Kollege Watson, übernehmen Sie ... oder: Was Systeme der künstlichen Intelligenz für den Arbeitsplatz bedeuten (können)

Editor's Notes

1. “Work: it’s what we do”. Regardless of the role we play, or industry we’re in, our work is fundamentally about 3 things: We work on and with content: we consume, create, and share reports, memos, widgets, ideas, education, training. We work together in teams: we plan, prioritize, collaborate, and communicate. And we follow processes, whether formal workflows or ad-hoc projects and exception handling. You’ll note that, in all three of those things, there are usually other people involved. Humans are biologically wired to consume information, to connect with each other, to set goals and move toward them. Consuming, connecting and creating are the essence of ‘collaboration’, and collaboration fosters both progress and innovation. However only about 1/3 of real value-added collaboration comes from less than 5% of employees. In the US, only 30% are actively engaged in the workplace. Extensive research shows that employee engagement is strongly connected to business outcomes essential to an organization's financial success, such as productivity, profitability and customer engagement. Engaged employees support the innovation, growth and revenue that their companies need And lastly, Gloria Mark of the University of California, Irvine found that a typical office worker gets only 11 minutes between each interruption, while it takes an average of 25 minutes to return to the original task after an interruption. Last year $588 billion dollars lost to U.S. businesses because of office work interruptions. We need a better way to collaborate, encourage engagement, and minimize the interruptions
2. A large part of this distraction is the unintended consequence of one of the most important booms to modern business: the rise of digitally-enabled collaborative work. We are all increasingly used to and adept at using social media in our personal lives. It is playing an increasing role at work, for example, using LinkedIn to connect with colleagues As a result, Harvard Business Review estimates that the time we spend at work in collaborative activities has increased 50% in the last decade. Collaborative work is uniquely adapted to deal effectively with complex challenges with multi-faceted solutions, requiring many different kinds of expertise. The office has become both physical and virtual where people collaborate; and individual work is increasingly occurring in shared spaces, or outside the office altogether. As they become increasingly digital, many organizations are remaking themselves into collections of small, agile teams of highly-skilled and often widely-dispersed individuals. Location-independent work has more than doubled (103%) since 2005, and an IPSOS/Reuters poll revealed that a fifth of the global workforce currently telecommutes. And we connect constantly to devices to access these experts and their information, as Mobile and Cloud have enabled ubiquitous (and constant) connectivity and accessibility of information, services, and people. Hence the resulting in distraction, an increased inability to think, and a lack of fulfillment – with the average employee being distracted once every 11 minutes -- and then needing an average of 25 minutes to refocus on tasks. People spend 80 percent of the workday on meetings, phone calls, and emails–leaving little time to get critical work done. Just in case you thought e-mail was dead: The Radicati Group research indicates that business email volume will raise from >100 billion mails sent/received per day in 2013 to >132 billion in 2017. This just proves that we typically don’t replace one collaboration mode with another, but rather add them on top of one another. Which leads to that noise and distraction problem.
3. We can no longer expect employees to remain satisfied with the tools that they are provided by the IT department when they know that there is a better way to accomplish tasks and achieve success. The best solution is often a "mashup" of technologies accessible from the cloud, rendered on a myriad of devices. But is that really the best way or just the way we have come to accept technology. These technology choices actually cause the interruptions. So, as we grapple with the unintended consequences of all this digital collaboration, it’s time to rethink the digital workplace. The very tools that have allowed us to access people and information from anywhere, almost instantaneously, are now causing disruption, distraction, and noise that is almost intolerable. One more digital workplace tool is no longer the right answer. It’s time to rethink the digital workplace. IBM has decided to change all this.
4. Cognitive solutions can understand, reason and learn – a cognitive business utilizes these attributes to think beyond the possible Understanding - The ability to understand data structured and unstructured, text-based or sensory in context and meaning, at astonishing speed & volume. Reasoning - The ability to form hypothesis, make considered arguments and prioritize recommendations to help humans make better decisions. Learning - The ability to ingest and accumulate data and insight from every interaction continuously. Is trained, not programmed, by experts who enhance, scale and accelerate their expertise.  
5. HOW ARE COGNITIVE SYSTEMS DIFFERENT?   The key reason cognitive businesses operate with an entirely different set of advantages is because they are using cognitive systems. Their abilities to get to data expand and deepen exponentially. They have programmed and probabilistic computing, giving them analysis plus hypotheses. They can interact with their business systems more naturally, more directly.
