Part VII
Cognitive Systems
© Springer-Verlag GmbH Germany 2018
Claudia Linnhoff-Popien, Ralf Schneider and Michael Zaddach (eds.)Digital Marketplaces Unleashedhttps://doi.org/10.1007/978-3-662-49275-8_27
27. Cognitive Computing – the new Paradigm of the Digital World
Wolfgang Hildesheim1
(1)IBM Deutschland GmbH, Düsseldorf, Germany
Wolfgang Hildesheim
Email: [email protected]
27.1 Cognitive Computing – the new Paradigm of the Digital World
27.1.1 A Brief History of Eras
Cognitive systems like IBM Watson understand at scale, reason with a purpose, learn with each new interaction, and interact naturally with humans, augmenting human intelligence – but before discerning the significance of cognitive computing, it is firstly important to place it within historical context. To date, there have been three distinct eras of computing: 1) The Tabulating Era which helped revolutionize the way in which we were able to manage large volumes of structured data like the census; 2) The Programmatic Era which ushered in the computer revolution allowing us to apply rules and logic revolutionizing the ways in which large and complex transactions were automated (e. g. financial systems, travel systems, etc.); and 3) The Cognitive Era which is extending our ability to work with information of all types, structured and unstructured (e. g. text, pictures, video), with natural conversational interaction, exploration not simple search, decision optimization based on evidence and confidence, all in a time frame that allows us to achieve better results.
The Tabulating Era, from the early 20th Century to the 1940s, was the birth of computing, consisting of single‐purpose mechanical systems that used punch cards to tabulate. World War ll moved us from tabulators to electronic systems and marked the beginning of the Programmatic Era. Subsequent to the war the age of ‘digital computers’ evolved, moving into businesses and governments. They performed logical operations from a set of structured instructions (i. e. rules). This is very much what we have known of computing since the 1950’s, and while the languages we use to program have evolved the basic premise of computing is the same.
Now we have entered the Cognitive Computing Era, developing systems that can use natural language processing to extract meaning from large volumes of unstructured data and learn as they do so. Cognitive systems such as IBM Watson make sense and give purpose to a world awash in an overwhelming deluge of data. Cognitive computing uses technologies like machine learning to find meaning by discovering previously unseen patterns, drawing new inferences and identifying new relationships from vast amounts of data, and helping humans make confidence weighted, evidence based, decisions more rapidly. Existing computers – let alone humans – simply cannot handle the volume and diversity of data being generated everywhere, by everyone, every day. We are not just trying to improve productivity with cognitive – doing things faster and more efficiently; we are trying to augment human decision‐making; we are trying to use these computers to digest data and come up with better outcomes. Unlike existing computers that must be programmed, cognitive computing understands the world in the way that humans do: through senses, learning, and experience. What “search” is to literal data retrieval (i. e. key word match), “cognitive” is to better, more informed and more timely discovery and decision making.
27.1.2 What is Cognitive Computing’s Relationship with Artificial Intelligence (AI)?
Cognitive computing brings together technologies associated with artificial intelligence (AI) with deep subject matter expertise and relevant content. It offers the ability to boost productivity and nurture new discoveries across a broad range of industries. Based upon AI technologies such as machine and deep learning; language, speech and vision capabilities; high‐performance cloud computing; and new computing physical devices (e. g. smartphones, robots, etc.), cognitive computing is changing the way we work with technology. Guided by the view of “augmented intelligence” rather than “artificial intelligence” cognitive systems enhance and scale human expertise, side‐by‐side with humans to accelerate and improve our ability to act with confidence and authority. Focused on developing practical applications that assist people with specific challenges and tasks, cognitive computing exposes a wide range of specific artificial intelligence services that support a range of applications to help augment human intelligence. The power of cognitive systems is today helping mankind better understand our world and make more informed decisions about how we live in it. We believe that in the future, every critical decision will be informed by systems like Watson.
27.1.3 How Cognitive Moves Beyond Narrow Aspects of Artificial Intelligence
Unlike other areas of computer science that align to a single discipline, cognitive computing combines a variety of academic fields, from machine learning and algorithmic strategy, to neural networks and natural language processing, to industry knowledge and beyond. We see, in our everyday lives, examples of narrowly focused, purpose‐built aspects of artificial specific intelligence (ASI) such as data discovery in genomics and facial recognition for physical device access, each applying select cognitive computing capability. In contrast, however, cognitive solutions bring together all the abilities to understand in context (i. e. comprehend), reason (deductive, inductive, abductive and adaptive), learn, and interact naturally with humans (natural language processing, natural language generation).
