FEATURE
What Trends May Come in 2015
Although some of the information industry’s biggest headlines may be hard to predict a year in advance—this year’s declaration of bankruptcy by Swets, for example—for dedicated trend watchers, some news items for the upcoming year can be gleaned by industry professionals with an eye for burgeoning hot topics.
John Blossom, Leigh Watson Healy, and Timo Hannay share their expertise and help map out the most likely trends, technologies, and movements to come that answer today’s questions and solve today’s problems—while undoubtedly throwing a few new questions and problems into the mix themselves.
Content and Technology Trends
John Blossom
President, Shore Communications, Inc.
While mobile and cloud technologies continue to put enormous pressure on content producers to define the best value points for their products and services, 2015 is likely to be a good year for content providers that are looking to transition to web publishing more gracefully. With the U.S. Federal Communications Commission (FCC) likely to put only modest pressure to prevent premium charges for specific internet content services, 2015 is likely to see an accelerated push toward the cable TV industry “pulling the plug” on itself and shifting its primary delivery of consumer content to the internet. Premium is “in,” at least for publishers, with other forms of consumer and professional media following suit and finding more ways to deliver premium services on more information platforms than ever before. Content is moving more and more toward the model being pioneered in the computer gaming industry, featuring multiscreen, multiperson interactive experiences that enable people to direct and share information and experiences to the devices of their choice with remarkable ease.
In recent years, I have highlighted mobile phone and tablet computer chips as key technologies driving changes in the content industries. While these processors continue to impress and to expand the graphics and processing horizons for these devices, much of the pivotal technology for 2015 will be both much larger and much smaller than these chips. On the small side, inexpensive microprocessors embedded in appliances and in environmental and industrial sensors are likely to take center stage as a key driver of “signal,” the vast amounts of data that surge into the web that can inform service providers about what the world is doing at any moment in stunning detail. Complementing these trillions of microchip-driven sensors and micro-appliances are the internet cloud computing resources that interpret a world of sensors and online media to provide predictive analysis and services. While artificial intelligence (AI) was just a far-off notion for most people a few years ago, 2015 will mark a broad awareness that AI now has a permanent and powerful collaborative role in the content industry.
While many of these trends favor today’s technology giants, 2015 is not necessarily going to be a rosy year for them in many ways. Many industry analysts wonder whether we’ve reached “peak Google,” meaning that Google’s ad-driven monetization of search and mobile platforms will continue to keep up with the transition of advertising dollars to mobile platforms, where ad rates are significantly lower. This may prove to be a short-term trend, especially since the number of ads being served up at lower prices is still increasing very quickly, but for Google, Microsoft, Apple, Samsung, and other big technology companies, the question will be what they do for a major encore now that global markets are becoming saturated with their devices and services. Those positioned best for supporting the growing realm of mobile financial transactions and local delivery services might be best prepared in 2015 to find new ways to help marketers take advantage of their content and technology prowess.
Sensored World, Sensible Choices
Leigh Watson Healy
Chief Analyst, Outsell
Outsell’s theme for 2015—Sensored World, Sensible Choices—is about how everything we do is “sensored,” monitored, and analyzed. For example, the average American is on some kind of video surveillance camera 200 times a day. What will result from the clash between “sensorship” and its benefits, and privacy, predictive analytics, and security? How do we navigate the issues for our industry? The following are some key trends to watch:
- Volatility—Political instability, terrorism, hackers, and social and political unrest all affect our industry. Leaders must be ready with multiple scenarios to harness this explosive energy rather than be flattened by it, and they must seize the opportunities that result
- Structural change—Monoliths are tumbling; we see Uber and the taxi industry and KAYAK and others in travel. New demands at an accelerated pace mean that systems, staff, information solutions, methodologies, and the ability to implement must be ready and more agile than ever.
- Data security—This is potentially the kryptonite of the internet and of industries that drive off of the internet. Challenges to security and privacy could weaken and sap the strength of the information industry. Our systems must be bulletproof.
- Future of money—Will bitcoin or its look-alikes replace currency? Will we even need a wallet? We need to prepare to do commerce in a virtual currency environment.
- Sustainability—This is a topic that more data and more information will help address, both as a challenge and an opportunity—solving for water, for food, and for health—to find ways to really improve the world.
- GAFA as user interface—Google, Apple, Facebook, and Amazon (GAFA) have a grip on controlling design and user experience, as well as on our interaction with commerce, with the internet, and with many information services. “Take it anywhere with you on any device” will permeate user expectations, and this has implications for desktop patterns and workflows.
- Physical touch—The need for connection with people is increasing. The trend toward handmade and analog is fascinating. The changing nature of work means the changing nature of information services that feed off these new solutions in ways that connect people and support the creativity that will be unleashed.
