Everybody talks about the “cloud” as if it is a digital savior. A beautiful white fluffy (free) cloud on a blue-sky day. Sounds nice, huh? But what if it’s a storm cloud? Today – there is a mad rush to move pictures, video, and event private data to the cloud. We live in a world today of constant connection. We’re blessed with unlimited access to pervasive communications. We are, in fact, shifting from an era of mere content abundance to an avalanche of undifferentiated data. Our hard drives runneth over. So - you can't blame your self for wanting to move to the cloud. Unlimited space for all your crap - and free. Who wouldn't sign up? Today the noisy web has resulted in the emergence of a handful of private, walled garden webs. A closed web. Will our cloud providers become information overloads? Can we save the web from privatization, and regain control over our data and our identities? Only if we move fast. Before ‘Big Data’ becomes ‘Big Government.’ Find out how digital ‘overload’ can insure power in the human web.
by Becky Wang
Today, we have data – lots of it. We can process information – in many ways. We have models to understand our process. With these tools and a dash of creativity, we are discovering surprising patterns of human behavior and by extension, a way to accurately predict our desires and our future. In fact, we can quantify movements, behaviors, desires, and moods on a scale that wasn’t possible before a series of advances in processing power, developments in psychology, the science of social networks and collaboration, and most importantly, access to data. As we have evolved from Web 1.0 to 4.0 – in this anticipatory era – what will we dream up next? Beyond addressability and ad relevance, marketing initiatives and product development, how else can businesses utilize these advances? In advertising, industry, & humanity, can we make the leap from inductive logic to intuition? Can we supplement our brain mechanics with these new tools to finally predict what makes us happy?
by Erik Swan and Michael Wilde
WTF is Big Data & Why Should I Care?Love that smartphone? Navigate with your GPS? Tweeting about this session? Everything other than brushing your teeth has is generating data. Every action we do generates data & a record of that action. According to a recent study by McKinsey, 15 out of 17 industry sectors in the US have more data stored per company than the Library of Congress. The sheer volume of data, driven by new devices & disparate data sources, requires a shift in how to capture & analyze information. If you could mine data generated by your audience, what questions might you ask? Improving your perspective on what users are doing or how they're interacting with you can yield some amazing returns. Analyzing big data can be as easy as surfing the web. We'll show some cool ways to ask questions, in realtime, to some fun data sources & get amazing answers. See how to turn data into information, information to knowledge & knowledge to action.
by Ravi Iyer
Moral psychology and data analysis will eventually converge because successful organizations no longer serve physical, but psychological needs. This presentation will show how, in an age where consumption is about values (e.g. Whole Foods) and happiness (e.g. Zappos) rather than survival, moral psychology is essential knowledge for any organization. Leveraging our work at YourMorals.org, I will present research showing: 1) why emotional profiles are more important than demographic profiles, 2) how social networks form from moral agreement, and 3) why the ideological identification of employees and customers is important knowledge. Organizations will both use and contribute to the world's knowledge of moral psychology. Leveraging my dual experience as a data scientist for Ranker.com and as a moral psychologist at USC, I will illustrate how you can use recent moral psychology research to better help your customers and employees understand and live up to their values.
by Arnab Gupta
Using Big Data Takes Machines & Humans Man vs. machine – usually, good (man) versus evil (machine) – has long been the stuff of scary science fiction. And now as machines master more advanced processes, the prospect that thinking machines will outperform and ultimately replace thinking humans becomes more real and threatening. Example: IBM’s Watson, an advanced AI machine that’s squared off against Jeopardy’s best human contestants and won.But Arnab Gupta, CEO of Big Data analytics firm Opera Solutions, believes “humans vs. machines” is the wrong construct. Humans PLUS machines is far more powerful. Marrying machines’ ability to discern patterns in Big Data with humans’ ability to derive meaning from this output enables far better decisions. It’s the next wave in productivity.How to accomplish this, when machines and people speak different languages and “think” differently? At SXSW, Arnab will explore the power of “machine + humans” and discuss ways to create collaboration.
Technological innovation has dramatically increased the types andvolume of personal information created and captured. Social networks,mobile devices, thermostats, cars, even kitchen appliances collect andaggregate data from and about users. Personal data is among the mostvaluable assets for the current crop of tech startups. On the darkside, consumers have very little conception of the amount of data theyare creating and sharing and little appreciation of the potential risksand harms. On the bright side, data-based innovation can lead to newproducts, more efficiency, and lower costs. How can we protectourselves, without overreacting, in the age of data abundance? Can wetrust in the market to deliver the appropriate controls and usereducation, or do we need regulatory intervention? This session is sponsored by CNET / CBS Interactive.
by Gilad Lotan
“My real competition is 30 billion status updates,” PepsiCo Head of
Digital Shiv Singh has said of the challenge of being a brand in the
social space. Attention is the new bottleneck, and brands often adopt
counter-productive strategies to try and break through. They swear by
a certain time of day or spend an inordinate amount of time trying to
reach certain Twitter users deemed "influencers."
But what if there's something else at work in the massive flow of
information on Twitter? What if its not so much these so-called
"influencers" that propel a piece of information to major viral
broadcast, but the micro-networks and the aggregated interactions that
amass around them instead? Part case study of how massive spreads of
information and half how-to on the tools brands need to create and
manage micro-networks, this presentation will unlock that data
patterns on social that, when intelligently predicted and captured,
can be used to amplify the spread of a message on a grand scale.
9th–13th March 2012