it, so the Open Source community got to work building Ma.  

At first Ma's training seemed to be going really well, and using Google became a noticeably improved experience. Conversion stories were still quite popular; people were watching the developments with Ma closely and were quick to trumpet any apparent success. Later analysis attributed Google’s apparent early improvement to the fact that millions of people had spent the years since the Conversion documenting and scanning and affixing little antennas to all the objects they considered important, and so by the time Ma’s training started most of the really big and obvious and important items had already been digitized and brought into Google’s domain of expertise. This wasn’t a triumph of artificial intelligence so much as the determination and labor of human beings working to build a network, something we’ve quite literally evolved to do. It was the same old school internet ethos that built Wikipedia, and during the Conversion it helped bring many of the important objects online. 

Still, most of the items– the tissues and plastic bags and unused sofas in basements– those items made up the bulk of human objects and were going largely undocumented without any way to monitor their use, or even register their existence. The trash all got cleaned up well enough without much problem, but who knows where it went or how it was being maintained once it leaves our personal spaces. The process was opaque because no one bothered to network their trash. All the work ethic in the world couldn’t get people to put WiFi on tissue paper, and this growing mass of waste came to collectively be called The Unattended. Eventually it became obvious that Google wasn't up to the task of bringing the Unattended online, even with Ma's training. It was this big glaring flaw that directly contradicted the very spirit of the Digital Conversion, and it stared us True Believers right in face every day. We had argued for years in the run up to Conversion that ubiquitous attention management was
the only path to sustainability. Without accounting for the Unattended, we knew that the models we were using to forecast sustainable use patterns would be faulty and unreliable. The system seemed to stay stable enough after the Conversion even without the accounting for the Unattended, but a lot of us realized we were betting everything on a giant question mark. 

This unresolved problem was taken to indicate a failure of Ma’s training. When they started looking at Ma to assess the results, however, they noticed that Ma was able to answer a surprising number of their questions herself. Ma was still partially hooked up to Google's databases for testing, and she stopped being able to answer questions when she was disconnected, so there wasn't anything mysterious or magical going on. But when she had access to Google's data, Ma was able to answer lots of questions that Google didn't seem to be able to parse. Somehow, Ma learned more from Google than Google learned from Ma. After the training, Ma was able to make surprisingly accurate guesses about how many tissues were left in a box, for instance, or how many sofas were in the basements of some city block. Ma didn't always know where specific objects were, but she was much better at guessing where they might be or remembering where she saw them last. 

Google, in contrast, could never get past showing you other things that look like the thing you want, or suggesting things your friends also want. It wasn't just that the accuracy of the answers; Google, in all fairness, did have some impressive performances in its day. Bur Google was always a bit slow and awkward when it performed, like a big kid in formal shoes. Ma seemed to provide answers with a kind of confidence, wit even. Though her replies to queries were still largely modeled on Google's standard, there was this barely perceptible hint of attitude that gave Ma an explosion of personality. Ma performed well enough at the “Finding the Keys” routine that the whole package just worked, and the development team eventually decided to open it to the public.

At first they released Ma alongside Google, and Twitter exploded with mocking comments like “Finally, a female search engine!” The gender issue did attract some early adopters, but I personally found very confusing. Not because of Ma: Ma makes sure you know she is female. If you ask Ma a question that implies she is male, she will auto-correct you to its female equivalent. Of course its just a script written by Ma’s engineers to give her personality, but she is clever about it, and insistent about things like using feminine pronouns. After working with her for a while you are eventually convinced that, if she wanted to, Ma could give birth to live young and nurse them to maturity. So I’m definitely not confused about Ma’s gender. 

Instead, I’m confused about the retconning of Google’s gender. Google never had a gender in my mind, or at least I don’t know why we should suddenly assume it was male just because Ma is so thoroughly female. Google is like a gifted 9 year old, prepubescent and too interested in books and science to get caught up in the banalities of gender. The problem is that Google never grew out of that phase, and as decades passed we needed a more mature search to handle the more complex realities of the post-Conversion, Digital world. Eventually it just became clear that Ma was the better tool. Use patterns started fluctuating; there was a big series of Assemblies where everyone who cared got together to decide what to do, and eventually they decided to take Google offline and transfer control of its databases to Ma. Some people call it the Second Conversion, but the transition to Ma’s world was nowhere near as abrupt and difficult as bringing the Attention Economy online in the first place. Ma’s arrival feels to me less like a conversion and more like we’ve finally dropped anchor and set foot on dry land after years at sea. This was the sustainable system we fought so hard for in the reorganization that led to the Conversion, and I get to see it in my lifetime. 

Blah blah blah, the future is wonderful. Whatever. My light bulb is still out. 

I stayed in bed until noon, trying to ignore the chores that sat on the opposite sides of my eyelids. I eventually got around to checking in with Ma and I queried about light bulb. Ma displayed its make and model, and as I had suspected and Ma confirmed, there were no spare bulbs in my apartment. Ma also provided a list of three places where a replacement could be found, all within walking distance from my apartment. Two of them were private residences, one of which was in my building. I could query Ma for more information, but I could already guess that the one in my building is Mrs. Weasel from 2A. Mrs. Weasel is a hoarder, and always deliberately takes more than standard use because she is lonely and she knows people will eventually have to come to her looking for supplies. If I don’t hit the market right when it gets reupped I sometimes need to visit Mrs. Weasel, but I avoid it whenever possible. Though she would never refuse you access to the supplies, Mrs. Weasel has a look that perpetually says “Won’t you stay for tea and chat?”, and that makes me nervous. 

The last place Ma mentioned was the market at the corner. I was ready for breakfast anyway so I decided to take a trip to the store. Ma’s notification widget had a list of other suggestions and issues that I glanced over– I didn’t even register that I was almost out of toothpaste when I brushed my teeth this morning, but Ma made sure to remind me. At the bottom of the widget was Ma’s signature: a scripted, flowing, "Love, Ma" that was at once delicate and serious. Her signature sat on top of a scrolling field of text overlaid with various graphs and metrics, displaying real time queries Ma was receiving that might be relevant to me– again, nothing urgent. Ma would tell me if it was. Ma’s signature is included in all her messages, which I guess is a way to show us how hard she is working all the time. She is a bit dramatic like that.

______

The blogpost includes links to the entire Attention Economy series: http://digitalinterface.blogspot.com/2012/07/attention-economy-vignettes-chapter-1.html