Cognitive systems take advantage of a plethora of data to create a more human‐like interaction with people, based on the method, type and the preference of each person. Because the volume of data being generated in today’s world is so large and happening so quickly, Watson can do what humans – and today’s programmable computers – simply can’t: ingest incredible amounts of data in every form imaginable to help support better decision‐making. Collating information such as geolocation, medical records and images, and transactional data with other details that have been traditionally difficult to access and understand: sentiment, emotions, personality – allowing cognitive systems to adapt to the individual. Continuously learning from these engagements, cognitive systems deliver increased value and are emotionally astute.
Secondly, cognitive systems are designed to help organizations augment and scale expertise in order to enhance the performance of their employees. With the pace of an industry’s and profession’s knowledge increasing at an untold rate, cognitive systems are able to master a domain’s language and terminology enabling professionals to become experts more efficiently. Cognitive computing represents a necessary next step in our ability to harness technology in the pursuit of knowledge – which goes beyond improving productivity and efficiency, to actually augmenting human decision‐making. Taught by leading experts in the field, systems like Watson learn at scale, reason with purpose and interact with humans naturally.
Business processes are also changing with the introduction of cognitive computing, transforming how a company operates. Incorporating internal and external data sources, cognitive systems enable organizations a greater awareness of processes, industry contexts and business environments – feeding a process of continuous improvement and operational excellence. Further amplified by the Internet of Things (IoT) which with the help of cognitive capabilities can sense, reason and learn about their users and the world.
Finally, cognitive systems equip businesses with perhaps their most powerful tool – a better vision, exploration and discovery of their future. From health research to product innovation, cognitive computing is allowing businesses to spot patterns, trends and opportunities that would be almost impossible for traditional programmatic systems to identify. To foster this level of innovation systems like Watson are built on an open platform, cloud accessible, a
llowing everyone access to the technology. This affords third parties the ability to build out services, products and solutions unencumbered by restrictions and benefiting from the ongoing investments made in R&D. In the case of Watson the user’s IP remains with the user as well as their data rights. This is a fundamental departure from what has been a growing trend for organizations to aggregate and take ownership of others’ content.
27.1.4 Stretching the Boundaries of Cognitive Computing
Cognitive computing has come a long way since Watson first appeared on the gameshow Jeopardy in 2011. The game playing Watson in that case was limited to understanding a single corpus of data and responding to a single questions. Today Watson can see images, helping radiologist make sense of MRIs and CAT scans, analyze audio and help music producers develop award winning songs, discover hidden patterns in geological patterns, navigate financial regulations, help optimize legal decisions, and more. In just five years, we have evolved from Watson at play to Watson at work, helping doctors, lawyers, accountants, and engineers, to name a few, address the growing challenges of their respective vocations and tackling some of societies greatest problems.
Cognitive computing is not a single thing but a compendium of capabilities, technologies, resources, services, and the like. By delivering a broad and robust set of individual APIs, systems like Watson spark creativity and business innovations. For example, in a short amount of time, we’ve seen Watson technology applied to everything from cutting edge cancer research and better understanding how diabetes works to oil exploration, educational toys and the world’s most complex financial systems. Watson’s industry domain knowledge continues to expand across industries and Watson has learned the idiosyncrasies and colloquialisms in languages like Arabic, Spanish, Brazilian Portuguese, Korean and Japanese, to name a few. We have witnessed the growth and adoption of cognitive technologies among industry leaders like Apple, Johnson & Johnson, Medtronic, Memorial Sloan‐Kettering, Thomson Reuters, Swiss Re, and many others. To scale systems like Watson globally, we have witnessed important partnerships with organizations such as SoftBank in Japan, SK Holdings C&C in Korea, Mubadala in the Middle East and Africa, and GBM in Latin America – all accelerating the availability of this new era of computing in their respective geographies.
In order to achieve all of this, and more, our approach to advancing Watson is to focus on three core tenets: science, simplicity and scale.
Science
Over the past two years, IBM has taught Watson new languages; increased its core knowledge of key industry domains; made it available via new form factors (tablets, smartphones, robotics and smart watches); and enhanced it with technology allowing it to “see”, understand tone and emotion, and more.
Simplicity
Our ongoing commitment to research, upwards of $6 billion a year is allowing us to make Watson easier to teach, easier to use, and easier to connect to existing technologies, systems, and data sets. As well as making it easier for developers to build Watson into their applications.
Scale
IBM is committed to scaling Watson by creating a repeatable, robust and secure platform that is flexible enough to use across a wide variety of domains and industries.
27.1.5 The Partnership on Artificial Intelligence
We have seen tremendous advances since 2014 in the deployment of cognitive technologies across industries and professions to address some of the world’s most complex challenges. In order to advance the public understanding and use of these technologies, IBM, Amazon, Google, Facebook and Microsoft have created a non‐profit organization, named the Partnership on Artificial Intelligence to Benefit People and Society. Together, the organization’s members will conduct research, recommend best practices, and publish research under an open license in areas such as ethics, fairness and inclusivity; transparency, privacy, and interoperability; collaboration between people and AI systems; and the trustworthiness, reliability and robustness of the technology.