6. We see this assistance showing up in the form of two new type of team members. Personal Assistants that help workers to prioritize work and will handle an increasing number of basic, but time consuming tasks, like responding to email, scheduling meetings, and even helping users to understand the best tone for communicating with others based on their personalities. Experts will be sources that are trained to provide answers or insights to workers on a particular topic. If you remember Watson playing Jeopardy, you get a sense of how this could work, but rather than answering general questions, we foresee a time when Watson experts will be able to answer question, or point users to additional sources, on a huge number of topics includes industry specific, role specific or general business sources.
7. We see this assistance showing up in the form of two new type of team members. Personal Assistants that help workers to prioritize work and will handle an increasing number of basic, but time consuming tasks, like responding to email, scheduling meetings, and even helping users to understand the best tone for communicating with others based on their personalities. Experts will be sources that are trained to provide answers or insights to workers on a particular topic. If you remember Watson playing Jeopardy, you get a sense of how this could work, but rather than answering general questions, we foresee a time when Watson experts will be able to answer question, or point users to additional sources, on a huge number of topics includes industry specific, role specific or general business sources.
8. Visual Indicator on left shows me that Cognitive Inbox has promoted some emails with a level of actions. Opening this email will show WHY Watson is promoting this email. Purple highlight is an example of a repeatable collaborative action that the natural language processing found. At the top it picked up the fact is is a “REQUEST” and that it is “DUE SOON” and that they key person is “ELIZABETH SCHONFIELD” With the minus sign next to these items allow me to TEACH the system what is really important to me. So I remove Elizabeth and then click on the Show More and add Dan to the list
9. IBM Watson is available to expand and grow with a set of APIs in the cloud. All of these can be combined with other services available on Bluemix Our Watson APIs extend application to really enable better outcomes. Built with the latest AI technology, these APIs enable applications to see, talk, reason and learn. Higher Reasoning Skills – New APIs that With the IBM Watson Conversation service you can create virtual agents and bots that combine machine learning, natural language understanding, and integrated dialog tools to provide automated customer engagements. Foundational Cognitive skills- These APIs will analyze, tag, categorize and understand image content with apps that see. They work with previously unattainable information from unstructured data sets and train Watson to recognize content and deploy cognitive apps.. These APIs will allow for visual insight, recognition, and personality insights. And how does this relate to collaboration. Consider being able to analyze photos, and videos inside emails to understand customer preferences. Or get a deeper understanding of customer personalities so you can increase personalize messages for your customers. Or use visual recognition to help classify comments into logical categories to identify trends. Watson natural language APIs offer among the widest variety of speech and language services available. Develop apps that interact and engage at a deeper level when they carry on conversations with users and customers. Using these apps we can analyze emails and consider changes for a better email by using a tone analyzer which leverage written word to better identify emotion. Or make it easier to collaborate with using Watson to convert text to human voice. Knowledge Organization Skills – These APIs center around text analysis service functions, each of which uses sophisticated natural language processing techniques to analyze your content and add high-level semantic information. For example emotional Analysis helps build empathetic systems that uses state-of-the-art machine learning models and feature engineering techniques to predict emotion labels. Other APIs Entity Extraction: what are the entities (people, places, organizations, etc.) in text Sentiment Analysis: how are people talking about the entities (positive, negative) Keyword Extraction: identify important topics in content Concept Tagging: high-level concepts in text (e.g. article is about monetary policy) Relation Extraction: subject / action relations between entities Taxonomy Classifier: hierarchical categorization (finance/personal finance/credit card) Author Extraction: who wrote the article Language Detection: what language is this written in Text Extraction: extract the important parts of text within an article Microformat Parsing: enhances webpage categorization and indexing and to perform content discovery tasks Feed Detection:  discover new content, including blog posts, news articles and comment streams. Linked Data Support: bring any content into the semantic web We will be using these APIs to make collaboration solutions to help change the way you work. With taking advantage of language, data, text, and vision we can extend the human potential of everyone.
10. IBM Talent Insights, powered by Watson Analytics Anwender: HR Professionals, die das Management von der strategischen Seite her unterstützen Daten-Upload: Simple, mit drag&drop Daten-Analyse: 1.) Interaktive Daten-Exploration, 2.) Multi-Faktoren Treiber Analytics (Predictive Analytics), wenn man herausfinden will, welche Einflussfaktoren den grössten Einfluss auf ein Thema ausüben 3.) Eingebaute Resultat-Präsentationsfunktionen (Storytelling mit z.B. interagierenden Graphiken). IBM hat ein Starterkit verfügbar (Lizenzen und Services-Unterstützung)