Читать книгу What To Do When Machines Do Everything - Roehrig Paul - Страница 6
1
WHEN MACHINES DO EVERYTHING
Digital That Matters
ОглавлениеFor the past decade, we've collectively enjoyed “digital that's fun.” We've seen the incorporation of Twitter (2006), the introduction of Apple's iPhone (2007), and Facebook's IPO (2012). These companies, along with others, such as Google, Netflix, and Amazon, have been able to generate unprecedented commercial success in terms of customer adoption, daily usage, and value creation by changing how we communicate and socialize. Yet, history will note that we started the digital revolution with the amusing and the frivolous: Facebook posts, Twitter feeds, and Instagram photos. We are using the most powerful innovations since the introduction of alternating current to share cat videos, chat with Aunt Alice, and hashtag political rants. However, that's just the warm-up act, for we haven't yet begun to fully realize the potential of the new machines.
Technology writer Kara Swisher summed it up best when she said, “In Silicon Valley, there's lots of big minds chasing small ideas.”6 Well, we're entering an era of big brains focused on big ideas —digital that matters– using these technologies to transform how we are educated, fed, transported, insured, medicated, and governed.
While companies such as Facebook, Amazon, Netflix, and Google (sometimes known as the FANG vendors) seem to have established themselves as the presumptive and eternal winners in this space, history will likely remember them as the precursors to a much more momentous and democratic economic shift. The next wave of digital titans probably won't be characterized by start-ups from Silicon Valley; instead, it will be made up of established companies in more “traditional” industries – in places like Baltimore, Birmingham, Berlin, and Brisbane – that figure out how to leverage their longstanding industry knowledge with the power of new machines.
We're starting to see this play out as we collectively work to apply systems of intelligence to help address some of our most vexing societal ills in areas where digital technology is not just entertaining or convenient but also life-altering. Certainly, many of our institutions – the pillars of our society and our everyday lives – are ripe for improvement.
For example, worldwide we lose 1.2 million lives to car accidents annually, with more than 94 % of these accidents a result of human error.7 In the United States alone, these wrecks cost society over $1 trillion. This is nearly one-third the amount the U.S. federal government collects in individual income taxes.8 Driverless cars promise to save countless lives and heartache.
One-third of all food produced in the world goes to waste. The food wasted in rich countries alone is almost enough to feed all of sub-Saharan Africa.9 By instrumenting the supply chain and applying AI, we could literally feed the world.
Medical misdiagnoses could also plummet. Right now, 5 % to 10 % of trips to the ER results in a misdiagnosis.10 More than 12 million diagnostic mistakes contribute to 400,000 deaths caused by preventable errors each year, and that's just in the United States.11 Applying data to the diagnostic process could dramatically improve patient outcomes.
The United States spends more per student on secondary education than most other countries in the world but generates mediocre results. In a recent international study, American students achieved scores far below those in many other advanced industrial nations in science, reading, and math.12 By tailoring lessons to the individual learning style of each student through technology, we could make the education process radically more productive and effective for both students and teachers.
These are the sorts of big things that we can address with the new machine. It's digital with purpose and digital that matters, and the big brains bringing these innovations forward will not necessarily reside in Silicon Valley or an MIT dorm room. They may well be sitting in an office down the hall at your company.
For example, McGraw-Hill Education is applying new technology to help teachers and kids improve learning with a system called ALEKS. The artificially intelligent Assessment and LEarning in Knowledge Spaces system uses adaptive questioning to quickly and accurately determine exactly what a student knows and doesn't know in a course. ALEKS then instructs the student on the topics he or she is most ready to learn. As the student works through a course, ALEKS periodically reassesses the student to ensure retention. All of this results in more flexible, one-on-one instruction for students, which boosts student success. And for teachers, ALEKS helps take over some of the more routine – and, let's say it, boring – work to allow them to focus more intently on working with students. Discovery, one of South Africa's leading insurers, uses its Vitality platform to provide economic incentives – discounts on travel, entertainment, healthy food, gym memberships, sports equipment, health products, and the like – to its members based on whether they participate in healthy behaviors. Members earn points by logging workouts with connected fitness devices and purchasing healthy food (also logged by swiping their Vitality card). The insurance sector may not be known as a hotbed of innovation, but Discovery has built a thriving business based on the value derived from the new machine.
6
John Kennedy, “Kara Swisher: ‘In Silicon Valley, There Are a Lot of Big Minds Chasing Small Ideas,’” Silicon Republic, June 24, 2015, https://www.siliconrepublic.com/start-ups/kara-swisher-in-silicon-valley-there-are-a-lot-of-big-minds-chasing-small-ideas.
7
“Human Error Accounts for 90 % of Road Accidents,” International News, April 2011, http://www.alertdriving.com/home/fleet-alert-magazine/international/human-error-accounts-90-road-accidents.
8
See http://www.rmiia.org/auto/traffic_safety/Cost_of_crashes.asp and http://www.who.int/violence_injury_prevention/publications/road_traffic/world_report/en/ and https://en.wikipedia.org/wiki/United_States_federal_budget.
10
“Surprising Number of Emergency Room Medical Errors,” July 15, 2016, http://philadelphia.cbslocal.com/2016/07/15/surprising-number-of-emergency-room-medical-errors/.