Society 4.0 (R)Evolution of Society? Förderschwerpunkt-Tagung Innovationsfähigkeit im demografischen Wandel Aachen, 8 th May 2014 Univ.-Prof. Dr. rer. nat. Sabina Jeschke Institute Cluster IMA/ZLW & IfU Faculty of Mechanical Engineering RWTH Aachen University www.ima-zlw-ifu.rwth-aachen.de
Outline 2 I. The Drivers: From Industry 4.0 to Everything 4.0 From Science Fiction, its realization its interconnection with big data over to its technological consequences II. Consequences: Selected Impressions of a Society 4.0 Economy Social Trends Culture Infrastructure & Mobility Technology III. Summary und Next Steps
The fourth industrial (r)evolution Industry 4.0 - Everybody and everything is networked 3 The first three industrial revolutions came about as a result of mechanisation, electricity and IT. The introduction of the Internet of Things is ushering in a fourth industrial revolution. Industry 4.0 will address and solve some of the challenges facing the world today such as resource and energy efficiency, urban production and demographic change. Henning Kagermann et.al., acatech, 2013 Vision of Wireless Next Generation System (WiNGS) Lab at the University of Texas at San Antonio, Dr. Kelley Weidmüller, Vision 2020 - Industrial Revolution 4.0 Intelligently networked, self-controlling manufacturing systems local to global local to global around 1750 around 1900 around 1970 today 1 st industrial revolution Mechanical production systematically using the power of water and steam Power revolution Centralized electric power infrastructure; mass production by division of labor Digital revolution Digital computing and communication technology, enhancing systems intelligence Information revolution Everybody and everything is networked networked information as a huge brain
The fourth industrial (r)evolution The drivers. Communication technology bandwidth and computational power Semantic technologies information integration Embedded systems miniaturization Watson 2011 4 Google Car 2012 Towards intelligent and (partly-) autonomous systems AND systems of systems around 1750 around 1900 around 1970 1 st industrial revolution Mechanical production systematically using the power of water and steam Power revolution Centralized electric power infrastructure; mass production by division of labor Digital revolution Digital computing and communication technology, enhancing systems intelligence today Information revolution Everybody and everything is networked networked information as a huge brain
Cyber-Physical Systems Towards complex and networked social-technical systems 5 let s have a look Communication Consumer Energy Infrastructure Health Care Manufacturing Military Robotics Transportation [CAR2CAR, 2011] and [ConnectSafe, 2011]
The fourth industrial (r)evolution Not restricted to industry: Cyber Physical Systems in all areas 6 Back to: The earth converted into a huge brain (Tesla 1926) Integrating complex information from multiple heterogenous sources opens multiple possibilities of optimization: e.g. energy consumption, security services, rescue services as well as increasing the quality of life Building automation Smart metering Smart grid Room automation Smart environment and more
Scientific challenges and achievements Two worlds coming together 7 Physical world Cyber-physical Digital world Manufacturing process Embedded Systems Material behavior Simulation Automation Unique Identifier Semantics Things Internet Service-oriented Closed System controllable and partly predictable by simulation CPS Open System difficult to control or to predict system behavior IOT
In search of a definition Let s ask Google 8 Big data is the term for a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications. The challenges include capture, curation, storage, search, sharing, transfer, analysis and visualization. Big Data refers to technologies and initiatives that involve data that is too diverse, fastchanging or massive for conventional technologies, skills and infrastructure to address efficiently. Said differently, the volume, velocity or variety of data is too great. But today, new technologies make it possible to realize value from Big Data. Every day, we create 2.5 quintillion bytes of data - so much that 90% of the data in the world today has been created in the last two years alone. This data comes from everywhere: sensors used to gather climate information, posts to social media sites, digital pictures and videos, purchase transaction records, and cell phone GPS signals to name a few. This data is big data.
