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all the data in the world has been generated in the last two years. This includes digitized versions of traditional print media, as well as all the output of our interactions via social media: tweets, uploaded pictures and video, e-mail, instant messages, etc. Data becomes “big” when its scale is so large it can’t be grasped, managed and manipulated by traditional statistical software, and the scale of the information we are generating now is mindblowing: by 2012, people were creating 2.8 zettabytes of data a year, and this is projected to double by 2015 (“zetta” is 2 to the 70th power). But what’s really impressive are the tools we are developing to make sense of all these bytes. While the human race is rapidly depleting or degrading natural resources—oil, water, minerals, biodiversity—one resource is growing at an exponential pace. Every two days people create as much information as we did from the dawn of civilization up until 2003. Put another way, 90 percent of Sci-fi author Sir Arthur C. Clarke coined three laws of prediction, the third of which is “Any sufficiently advanced technology is indistinguishable from magic.” Big data analytics definitely launches us into that magical realm. While some of the current applications merely increase efficiencies of traditional business (reducing fuel use, for example), they can open up whole new vistas. Predictive marketing enables stores to process the vast amount of personal data they collect on customers to identify what they might buy, and when, with pinpoint accuracy. (Target famously outraged one father by sending coupons for baby products to his teenage daughter, only to have the abashed dad find out “there’s been some activities in my house I haven’t been completely aware of.”) Analysts are becoming ever more savvy at reading the digital footprints we leave via social media, parsing our Facebook posts or mining our tweets to predict our basic personality traits, values and needs. 25
Page 1 and 2: TrendsWatch 2014
Page 3 and 4: Table of Contents INTRODUCING TREND
Page 5 and 6: eally free—we are asking you to p
Page 7 and 8: Left: CFM director Elizabeth Merrit
Page 10 and 11: RIght: The New Museum of Contempora
Page 12 and 13: of the rich and undeserving of publ
Page 14 and 15: MUSEUM EXAMPLES The NEW MUSEUM in l
Page 16 and 17: Synesthesia: Multisensory experienc
Page 19 and 20: experiences are a hot thing: Ultrav
Page 21 and 22: Above: Graphic design for a fiction
Page 23: MUSEUM EXAMPLES Museums and other c
Page 27 and 28: Project (SIAP). These may only coun
Page 29 and 30: “big stuff.” And less expensive
Page 31 and 32: with Census data for a demographic
Page 33: The new Graph Search engine on Face
Page 36 and 37: of banning Google Glass before it w
Page 38 and 39: Museums enjoy high levels of trust,
Page 40 and 41: What’s Mine Is Yours: The economy
Page 42 and 43: Left and Above: Lyft pairs passenge
Page 44 and 45: In a dismal job market, collaborati
Page 46 and 47: We are also experiencing the rise o
Page 48 and 49: Robots! Are Rosie, Voltron, Bender
Page 50: learner” for students, helping th
Page 53 and 54: ainwaves. Robotic exoskeletons can
Page 55 and 56: tolerance for repetitive tasks. Thi
Page 57 and 58: Author credit Elizabeth E. Merritt
Page 59: Help us keep an eye on the future T

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