Group items tagged

collective intelligence is not as dependent on individual intelligence as first thought. Having more women in a group improves the collective intelligence, because it raises the level of "social sensitivity." Another important factor is letting everyone talk equally, rather than having the loudest or most opinionated people dominate the conversation.

Just as a tissue is a new, bigger level of organization for a bunch of individual cells, these new social structures are a new bigger level for individual humans. And in both cases the new level breeds emergence. New behaviors emerge from the new level that were impossible at the lower level. Tissue can do things that cells can't.

optimizing groups with more women and more democratic discussion is just as important as casting your crowdsourcing net far and wide.

Forrester Research defines digital intelligence this way: The capture, management and analysis of data to provide a holistic view of the digital customer experience that drives the measurement, optimization and execution of marketing tactics and business strategies."

Two years ago, the two greatest Jeopardy champions of all time got obliterated by a computer called Watson. It was a great victory for artificial intelligence--the system racked up more than three times the earnings of its next meat-brained competitor. For IBM’s Watson, the successor to Deep Blue, which famously defeated chess champion Gary Kasparov, becoming a Jeopardy champion was a modest proof of concept. The big challenge for Watson, and the goal for IBM, is to adapt the core question-answering technology to more significant domains, like health care. WatsonPaths, IBM’s medical-domain offshoot announced last month, is able to derive medical diagnoses from a description of symptoms. From this chain of evidence, it’s able to present an interactive visualization to doctors, who can interrogate the data, further question the evidence, and better understand the situation. It’s an essential feedback loop used by diagnosticians to help decide which information is extraneous and which is essential, thus making it possible to home in on a most-likely diagnosis. WatsonPaths scours millions of unstructured texts, like medical textbooks, dictionaries, and clinical guidelines, to develop a set of ranked hypotheses. The doctors’ feedback is added back into the brute-force information retrieval capabilities to help further train the system.

For Watson, ingesting all 2.5 million unstructured documents is the easy part. For this, it would extract references to real-world entities, like corporations and people, and start looking for relationships between them, essentially building up context around each entity. This could be connected out to open-entity databases like Freebase, to provide even more context. A journalist might orient the system’s “attention” by indicating which politicians or tax-dodging tycoons might be of most interest. Other texts, like relevant legal codes in the target jurisdiction or news reports mentioning the entities of interest, could also be ingested and parsed. Watson would then draw on its domain-adapted logic to generate evidence, like “IF corporation A is associated with offshore tax-free account B, AND the owner of corporation A is married to an executive of corporation C, THEN add a tiny bit of inference of tax evasion by corporation C.” There would be many of these types of rules, perhaps hundreds, and probably written by the journalists themselves to help the system identify meaningful and newsworthy relationships. Other rules might be garnered from common sense reasoning databases, like MIT’s ConceptNet. At the end of the day (or probably just a few seconds later), Watson would spit out 100 leads for reporters to follow. The first step would be to peer behind those leads to see the relevant evidence, rate its accuracy, and further train the algorithm. Sure, those follow-ups might still take months, but it wouldn’t be hard to beat the 15 months the ICIJ took in its investigation.

The beauty of such Big Data applications is that they can process Web-based text, digital images, and online video. They can also glean intelligence from the exploding social media sphere, whether it consists of blogs, chat forums, Twitter trends, or Facebook commentary. Traditional market research generally involves unnatural acts, such as surveys, mall-intercept interviews, and focus groups. Big Data examines what people say about what they have done or will do. That's in addition to tracking what people are actually doing about everything from crime to weather to shopping to brands. It is only Big Data's capacity for dealing with vast quantities of real-time unstructured data that makes this possible.

Much of the data organizations are crunching is human-generated. But machine sensors — what GE people like CMO Beth Comstock called "machine whispering" when I talked with her this past summer — are creating a second tsunami of data. Digital sensors on industrial hardware like aircraft engines, electric turbines, automobiles, consumer packaged goods, and shipping crates can communicate "location, movement, vibration, temperature, humidity, and even chemical changes in the air."

the number of Google queries about housing and real estate from one quarter to the next turns out to predict more accurately what's going to happen in the housing market than any team of expert real estate forecasters. Similarly, Google search queries on flu symptoms and treatments reveal weeks in advance what flu-related volumes hospital emergency departments can expect.