A bit of a jump into the deep end Google Flu: predicting future (predicting the spread of diseases) 9 It all started with the flu [Google Correlate 2011] actual flu trend can be identified 7-10 days earlier by Google Flu Trends than by official data of the Center for Disease Control (CDC) [Helft 2008]
A bit of a jump into the deep end Pandemics: exploring new patterns of complex scenarios 10 A circle-model to foresee and to analyze pandemics [Brockmann and Helbing 2013] Computational work conducted at Northwestern University has led to a new mathematical theory for understanding the global spread of epidemics. [ScienceDaily 2013] The spreading takes place on the worldwide air transportation network of more than 4000 airports and 25000 direct links. [Brockmann/Helbing 2013] Is the spread of infectious diseases complex, or does it look just complex? [Erickson 2013] Using data of flights, trains, etc. the cities are rearranged. Result is simple: a circular wave that produces a stone in the water. Here: distances of places and countries adjusted depending on the flight connections
A bit of a jump into the deep end Predicting human behavior: transparent consumers 11 How Target figured out a teen girl was pregnant before her father did Unique Target Id Each interaction with retailer is assigned to that id Group of pregnant customers Customer Coupon campaign Customer profiles Clustering customers into groups, for example to identify disruptions in life (e. g. weddings, job changes and pregnancy) Andrew Pole Statistician working for Target Pole identified about 25 products that allowed him to assign each customer a pregnancy prediction score and the estimated due date
A look ahead Roboter Recruiting : Don't call us, we'll call you 12 in more and more companies, computer algorithms are part of the employment of new workers [Handelsblatt 03/2014]! CV data are combined with success data of the particular company or field Germany: about 40% USA: > 90% Great developers are everywhere, and Gild can prove it. on www.gild.com Fairness? different mental models between human and computer software based selection is incapable of analyzing true motivation, extraordinary engagement etc. Talents might be overlooked / lost But: Selection shows a higher degree of equal opportunities regarding gender, age, culture, etc. Selection shows a higher degree of tolerance in respect of disruptions in the CV
Outline 13 I. The Drivers: From Industry 4.0 to Everything 4.0 From Science Fiction, its realization its interconnection with big data over to its technological consequences II. Consequences: Selected Impressions of a Society 4.0 Economy Social Trends Culture Infrastructure & Mobility Technology III. Summary und Next Steps
Societal trends in Society 4.0 Digital natives entering the scene 14 Jerry King, The Digital Native Adressing pictures of the French poet Charles Baudelaire: When teens turn to networked publics, they do so to hang out with friends and be recognized by peers. They share in order to see and be seen., but how much they share is shaped by how public they want to be. They are, in effect, digital flâneurs. [Danah Boyd, 2014] Zur, O. & Zur, A. (2011): On Digital Immigrants and Digital Natives http://www.zuri nstitute.com/dig ital_divide.html Thinking and sensing VirtuaLive Telepresence, Teliris scanned reading picture-oriented virtuality-approved Learning game-based learning used to fast feedback Social life networked community-oriente Less attached to one company, one field, Working habits multi-tasking non-linear approach tech-savvy
Societal trends in Society 4.0 New business ecosystems are growing 15 Hybrid Organizations - Creation of the fourth sector Organizations which does not fit into the traditional categories public (government), private (business), and social (non-profit) sectors Partly: born digital Partly: born global New potential for growth through new value-chain partnerships around a globalized world Adress a variety of societal challenges, engagement as enabler for services Examples here: http://ncfsrp.org/article/what-fourth-sector Challenges for hybrid organizations Complexity of management models New business-models examples: Globalization Personalization Pay by the hour Legal Structure Organizational Culture & Talent Development Public / private partnership Private Sector Sponsorship / partnership Social entrepreneurship Civic / social sector Public Sector Tania Ellis, The New Pioneers, Wiley 2010 Service delivery
