Disruption ahead: Deloitte's point of view on IBM Watson8 9. What makes Watson unique In technical terms, IBM Watson is an advanced open-domain question answering (QA) system with deep natural language processing (NLP) capabilities. At this point, the Watson Software as a Service (SaaS) platform is most effectively used to sift through massive amounts of text--documents, emails, social posts, and more--to answer questions in real time. Watson accepts questions posed by the user in natural language and provides the user with a response (or a set of responses) by generating and evaluating various hypotheses around different interpretations of the question and possible answers to it. Unlike keyword-based search engines, which simply retrieve relevant documents, Watson gleans context from the question to provide the user with precise and relevant answers, along with confidence ratings and supporting evidence. Its learning capabilities allow Watson to adapt and improve hypothesis generation and evaluation processes over time through interactions with users. Developers and other users can improve the accuracy of responses by "training" Watson. IBM is also continuing to expand Watson's capabilities to incorporate visualization, reasoning, ability to relate to users, and deeper exploration to gain a broader understanding of the information content. Watson recently launched a new platform service that has the ability to ingest and interpret still and video images, which is another significant type of unstructured data.
Tom is an analyst at the US Department of Defense (DoD).1 All day long, he and his team collect and process massive amounts of data from a variety of sources--weather data from the National Weather Service, traffic information from the US Department of Transportation, military troop movements, public website comments, and social media posts--to assess potential threats and inform mission planning. While some of the information Tom's group collects is structured and can be categorized easily (such as tropical storms in progress or active military engagements), the vast majority is simply unstructured text, including social media conversations, comments on public websites, and narrative reports filed by field agents. Because the data is unstructured, it's difficult to find patterns and draw meaningful conclusions. Tom and his team spend much of their day poring over paper and digital documents to detect trends, patterns, and activity that could raise red flags. In response to these kinds of challenges, DoD's Defense Advanced Research Projects Agency (DARPA) recently created the Deep Exploration and Filtering of Text (DEFT) program, which uses natural language processing (NLP), a form of artificial intelligence, to automatically extract relevant information and help analysts derive actionable insights from it.2 Across government, whether in defense, transportation, human services, public safety, or health care, agencies struggle with a similar problem--making sense out of huge volumes of unstructured text to inform decisions, improve services, and save lives.
William D. Eggers is the executive director of the Deloitte Center for Government Insights. Dr. Peter Viechnicki is a strategic analysis manager and data scientist with the center. This piece is adapted from their new study, How much time and money can AI save government? Government agencies are no exception, and today this requires endless staff hours spent inputting, processing and sharing information across systems. The work needs to get done, so someone has to peck away at a keyboard, right?
The role of the CFO is undergoing a serious transformation, and CFOs can expect their role to continue to evolve, according to a recent CFO.com article by Deloitte COO and CFO Frank Friedman. In the futurist article, Friedman says one of the biggest factors that will contribute to the CFO's significant change over the next five years is technology. Digital technology is obviously expected to drive change in high-tech companies, but Friedman says it's industries outside of the tech sectors that are of particular interest, as they struggle to understand how to grasp and harness the digital capabilities available to them. Five years from now, a finance team may be defined by how well it uses technology and innovative business tools, regardless of what industry it's in. The article outlines some examples of ways that digital technology will increasingly be used by CFOs in "non-tech" sectors: The role of today's CFO has already expanded to include strategic corporate growth advice as well as managing the bottom line.