I have not created any new way of writing. All I'm doing is writing computer programs that mimic the way people write. Going back to the Elizabethan sonnets, Shakespeare or one of his contemporaries created the 14-line iambic pentameter poem, where the rhyming pattern was 'a-b, a-b, c-d, c-d, e-f, e-f g-g.' G-g being a couplet at the end. By line 9 there has to be a turn in the poem, so there has to be a phrase like 'yet' or 'but.' The first line is typically a question, which acts as a title. All of them are 10 syllables in each line... they have to go in the rhythm of that pattern. If you do an analysis of sonnets, you'll realize that about 10% of sonnets violate those rules. But they do it only in a very particular way. Even that formulation of violation is itself constrained... Once you have all of those rules you then write algorithms that mimic those rules. It's a very different kind of philosophy from artificial intelligence.

The methodologies are extremely old, just like the methodologies of writing haiku poetry are very old. An Elizabethan sonnet is 14 lines - that is a line of code if you think of it that way. The code is constrained. So all genres, no matter what the genres are, are a form of constrained writing.

anticipatory systems. 

Increasingly, rather than waiting for us to tell them what we want, in the form of a search query or command, they'll prompt us with suggestions.

Here's a simple definition of anticipatory systems. Think of them as artificially intelligent services that are aware of external context — including ambient inputs like time of day, social connections, upcoming meetings, local weather, traffic and more.

more than 85% of U.S. adults turn to social media for connecting with friends or family, according to Pew Research. News is not the primary reason we turn to Facebook.

According to Digimind, 62.5% of companies use Twitter to glean market intelligence, surpassed only by LinkedIn (69.4%). Facebook? Less than 50%. 

Pew Research finds just 4% of people list Facebook as the primary way they get news, even though a whopping 78% stumble upon news while on Facebook despite not looking for it. Newsy information, in other words, is not Facebook's raison d'être. Friendship and personal communication are.

For the Xbox to be able to turn on, identify who you are, and log in to your profile at a moment's notice--simply at the sound of the voice command "Xbox on"--it needs to do something a bit creepy: It has to be listening to what people are saying in your living room all the time.

Microsoft almost definitely is not recording, let alone uploading and archiving, every sound that happens in your living room 24-7-365. That said, the fact remains that there is a microphone in your home that's always live and connected to some super-smart computing devices--and a very distant server.

Expect Labs made a smartphone app called Mind Meld that demonstrates their listening tech expertise. Mind Meld can listen to the online conversation of a group of people, and detect what they are talking to such a high level of automatic detection of content and context that it can magically suggest online sources of information that might interest the group.

H.G. Wells describing the “world brain” as a  “complete planetary memory for all mankind.”

As a Google engineer told author Nicholas Carr, “We’re not scanning all those books to be read by people. We’re scanning them to be read by our AI.”

Email remains a workhorse for marketers: It’s cheap and reasonably effective

According to an April 2013 Economist Intelligence Unit survey of US and UK web users, email ranked as among the top outreach channel at each stage of the purchase process, from introduction, to final prepurchase assessment to post-purchase follow-up.

The greatest percentage of marketers still felt challenged to create relevant and compelling content that will really draw in recipients. This ranked as the No. 1 challenge among B2B and B2C respondents to achieving their marketing objectives, but it was also considered the most effective tactic, cited by 71% of B2B marketers and 65% of B2C marketers. If marketers can create strong content, they believe it really does work at converting consumers.

social media is becoming a skill, not a job. Companies like Intel and Dell and IBM are leading the way in broadly distributed social participation, giving thousands of employees the opportunity to win hearts and mind in social and with smart content.

This decentralization of social communication has widespread ramifications for social media management software vendors, as it puts additional emphasis on triage and workflow tools.

The days of one social media manager handling Twitter, Facebook, Linkedin and the rest is coming to a close (as is the era of the one or two person content marketing team) and the same way all of us have a corporate email address and phone number, we’ll all (or nearly all) have a role to play on behalf of the company in social and content marketing, eventually.

According to the many advertising leaders we surveyed, connected devices and wearable technology--or, more broadly, the Internet of things--are top of mind for 2014. But where the last decade of digital experimentation has generally made technology front and center of an experience, the feeling is that the general relationship with technology has now matured to a point where it doesn’t need to be the star of the show. Instead, people are predicting a more seamless integration of technology into brand’s efforts. Or, as Scott Prindle, partner/chief digital officer, Made Movement puts it: “I think we'll see interesting opportunities to use technology to save us from technology.”

We'll see a trend towards ambient intelligence where our devices learn about our individual habits and interests, anticipate the kinds of information we're looking for, and surface it at the right time and in the right place. Our technology will be doing more work for us in the background, helping to free up the time that we're currently spending staring at screens.

It's better to try to invent the future rather than predict it.

The first wave: Experience design

The modern design challenge is to define a great experience for a consumer comprised of a range of touch points, in various cases composed of interactions with several devices, retail experiences, personal contact points, software interfaces, physical mechanisms, data, and software intelligence.

We are systems designers now.