Skip to main content

Currently Skimming:

2 The Technological Landscape
Pages 21-53

The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
Select key terms on the right to highlight them within pages of the chapter.


From page 21...
... The first is technology creation: the combination of fundamental capabilities enabled by advances in foundational science and engineering research to yield a new functionality. The second force is technology diffusion: the adoption of these technologies in new products and services and their emergence in new markets over time.1,2 For example, consider the invention of tools such as the Internet, the mobile phone, home wireless networks, computer algorithms that recognize faces, or self-driving vehicles.
From page 22...
... This section characterizes recent trends in technological capabilities and technology adoption and identifies possible changes to the technological landscape over the coming years, with an eye to technologies most relevant to the workforce. THE DIGITIZATION OF EVERYTHING Perhaps the most obvious ongoing technology trend is the widespread use of computers, digital and online data, and the communication infrastructure of the Internet.
From page 23...
... For example, a 2015 issue brief from the President's Council of Economic Advisers highlights this "digital divide," noting that 2013 rates of household Internet access correlate with education level of the head of household and that members of underrepresented minority groups have lower access rates. Geography also plays a significant role in determining access.5 Education has also been impacted by digitization, with increasing access to online courses, including video lectures; experts who can answer specific questions through online discussion boards such as Quora.com; and early technologies for customizing courses to individual students based on the digital trace of their performance to date -- not to mention the trove of digital knowledge to be explored by learners.
From page 24...
... Larger numbers of hospitals had implemented computerized pro vider-order entry systems.2 Computing technologies offer the promise of efficient capture, retrieval, and transmission of patients' health and clinical encounter data, efficient work flows via electronic order entry, and improvements in medical care with the delivery of new kinds of clinical decision support for health-care workers. Decision-support opportunities include methods that leverage captured data to predict outcomes (such as the risk of readmission, hospital-associated infection, or onset of sepsis)
From page 25...
... :737-744, doi: 10.1200/JOP.2015.010504. Computing Power and Networking The increasing use of digital technologies has been enabled by foundational advances in computing power and networked connectivity.
From page 26...
... For example, graphical processing units, or GPUs, have enabled a new family of massively parallel architectures that have gained significant popularity for machine-learning and big data applications, as discussed in the section "Advancing Technological Capabilities" below. Given current trends, shown in Figure 2.1, computing power and networking capabilities are expected to continue to advance at least over the coming decade.6 Research laboratories continue to pursue new approaches, such as quantum computing, which have not yet been proven practical, but which hold the potential for significant future improvements in computing power for some tasks.
From page 27...
... population had access to the Internet.7 Internet bandwidth has grown by approximately 50 percent every year over the last two decades.8 Wireless connectivity has become faster and more pervasive through 3G and 4G -- or third- and fourth-generation -- wireless protocols, while wired network speeds have improved. By 2014, a typical Internet speed was 100 megabits per second for end users; Google has introduced gigabit per second access to metropolitan areas across the United States, with companies such as AT&T and Comcast beginning to provide similar service levels.
From page 28...
... This capability is now at the heart of mobile computing applications such as location-aware Internet search, real-time traffic directions, and "find my friends" social networking tools. Another benefit of GPS technology is the direct transmission of highly accurate timing signals to computing systems, allowing more effective and cost-efficient synchronization of network activities and work processes.
From page 29...
... In addition to the computing power of the mobile device itself, its utility as a component of an enterprise workplace environment has expanded with wireless network bandwidth capabilities. Such capabilities have expanded from 12.2 kilobytes per second (Global System for Mobile Communications standard)
From page 30...
... The use of these forms of data and information exchange in organizations are affected by combinations of context, task urgency, and bandwidth; although studies of these aspects of organizational data sharing date to the 1990s, the capability of high-speed Internet infrastructure has led to a majority of survey respondents reporting daily or weekly videoconferencing.17,18 Mobile computing, increased Internet bandwidth and infrastructure support, and cloud-based data storage can also support the growing role of flexible "hoteling" or "touchdown" spaces, which 14  Visually, 2011, "The History of EMAIL and Growth of EMAIL Accounts," http://visual. ly/history-growth-email.