Economical trends in Society 4.0 Crowdsourcing giving way for new cooperation forms 16 Crowdsourcing Crowdsourcing is the act of taking a job traditionally performed by a designated agent (usually an employee) and outsourcing it to an undefined, generally large group of people in the form of an open call. Jeff Howe, 2012 Crowdsourcing.org! Various categories: Collective Knowledge Creative Content-Marketplace Open Innovation & Ideas Crowdfunding Engagement & Charity Example: InnoCentive (exchange-place to solve research-problems) New forms of employment: traditional forms of permanent positions will change Growing need for cross-company networks
Economical trends in Society 4.0 Knowledge Orientation and the creative class 17 Knowledge Based Economy! New global knowledge elite the creative class Rising levels of education around the world and lifelong-learning Data and knowledge based value creation (Open and Closed) innovation as a key driver and competition factor Potential for new social disequilibria Potential for new social schisms One new driver: Internet of Services Most innovative companies base on User-driven connection of IT-services (Salesforce.com) Life-transforming products (Alexion) Est. volume until 2025: over 20 billion Enabling new forms of cooperation Especially potential for SME as service provider for bigger companies Web-based services and functions shown as granular software components Combination of these services and functions on demand enabling ad hoc complex solutions
Economical trends in Society 4.0 New production paradigms and new consumption patterns 18 Individualization on production level! Shifts in consumer spending/preferences Individualized products Growing collaborative consumption Catch-up consumption in newly industrialized countries Hybrid and virtual models Production partly leaving the factory hall Rapid prototyping Small batch series, e.g. spare parts. 3D-Printing as flexible manufacturing process Shortening of value chains Reduction of stocks Higher flexibility in design and on-demand production
Societal trends in Society 4.0 Living in Health 4.0 19 Health 4.0 A connected scenario focusing on prevention and fitness Smart Data as enabler Analysis of anonymized patient data Development of empirical and evidence based treatments New way of cooperation New business models beyond healthcare Analysis of sensor data rises to interdisciplinary questions Wireless diabets management system Cellnovo [ Get Mobile, Get Healthy: The Appification of Health and Fitness by Mobiquity / Research Now] Leading to a quantified self Study: 53%: eating more calories than realized 73% more healthy because they use apps to track health/fitness 63% intend to continue or increase their mobile health tracking over the next 5years
Societal trends in Society 4.0 Individualization on all levels 20 Globalized Individualization!!! Personal level: Complex biographies and identities Educational level: Support of individual learning styles Shift in learning models as e.g. by more hybrid fields of study, Bologna, MOOC etc. Work level: A large variety of profiles for the future world of work A large variety of job profiles Technological Level: Smart systems all around Economical Level: DIY economies Individual Products: leading from mass markets to micro markets and postponement production Solving the scale scope dilemma of production through Industry 4.0
Technology Design in Society 4.0 New work world with new players on board 21 New Working World! Highly flexible working practices New ergonomical, managerial and organisational patterns Digitalisation of the world of work Collaborative methods of working Advances in automation Enhanced human robot cooperation Contribution to demographic change Technical world New phase of automation technology Robots outside fences/cages Mobile robotics Robots in everyday life Globalized organizations Structures above geographical distances Globalized virtual communication Human resource management Active Sourcing 4.0 New recruiting structures à la Amazon IT-supported recruiting Shift from permanently employed to temporarily employed Organizational functioning New types of organizations New ways of performance and success measurement Centered on the human as social being Public leadership of employees