AI has touched many parts of today’s world and cognitive computing is augmenting humans’ ability to understand – and act upon – the complex volumes of data being generated across society. Providing consumers of cognitive systems a critical voice in the development of this great technology – through rigorous research, the development of best practices, and an open and transparent dialogue – the founding members of the Partnership on AI hope to maximize this potential further and ensure it benefits as many people as possible.
27.2 The Implications of Cognitive Computing on Business
27.2.1 Without Cognitive You Cannot Achieve Digital Intelligence
Cognitive computing is a broad and flexible platform that can be applied to every company, industry and profession. Watson is helping inspire innovation and transformation. In a world where every business is digital, what is the differentiator? With data as an enabler those organizations that can infuse digital intelligence into the mix will be able to learn more, adapt faster, and provide a more personalized and relevant engagement with all stakeholders. Digital business is a recipe for growth, not a destination. Where data goes cognition follows, and can be embedded in everything we do – it will touch billions of people forever changing the world we live in.
27.2.2 Market Penetration
Healthcare & Life Sciences
Today, the healthcare industry is coping with a significant upheaval due to unprecedented disruption from economic, societal and industry influences. It’s an industry that is undergoing tremendous change with more than $8 trillion spent annually worldwide. In the U.S. it represents over 17% of the national GDP and is growing at an unsustainable rate. Health leaders are facing new and increasingly complex challenges; from rapid digitalization and rising consumer expectations to rising costs and shortages of skilled resources. As a result, it is critical that healthcare providers are smart in how they approach data in order to unlock its full potential and conquer the disruptive forces within the industry. Cognitive solutions provide new capabilities to health organizations and have the potential to transform disruption into focus.
In 2015, IBM launched Watson Health and the Watson Health Cloud platform. Since then, we have invested more than $4 billion dollars in acquisitions and partnerships to build up our capabilities. The key to success in this new space is access to large, diverse and meaningful data sets around health and health‐related activities. In just one year, we have amassed one of the world’s largest and most essential sets of health‐related data, including information on more than 300 million patients “lives” and more than 30 billion medical images. The Watson Health Cloud allows this information to be de‐identified, shared and combined with a dynamic and constantly growing aggregated view of clinical, research and social health data.
Watson Health will help improve the ability of doctors, researchers and insurers to innovate by surfacing insights from the massive amount of personal health data being created and shared daily. Cognitive systems can help increase consumer engagement, discover new trends in big data at an accelerated pace, and finally, augment intelligence to the optimize decision‐making processes. Oncologists across the world are leveraging cognitive computing as an assistant, trained by experts in the domain, to evaluate specific details of each patient against clinical evidence. Watson neither diagnoses nor prescribes. Rather, it analyzes massive amounts of medical data – ranging from EMRs to scientific papers to images – to provide doctors and care providers with the best information needed to make quick and informed decisions that support patient well‐being. We applied Watson to healthcare first because it is the most complex industry and contains the biggest data set imaginable.
With the power of cognitive computing, health organizations have a new resource to help address consumer and patient
concerns quickly and comprehensively. These systems have the ability to provide timely, evidence‐based support to clinicians, patients and consumers; providing individuals access to an expert assistant twenty‐four hours a day, seven days a week. With the ability to read millions of pages of text in a matter of seconds, cognitive systems are enabling health organizations to discover insights in their data that could potentially be missed with traditional methods; thus overcoming the restrictions faced today. What’s exciting to the medical community is Watson’s ability to help doctors keep up with the incredible volume of data and knowledge that is being generated, over 8000 new reports daily. Watson augments a doctor’s capability by bringing together all of the best available information and knowledge that humans have created. Watson looks at that data and brings forth the best of what we know.
Accurate, evidence‐based decision‐making is vital in the health industry as, very often, patient lives can depend on this. With the exponential growth in health related data, organizations must ensure they leverage insights for all their data to optimize decisions relating to spending, strategy and diagnoses whilst adhering to complex regulatory pressures. Watson works with doctors to assist them in their day‐to‐day routines, but ultimately it’s the doctors and patients that will make the final decisions on the course of action.
Financial Services
As banks struggle to balance fiscal responsibility, with operational complexity and regulatory mandates, cognitive computing is changing the way financial service organizations address these challenges through a data driven, human centric approach to decision‐making. Allowing personalized communication capabilities on a scalable platform, cognitive systems are drastically improving the way organizations approach areas like customer engagement in order to provide a better experience whilst simultaneously reducing inefficiency and poor experiences. For example, banks today are applying cognitive capabilities to provide personalized wealth management advice to assist the bank’s relationship managers in analyzing vast amounts of data including research reports, product information and customer profiles; identifying connections between customers’ needs and the growing corpus of investment knowledge, and weighing various financial options available to customers.
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