From page 31...
... . While these innovative educational tools have stimulated much excitement, it is also important to understand exactly who is participating and benefitting from online courses.
From page 32...
... For example, a 2015 issue brief from the President's Council of Economic Advisers highlights this "digital divide," noting that 2013 rates of household Internet access correlate with education level of the head of household, and that members of underrepresented minority groups have lower access rates. Geography also plays a significant role in determining access.21 At the same time, there are limits to what can be learned through remote online tools, such as for fields relying on intensive apprenticeship with significant hands-on and embodied competency.
From page 33...
... In addition, radiofrequency identification technology provides a low-cost method to identify and track any physical item without use of battery power and has been widely used, for example, to track items during shipping. The significance of the Internet of Things is that it will further accelerate the trend toward digitization of everything, making it possible for the Internet to serve as a communication tool for capturing, sharing, and acting on even more digital information.
From page 34...
... ADVANCING TECHNOLOGICAL CAPABILITIES The paradigm shift to digitization enabled by development of the Internet and advances in computational power, networking speed, and data capture and storage has been transforming society for decades. New and compelling uses of these technologies, enabled by enhanced connectivity and computing power, continue to emerge.
From page 35...
... For example, fraud-detection strategies are now developed automatically by machine learning algorithms that analyze millions of historical credit card transactions. The increasing use of machine learning, along with other innovations, has produced significant progress in a variety of AI subfields, including computer vision, speech recognition, robot control, automated translation between languages, and automated decision-making.25 These advances in AI component technologies have in turn produced a number of highly visible AI systems over the past decade, including the following: • Intelligent agents such as Apple's Siri, Google Now, Microsoft's C ­ ortana, and Amazon's Echo.
From page 36...
... Multiple universities and companies have now demonstrated self-driving vehicles. For example, in 2015 the automotive company Tesla released software that allows its customers to put their automobile into self-driving mode on public highways, and Uber has recently begun testing self-driving cars on the streets of Pittsburgh.26 This demonstrates that computer perception and control -- in particular, computer vision and self-steering -- have reached an important threshold of practical reliability.
From page 37...
... Machine Learning and Big Data One of the most important drivers of AI advances over the past two decades has been machine learning: computer algorithms that automatically improve their competence through "experience." This experience is often in the form of historical data, which the machine-learning algorithm analyzes in order to detect patterns or regularities that can be extrapolated to future cases. For example, given experience in the form of a historical database of medical records, machine-learning algorithms are now able to predict which future patients are likely to respond to which treatments.
From page 38...
... These algorithms are able to discover useful abstract representations of complex data. Over recent decades, deep learning has helped to advance the state of the art in computer vision, speech recognition, and other areas, especially in tasks that involve complex perceptual or sensor data.29 For example, Xu et al.
From page 39...
... Data access will be bounded by personal privacy concerns, by the willingness of companies that own much of this data to share it, and by government regulations, such as those under the Health Insurance Portability and Accountability Act of 1996, which govern access to medical data. In addition, while some data are in the form of highly structured databases, many are in the form of unstructured video, audio, and text that are much less interpretable by computers, despite recent progress.
From page 40...
... An annual report issued by the International Federation of Robotics34 captures the sales and inventory of both industrial and service robotics in most countries and includes a break-down across use-cases. The industrial robotics market today has annual sales in excess of $10 billion each year, or more than $30 billion including installation costs and sale of accessories.
From page 41...
... "Industrial Robot Statistics: World Robotics 2015 Industrial Robots," last modified 2015, http://www.ifr.org/ industrial-robots/statistics/. ics assembly and metal work accounting for 21 percent and 10 percent, respectively.36 Figure 2.5 illustrates the distribution of application areas for robotics in 2015.