Technology Design in Society 4.0 Towards a transparent technology: organic computing 22 following social systems and biological models Hardware Division of labor Macro-scale Automation Micro-scale Multi-Core Learning form nature: Natural paradigms as key characteristics of innovation in hardware, software, algorithms, procedures, behaviour Software Service oriented Agentbased Speech Multimodal communication modes Touch! Bionics enter design and technology Decentralisation of complex scenarios Peer2peer designs in technology, symmetrical actor-network concepts Sustainability and resource-efficience in architecture, automotive lightweight, Facial sciencedirect.com Emotion Fraunhofer IOSB Affective Computing Michael S. Ryoo, CalTech
Energy technology in Society 4.0 Beyond traditional energy conversion: energy harvesting 23 Energy Harvesting Using residual energy from the environment Multiple kinds of energy harvesting: photovoltaic, kinetic, thermoelectric! Examples: wireless autonomous sensors and other devices, biomedical implants from environment and machines up to human energy harvesting Indefinitely operation of sensor nodes Several future scenarios and their use cases: Thermo electric harvesting Piezo electric harvesting Wave harvesting
Outline 24 I. The Drivers: From Industry 4.0 to Everything 4.0 From Science Fiction, its realization its interconnection with big data over to its technological consequences II. Consequences: Selected Impressions of a Society 4.0 Economy Social Trends Culture Infrastructure & Mobility Technology III. Summary und Next Steps
Summary Demographic Change other changes in society 25! Changes of society in comparison System-speed determined by the fastest (or: most critical) subsystem Influence on society Long-term perspective? Influence of demographical change to the overall system?? Smart Data 3D virtual production Industry 4.0 / Internet of Things Demographic change Time
Summary Society 4.0 Evolution of Interconnected Consciousness 26 Up to now Version 4.0 Scharner: From Ego-system to Eco-system Economies: How to Build Collective Leadership Capacity (2012) Connected Eco-System Social Market Collective and awareness State Centric Networking as central aspect Regulation and hierachy Community - System Focus on own community Community Global awareness
Summary Everything 4.0: Not only a scientific and/or technological challenge 27 Diversity Young to old, able and disabled, rich and poor, literate and illiterate, Expectations 24/7 availability, 100% reliability, 100% connectivity, instantaneous response, store anything and everything forever Privacy Individual private levels, context-situative Science Society How can we provide people and society with Cyber-Physical Systems they can trust? Technology Challenges Boundaries are unknown and always changing Complex systems are unpredictable (How) can we build systems that interface between the cyber world and the physical world? Ideally, with predictable, or at least adaptable behavior. Adapted from [CPS Summit, 2008]
Summary Research 4.0 : Cybernetics as a way to handle complex systems 28! Cybernetics - Management of Uncertainty Handling of uncertainties resulting from internal processes, changing environment and highly time-dependent processes is a core issue in organizational and system design. on the way to a learning system Analysis of interdependencies Multiple recurrence levels Iterative feedback loops Self-regulation Experimental approach 1. Starting experiments, 2. Tight result sensorics, 3. If necessary: fast re-adjusting Renunciation from a master plan Enabling culture! Culture of fault tolerance!
Summary Education 4.0: Leading to new models in science and education 29 QSR International, Education 4.0 The innovation and development of Cyber- Physical Systems will require computer scientists and network professionals to work with experts in various disciplines. This, [ ], will revolutionize how universities educate engineers and scientists. [Rajkumar, Cyber-Physical Systems: the next computing revolution, 2010] Partnership for 21st Century Skills: 21st Century Skills, Education & Competitiveness A Resource and Policy Guide (2008) Thinking critically and making judgements Solving complex, multidisciplinary, open-ended problems 21 st Century skillset Making innovative use of knowledge and information Communicating and collaborating Creativity and entrepreneurial thinking Global communication, global thinking