- Machine made—Will artificial intelligence create the intelligence that sits on top of our information and content in this converging world? We’re seeing fast-growing paid content businesses based almost exclusively on machine collection, curation, and analysis of data for paid content markets. Industry players need to learn how to transform by reducing the cost of creating product.
- Future of jobs—If machines can replace our high-end abilities—our analytic thought work—can they free us to do what humans do best: create? Leaders are battling for market share, and that requires different strategies, whether for a disruptive new entrant or an incumbent.
- The “new parochialism”—The concern that something might happen or something might go awry if we leave our desks or if we lift our heads up is something we need to be watchful of—to keep our wits and do what is needed to create engagement in the user experience for knowledge workers. It also has implications for how our leaders manage.
We are at a crossroads. What kind of world do we want to create and live in? What will result from the clash between sensorship and the promise it brings with privacy, predictive analytics, and security? The implications and opportunities for our industry are profound as we grapple with the challenges of value creation and value monetization in our connected and sensored world.
The Digital Academy and Augmented Intelligence
Timo Hannay
Managing Director, Digital Science
2015 will be the first year in which (some of) academia becomes truly digital. Yes, computers, databases, and other forms of IT have long loomed large in universities and research institutions. But the front lines of academia—its labs and the lecture theaters—have by and large remained resolutely analog.
This is changing, driven by two complementary forces: 1) the availability of inexpensive mobile and tablet computers, as well as increasingly sophisticated software tailored to the needs of academia (Disclosure: Digital Science, the business I run, creates such software.) and 2) increasing demands on institutions to demonstrate transparency and reproducibility in research 1 and value for money in teaching 2 —profound challenges that strike at the heart of academia’s roles in society. As researchers make better use of computers to capture their research data in auditable, reusable, and shareable forms, and as professors increasingly rely on technology to disseminate lectures, support students, and track their progress, the digital academy will at last have arrived.
And yet, in reaching this milestone, academic institutions will merely be catching up with the worlds of commerce and consumerism. This raises a question: Where is the rest of the world going next, and where, by extension, might the academy follow? The answer is artificial intelligence (AI).
It’s true that AI has suffered a number of false dawns, from its heady beginnings in the 1950s, when researchers thought that intelligent machines would be with us inside a generation, to the unfulfilled promise of expert systems and “fifth-generation” computing in the 1980s. Even Deep Blue’s watershed victory over Garry Kasparov in 1997 felt like an anticlimax. After all, this was merely the abstract world of chess; true intelligence demands more, not least a degree of versatility. (The comedian Emo Philips put it beautifully: “A computer once beat me at chess, but it was no match for me at kickboxing.”)
That debate is now over. As we enter 2015, AI is no longer an up-and-coming technology; it has arrived, driven in large part by ubiquitous networked computing and vast quantities of data. From street directions and machine translation to voice and image recognition, our handheld computers (aka phones) are no longer self-contained but benefit instead from being connected to supercomputer-like banks of servers in the cloud that are themselves linked to all the requests that every other user is making—or has made—on his or her own hyperconnected devices. The result is not the kind of rules-based AI that technologists imagined in days of yore, but to anyone from just a few decades ago, these systems—along with IBM’s quiz maven, Watson, and Google’s self-driving cars—would appear miraculous.
Such developments have also been enabled by rapid improvements in algorithms, particularly “deep learning” approaches that have now achieved human or superhuman levels of performance in such previously intractable areas as handwriting recognition and identification of traffic signs. Importantly, this technology is no longer limited to large corporations or academic experts, but now is well within the reach of motivated entrepreneurs and hobbyists, 3 heralding an exciting period of experimentation and accelerating progress.
What will this mean for society as a whole and academia in particular? First, AI is becoming embedded in our lives, but—popular hysteria and some exceptions notwithstanding—will tend to augment human intelligence rather than replace it. The most effective decision makers of the future, from surgery to the stock market, will be symbiotic combinations of carbon- and silicon-based machines. And before much longer, this will be true in teaching and research too, where interactive learning systems 4 and “robot scientists” 5 are still in their infancy but growing up fast.
Endnotes
1. economist.com/news/leaders/21588069-scientific-research-has-changed-world-now-it-needs-change-itself-how-science-goes-wrong
2. economist.com/news/briefing/21605899-staid-higher-education-business-about-experience-welcome-earthquake-digital
3. neuralnetworksanddeeplearning.com
4. www2.saplinglearning.com/higher-education
5. sciencemag.org/content/324/5923/81.abstract and www.aber.ac.uk/en/cs/research/cb/projects/robotscientist
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