From page 42...
... The service robotics market is expected to see major growth significantly beyond the industrial market, since it includes subsectors such as driverless cars, unmanned aerial vehicles (sometimes referred to as drones) , and entertainment robots.
From page 43...
... There is also research to explore styles of interaction between robots and people, such as work on building robots from more pliable materials to avoid accidental harm to people; research on styles of conversation between robots and people to produce effective communication; human instruction of robots; and robots' explanation of their actions. Computer Perception: Vision and Speech Over the last 15 years, tremendous progress has been made in computer perception, especially in the areas of computer vision and speech recognition.43 Computer vision is widely used today in a range of applications, including fingerprint recognition at safety barriers, high-speed processing of handwritten addresses on letters by the U.S.
From page 44...
... Ma, X Huang, et al., "ImageNet Large Scale Visual Recognition Challenge," International Journal of Computer Vision, last modified January 30, 2015, http://arxiv.org/ pdf/1409.0575v3.pdf, with permission of Springer.
From page 45...
... . As in the case of computer vision, much of the recent progress in speech-totext systems has been due to the use of deep network machine learning algorithms.
From page 46...
... Reprinted with permission. FIGURE 2.8  Recognition word error rate versus the amount of training hours, demonstrating the sensitivity of competency of speech recognition to increasing amounts of data.
From page 47...
... This technology has many other potential uses, and IBM is now applying it to medical applications using large collections of medical text. Given that the rate of publication of new medical results outpaces the ability of doctors to read journal articles, decision support systems such as Watson have potentially game-changing consequences for augmenting human capabilities in fields that require knowledge-based decision-making.
From page 48...
... For example, efforts have been under way to develop collaborative robotic systems in surgery to allow robotic surgical systems to work hand in hand with human surgeons. Promising prototypes and research to date have considered technologies to recognize and understand the actions and intentions of human surgeons and coordinate activities between robotic and human surgeons.53,54,55 Directions in research and development on complementary computing systems show how the talents of machine competencies can be joined with the intellect and physical prowess of people and highlight the likelihood that technical advances will bring to the fore new roles and types of work for people in joint human-machine problem solving -- where people bring critical, uniquely human contributions into the mix of initiatives.
From page 49...
... increasing investments by industry in research and development in AI and other parts of IT. Although it is impossible to predict future capabilities perfectly, certain ongoing technology trends make the following workforce-relevant developments likely over the coming decade.
From page 50...
... • Computer perception of speech, video, and other sensory data. It is likely that computer competence in perceptual tasks, including speech recognition, computer vision, and interpretation of nonspeech sounds, will advance, potentially leading to significantly improved abilities in several areas, such as listening and image processing.
From page 51...
... For example, if advances are made in technology for privacy-preserving machine learning methods, which would use data while guaranteeing preservation of individual privacy, this would dramatically increase the variety of data mining and machine learning applications that reach the market -- for example, medical applications that are currently avoided because of privacy concerns. If it becomes possible for computers to learn how to accomplish tasks through instruction from their users, this could have a truly dramatic effect: it would change the number of effective computer programmers from its current short supply to billions of people, enabling each worker to custom instruct their system on how to best assist them.
From page 52...
... It has already eliminated and created jobs, but more frequently it has transformed jobs and the way they are performed. IT has transformed business practices as companies have moved routine operations online, where they can be better tracked and partly automated (e.g., supply chain management or customer relationship management)
From page 53...
... Machine learning algorithms are now mining the exploding volume of online data to capture regularities that enable them to automate or semiautomate many knowledge-intensive decisions, from deciding which credit card transactions to approve to deciding which X-ray images contain evidence of tumors. As increasing volumes of data and decisions come online, the potential applications of this technology will grow as well.


This material may be derived from roughly machine-read images, and so is provided only to facilitate research.
More information on Chapter Skim is available.