The panel,will starts at 7 p.m. Pacific at the Hyatt Regency Santa Clara. In previous years, the audience held up red and green cards supplemented by electronic voting devices to indicate what they think of each trend–alas, no more–but last year they used a Twitter-based polling system. This year, it’s a service called Poll Everywhere, at pollev.com, that audience members accesses on their cell phones.
Technically, the trends are supposed to be ones that aren’t obvious yet but will be explosive within five years–tough criteria. Some of these trends have been explored before, including at previous tech trends events. But often take a decade to develop.
Forbes lists and comments the upcomming top trends:
1) EyePhones Replace iPhones: Eyewear computers will record our lives, says Cowan. The impact of graphical computing is minor compared with how facial computing will impact our lives. Ha, a photo of Star Trek captain Jean-Luc Picard as a Borg. Anyway, these eyewear computers will make iPhones obsolete. He’s not talking about just Google Glass, but more of an immersive experience. But still in four adorable colors, he adds.
We’ll be able to log our lives and summon up conversations from the past, or know what it’s like to be in the space station. We’ll be able to double-click on things we see to interact with them or buy them. Abroad, the signs will be in English for us, and speech will be subtitled. A new generation of games will emerge that are more immersive than any so far.
Two reds, and two greens. Ganesan says we’ll get too distracted and the biggest premium will be undivided attention. Jurvetson thinks it won’t replace other devices and will be relegated to niches like military or geeks. There are some killer apps, though, like augmented info on people as you meet them. Lin says they could be useful even in, say, a Zappos warehouse, so workers know what to pick off a shelf while leaving their hands free. But it would be better as a contact lens.
About 60% of the audience doesn’t think this will happen.
2) The “Right Now” Economy: Ganesan says the proliferation of a ubiquitous mobile devices, consumer web services, the ability to get feedback from the crowd, and analytics for the big data that results means consumers are moving from a “plan ahead” economy to a “right now” economy. Thus we see the rapid rise of companies such as Twitter, Waze, Uber, and Skout. For better or worse.
Twitter has faster news than most news services, he says. Waze has real-time traffic. You can get an immediate ride via Uber. And Skout? Instant hookup, theoretically. Three green and one red paddle. Zachary says it’s just human nature to want what you want immediately. It’s the obvious thing. Maybe, Ganesan says, but you can do all this only now. Red-paddle Jurvetson says he actually agrees with the trend but thinks it’s already too obvious–the entire history of the Internet is instant info and purchases. Ganesan argues that the trend really is about to reach critical mass with, well, the masses.
The audience is split, a few more disagreeing than agreeing.
3) Deux Ex Machina: Machine learning innervates the tech frontier. (Innervate means to add intelligence to things that weren’t before, Jurvetson says. OK.) He says machine learning will underly a lot of innovations like it does Siri, driverless cars, and Google Now today. Big data and sensors everywhere are only useful if we have machine learning to make it meaningful. Humanoid robots entering the workplace. Real-time translation services. Just about anything you hear from Google that’s new involves machine learning.
Paddles: two green, two red. Cowan, a red, whips out his iPhone and asks Siri, “Will machine learning be important in the next five years?” The answer: “Would you like me to search the Web for that?” In other words, no. For things to actually work, he says, you need human curation of the algorithms. And for these systems to get smart, it takes as long as for a human. We won’t see a Moore’s Law for acceleration of the smartness of these algorithms. Ganesan, who waved a green paddle, thinks the glut of data will nearly mandate the need for machine intelligence. It’s not obvious yet but likely to happen faster than we think. Look at what IBM Watson is doing in medicine.
Lin says you won’t trust a black box to trust things about your life. (Well, what about the Magic Eight-Ball. OK, it’s a ball, not a box.) A human had to teach a car how to drive. Jurvetson responds that that’s the whole point of machine learning–it gets taught and then does the job more consistently–he’d rather have a driverless car than most people he has driven with.
Audience: Around 75% agree (as do I).
4) The Individual Revolution: Technology has given us unprecedented tools to get work done individually that once required large organizations, Lin says. Again, half red, half green. Zachary, a green paddle, says a lot of companies he sees are focused on human potential. Jurvetson, a red, isn’t sure what examples he’s thinking of. Neither am I, honestly. Lin says the ubiquity of the mobile phone is what’s empowering this. All these services enable a much faster response. Ganesan, who agrees with Lin, says all these productivity tools enable individuals to be a much bigger business presence.
Cowan, the other red paddle, says there’s an illusion that we should all be our own bosses. There’s a downside to the incubators who promote this. The most worthy ventures I see require teams to pursue. The audience isn’t so sure either–two-thirds disagree.
