It is my view that contextualization is the most important issue in networking. If the history of advances in IT can be linked, as I believe, to bringing technology closer to consumers/workers, then the ultimate step is to make tech a participant in our lives. We’re seeing early initiatives in this direction with things like personal assistants, but from the very first “assistance” has tended to run up on the reef of context.
The most popular early question asked of these assistants was “What’s that?”, which reflects a very basic truth; an effective assistant is an almost-human but invisible companion. It sees what we see, knows what we know, which means it shares our context. It’s that context-sharing, in fact, that makes it valuable. However, it’s a lot easier to say we’re going to create a ghost-like companion than it is to make that companion real.
Contextualization to create ghost companions who are literally partners in our lives presents some major technical and social challenges. The most obvious, and usually most problematic, is the problem of protecting privacy. Something that knows everything we know is both a companion and a potential thief and predator. If “the network”, meaning a set of network-connected applications and database resources, know everything about us, we can bet that most of that everything will end up being hacked or revealed through the fine print of user terms of service. A major breach of confidentiality would have such dire legal consequences that the risk alone would deter most companies from exploiting contextualization fully.
Context is important for our ghost companion because to be useful rather than distracting, it has to mimic our behavior. Anyone who’s walked around town with a young child while trying to complete an adult mission knows the challenges that a behavioral disconnect can create. To make an application or service mimic behavior means it has to understand what drives it, and that’s what I mean by context.
We have context today, but in nearly all cases we obtain it by having it communicated to our “ghost companion” directly. That’s bad because a companion should share our context, not be informed of it. Anything less than sharing means that our ghost is too ephemeral to be truly useful to us. It needs a foot in both worlds, so to speak.
What are the technical ingredients of contextualization? The best answer lies with our own senses. Our visual sense is by far the richest of all our senses, meaning that it conveys the most information in the least time. We must start any formula for context with the notion that our ghost companion must see what we see. That doesn’t necessarily mean that our ghost has to have virtual eyes and full visual recognition intelligence, but it does mean that it has to be able to infer or construct at least a loose picture of what’s around us, what we would see if we scanned our surroundings.
The second key contextual ingredient is mission. We behave differently when walking down a street to the office, versus walking down the same street to go to lunch, versus walking down the street while shopping. Even something like shopping creates different missions; we might be looking for “a gift” or we might be looking for a specific pair of running shoes or a computer.
The third contextual ingredient is recent stimulus. A text, email, phone call, or other interaction with the outside is often a behavioral trigger. It can, for example, create a change in mission. These stimuli are appeals to our senses, intrusions from the outside that could change what we do, drive what we try to do.
The final ingredient in context is history. We can understand the future only through the analytic filter of the past, because people are individuals with their own way of looking at things and their own balance of logical versus emotional responses. We may, in the future, face the spooky possibility that a service could read our thoughts, but until we cross that bridge the best way to interpret the other contextual elements is by reviewing how we reacted to them before. Do I jump puddles or walk around them?
We already have the means of acquiring all of these contextual elements, at least in the sense that we have the information available. The real work in contextualization is to do the acquiring and exploitation of contextualizing information within three constraints, which I’ll call the “Three Laws of Contextualization”.
The First Law is the consumer’s privacy must be protected, at least to the point where contextualization doesn’t add to risks to privacy already routinely faced. In my own view, it should be possible to create a framework for contextualization that could, down the line, absorb some of today’s ad placement functions, as a way of responding to likely regulatory intervention.
The Second Law is contextualization must create enough value to the end consumer to cover any costs they’re expected to bear. Those costs could be direct fees or indirect costs associated with the surrender of personal information. If the latter is the case, the trade-off of cost/benefit must be clear.
The Third Law is every stakeholder in the contextualization process must have benefits that cover their ROI expectation when compared to costs/risks. We can’t assign somebody an unprofitable role in contextualization just because we don’t know how to make the role profitable. A way must be found.
If protection of user privacy is indeed the prime issue (which it clearly is), then that means that contextualization has to frame contextual data somewhere under explicit user control. You do not allow services and applications to collect and correlate because that would necessarily give the owner/provider of that process access to user information that would blatantly violate privacy concerns. There would only be two possible solutions—have the user’s own device do the contextualizing by absorbing outside information on demand, or have a “trusted agent process” hosted somewhere perform contextualization on behalf of the user.
Either of these two mechanisms would, in my view, depend on the notion that contextual information was present as what I’ve previously called an “information field”. An information field is published knowledge about something specific, and it’s emitted by everything that we would consider to be a part of our environment. Information fields live in our ghost’s netherworld, and by sensing those fields our ghost companion can create context without having us force-feed it. None of the field providers would see any of the other requests for information or their results. This would limit the ability of an information provider to use contextual information in such a way as to identify the requestor, or at least identify them enough to pose a risk.
An example of this relates to location. Misuse of information to facilitate stalking is one of the major public policy concerns regarding “IoT” or related services. If a given user, while on a given street, were to ask for nearby retail locations providing a given product, and if that user then looked at websites, and if that user had a cookie identifying themselves as perhaps a young female, having all that information would be enough information to make it possible to intercept the consumer.
One point this should make clear is that the information used to “contextualize” advertising could not be collected in such a way as to personalize the consumer. A contextual analysis of a user’s behavior might suggest ads, but the suggestion of what ads to show should be made by the user’s device or trusted agent, not by the ad source. This could have significant implications on having contextual services offered by websites who inherently know the user’s identity, such as social-media sites.
There are clearly a lot of dimensions to contextualization, more than I’m going to attempt to cover in a single piece. What I plan instead is to do three more, one on the information fields and their implementation, one on the trusted agent, and a final piece on how AI could fit into things. I can’t predict the exact timing of these pieces because I’ll treat other key industry news as it comes (as usual), but I’m hoping that over the next couple weeks we can complete them all. As always, I’ll be posting the availability of each piece on LinkedIn, and that’s the forum I’d encourage anyone to use in commenting or making suggestions.