30 Thank you for your Attention! Univ.-Prof. Dr. rer. nat. Sabina Jeschke Head of Institute Cluster IMA/ZLW & IfU phone: +49 241-80-91110 sabina.jeschke@ima-zlw-ifu.rwth-aachen.de Co-authored by: Dipl.-Ing. Thomas Thiele Research Group Knowledge Engineering phone: +49 241-80-91168 thomas.thiele@ima-zlw-ifu.rwth-aachen.de Markus Kowalski M.Sc. Research Group Knowledge Engineering phone: +49 241-80-91186 markus.kowalski@ima-zlw-ifu.rwth-aachen.de www.ima-zlw-ifu.rwth-aachen.de
Prof. Dr. rer. nat. Sabina Jeschke 31 1968 Born in Kungälv/Schweden 1991 Birth of Son Björn-Marcel 1991 1997 Studies of Physics, Mathematics, Computer Sciences, TU Berlin 1994 NASA Ames Research Center, Moffett Field, CA/USA 10/1994 Fellowship Studienstiftung des Deutschen Volkes 1997 Diploma Physics 1997 2000 Research Fellow, TU Berlin, Institute for Mathematics 2000 2001 Lecturer, Georgia Institute of Technology, GA/USA 2001 2004 Project leadership, TU Berlin, Institute for Mathematics 04/2004 Ph.D. (Dr. rer. nat.), TU Berlin, in the field of Computer Sciences from 2004 Set-up and leadership of the Multimedia-Center at the TU Berlin 2005 2007 Juniorprofessor New Media in Mathematics & Sciences & Director of the Media-center MuLF, TU Berlin 2007 2009 Univ.-Professor, Institute for IT Service Technologies (IITS) & Director of the Computer Center (RUS), Department of Electrical Engineering, University of Stuttgart since 06/2009 Univ.-Professor, Institute for Information Management in Mechanical Engineering (IMA) & Center for Learning and Knowledge Management (ZLW) & Institute for Management Cybernetics (IfU), RWTH Aachen University since 10/2011 Vice dean of the department of Mechanical Engineering, RWTH Aachen University since 03/2012 Chairwoman VDI Aachen
References 32 [Alberti, 2011] [BMI, 2011] [Gleich, 2010] [Grimme, 2012] Elisa Alberti, Smart Mobility Vision Report Deliverable of the Project Smart Metropolitan Areas Realised Through Innovation & People, 2011 Federal Ministry of the Interior, Demography Report - Federal Government Report on the Demographic Situation and Future Development of Germany, Rostock, 2011. Gleich et al., PricewaterhouseCoopers AG Wirtschaftsprüfungsgesellschaft, European Business School Geschäftsmodellinnovationen - Neue Wege am Markt beschreiten, 2010. Grimme-Institut, Gesellschaftg für Medien, Bildung und Kultur, Im Blickpunkt: Crowd Sourcing Marl, 2012. [Malone, 2013] Thomas W. Malone, MIT Center for Collective Intelligence, The future of work: How can we create more intelligent organizations? 2013. [ISI, 2006] Steffen Kinkel, Gunther Lay, Fraunhofer Institut System- und Innovationsforschung Technologietrends in der Produktion, Karlsruhe, 2006. [PTIDES] http://www.eecs.berkeley.edu/research/projects/data/101935.html; last visited on 22 th February 2013 [WBCSD, 2010] World Business Council for Sustainable Development; Vision 2050 Neue Agenda für Unternehmen, 2010. [Weller, 2013] Ingo Weller, Digitalisierung und Vernetzung: Chancen und Potentiale für Mitarbeiter und Human Resource Management, Presentation at the conference Münchener Kreis - Fachtagung Oktober 2013 München, 2013. [VDI, 2011] Wolfgang Luther et al., VDI Technologiezentrum, Nanotechnologie in der Natur Bionik im Betrieb Düsseldorf, 2011. [VDI, 2012] VDI Positionspapier, Zukunft der Bionik - Interdisziplinäre Forschung stärken und Innovationspotenziale nutzen, 2012. [Z_punkt] Z_punkt The foresight company, MEGATRENDS update.
Research on an Interdisciplinary Sandwich with Changing Paradigms Cyber Physical Systems alias Industry 4.0 33 Embedded systems miniaturization Semantic technologies - representing the field of artificial intelligence information integration Communication technology bandwidth and computational power Physical world Cyber-physical Digital world Reactivity Schedulability Diagram adopted from R. Alur, Uni. Penn Material beyond nature Time Concepts in Computer Sciences CPS Bottom up vs. Top down Living with Uncertainty @ ABB Bionic Principles IOT
Two Worlds coming together Everything 4.0: The Big Data Connection 34 Distributed Systems Big data - Volume AI Distributed sources SMART Distributed storage Distributed computing Velocity Distributed Artificial Intelligence Real-time capability Autonomy Variety Veracity Social media data DISTRIBUTED DS Natural language analysis Prediction Smart data Artificial Intelligence