5) The U.S. Is The Supreme Cyber Security Force: Citizens will accept complete observation by the state, says Zachary. Why? The forces of hate will never subside. People will create a drone with 3D printing and bomb a building. Then the government will crack down and analyze every cell phone call. Shades of Minority Report, or the Bourne movies. This will lead to other countries to develop technologies to counter this, creating cyber-wars. Once again, panelists split in half.
Ganesan, who disagrees, says the long arc of humanity is toward a more progressive, humanistic level–in actuality, we’re safer today than we ever have been in history. It’s much harder to demonize people and kill them when there are more social connections online. The fear is much greater because of the Right Now Economy, counters Cowan. Jurvetson says the amount of effort it takes to unleash mass destruction continues to drop fast, thus his green paddle–though he thinks a police state won’t work. Lin, a red, says he just believes in the good of human beings, especially as people know more about everyone else through all the information we will have at our fingertips.
Sixty percent say a police state is coming. Great.
6) Cyber Warfare Becomes A Good Thing. Cyber missions are instant, effective, relatively free, and nonlethal, says Cowan. This will completely disrupt the defense industry. Companies usually wish hacking will go away, but it won’t. There’s a great opportunity for startups to handle these threats. Hackers will be heroes, in other words. Two reds, two greens again.
Ganesan, a red, isn’t sure he wants to enable cyberwarfare vigilantes. Jurvetson doesn’t think it would be good to concentrate power in opaque organizations. Nearly 60% of the audience agrees.
7) Certifications, Not Diplomas: The emergence of Massively Open Online Courses (MOOCs) and other online lifelong learning educational sites such as Khan Academy, Coursera, and Udacity means the future will be deﬁned not by where you went to school but rather by what you know, says Ganesan. Hasn’t this really always been the case, at least by your 30s? The educational world is becoming ﬂat, he said. Or to put it more plainly, it won’t be what you studied that’s important, but what you shipped. Well, if you’re an engineer or an entrepreneur.
Two greens, two reds, yet again. Lin, mostly a red, thinks diplomas are still a signal we will use to assess people. Also, the good schools are already thinking of how they need to change to survive in this environment. Jurvetson, a green, says in the next five years there will be more accurate ways and signals to assess people globally on their skills than diplomas. Cowan, a red, says MOOCs are great for efficiently distributing information, but thinking outside the box and creatively happens better at universities where you’re not just an IP address.
Audience is split in half. Cowan adds: Your kid gets accepted into Stanford–are you going to say, no no, I’d rather she do MOOCs. No.
8) Erasing The digital divide Ironically Accelerates The Rich-Poor Gap. Winner-take-all network effects will rule, says Jurvetson. He says he’s a technology enthusiast but worries info technologies will exacerbate the gap, particularly in regional areas that used to be protected from global competition. Two billion people coming online in the next couple years will produce a wealth of cheap talent. Paddles: Yet another even split.
Cowan agrees with most of this, but he doesn’t think people who get off the technology bandwagon never catch up. He thinks it’s a temporary problem, because everyone will be part of the info economy. Jurvetson: Think about big parts of the world that reject science and modernity. Cowan writes them off, hmm. I’m not sure the fortunes of Mark Zuckerberg’s result in poverty for others, he adds. Lin agrees with Jurvetson: Facebook created billionaires, but it employs far less than Ford. Zachary thinks we’re at the beginning of an unpleasant wave for rich people, because governments will tend to tax the rich to resolve this rich-poor gap.
Audience: Around 70% agree.
9) Personalized Medicine: The ability to cheaply sequence genomes means we will solve a lot of diseases, says Lin. Calling John Doerr, who predicted this years ago, and I think he wasn’t the first. It’s possible in a year or two that we can sequence a person’s genome for $1000, maybe $100 in a few years. Machine learning and big data will allow us to understand this data and the medicine we need to fix our diseases. Paddles: half and half again.
Zachary, a red, thinks this will happen, but not in the next five years. It’s not just your genome, but flora in your gut and the like. Maybe personalized medicine, but not personalized medications. Jurvetson notes this has been on the list five or six times (actually, seven to nine times, says Upbin), but thinks that while it’s possible, we don’t have socialized medicine, so privacy and insurance are big obstacles.
Cowan, a red, who lost money on a personalized medicine startup, says we still can’t process the interplay among all these genes. The audience is slightly more in agreement than not.
10) Wearable Computing Is The Watch, Not The Glass: The watch supplants the phone as primary display and interface, says Zachary. Pebble, in which he has invested, has sold $36 million worth of its smart watches. Watches are just so natural for people to wear, unlike Google Glass. Paddles are all red! “That means I made a good investment,” he says. “To be a good investor,” responds Jurvetson, “you have to be contrarian and right.” He notes that nobody under 35 wears a watch. Too geeky, adds Lin. Plus, says Ganesan, a watch has little of the utility of the phone.