Augmented Collective Intelligence
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AUGMENTED. __COLLECTIVE__ INTELLIGENCE REPORT FULL HUMAN-AI NETWORKS IN A VIRTUAL FUTURE OF WORK GIANNI GIACOMELLI Gianni Giacomelli SUPERMIND.DESIGN Augmented Collective Intelligence Version 7.7.0 Last edit August 24, 2020 Download the latest at www.supermind.design Creative Common license terms here You are free to: Share — copy and redistribute the material in any medium or format; Adapt — remix, transform, and build upon the material for any purpose, even commercially. You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. Contacts: [email protected] https://www.linkedin.com/in/ggiacomelli/ Cover and chapter pages artwork credits: Bob Holzer, the Noun Project 1 Augmented Collective Intelligence Contents Contents ........................................................................................................................................................ 2 Acknowledgments ......................................................................................................................................... 4 About the author .......................................................................................................................................... 5 Prologue ...................................................................................................................................................... 6 Purpose and structure of this document ............................................................................................. 12 Overview .................................................................................................................................................... 17 “Man vs. machine”: a distracting, wrong perspective ............................................................................ 18 Conventional management practices aren’t enough ............................................................................. 21 The rise of machine-enabled networks of people, and machines .......................................................... 23 Network intelligences around, and inside, us ......................................................................................... 31 Building the four components of a supermind ....................................................................................... 40 First, illuminate the network............................................................................................................... 42 Second, direct and incentivize the network ....................................................................................... 43 Third, form “information feeders” ...................................................................................................... 44 Fourth, provide a platform for collaboration...................................................................................... 46 A workplan for a supermind ............................................................................................................... 48 What could we use a network intelligence for? ..................................................................................... 50 How to create a supermind .................................................................................................................... 58 A typical problem .................................................................................................................................... 59 A network intelligence’s architectural blueprint (or its garden layout) ................................................. 59 Module 1: the “who”. Illuminate the neural network ............................................................................ 70 Case studies – module 1 ..................................................................................................................... 80 In-depth case study module 1 – reskilling at scale ............................................................................. 80 Module 1 - technical notes ................................................................................................................. 84 Module 2: the “why”. Create and disseminate incentives aligned with meaningful goals .................. 106 Case studies – module 2 ................................................................................................................... 113 In-depth case study module 2 – reskilling at scale ........................................................................... 114 Module 2 - technical notes ............................................................................................................... 117 Module 3: the “what”. A knowledge and information feeder .............................................................. 126 Case studies - Module 3 .................................................................................................................... 132 In-depth case study module 3 – reskilling at scale ........................................................................... 134 Module 3 - technical notes ............................................................................................................... 136 2 Augmented Collective Intelligence Module 4: the “how”. Enable the network’s nodes to interoperate .................................................... 148 Case studies - Module 4 .................................................................................................................... 157 In-depth case study module 4 – reskilling at scale ........................................................................... 157 Module 4 - technical notes ............................................................................................................... 159 The process of designing a network intelligence .................................................................................. 183 Case study - Building superminds, and innovation capacity, at Takeda pharmaceuticals ................... 192 Things we must get smarter about ..................................................................................................... 194 Managing language in network intelligence ......................................................................................... 195 What can go wrong? ............................................................................................................................. 203 Managing thoroughly remote networks ............................................................................................... 208 Managing teams, and managing self, in a more remote and distributed work environment ............. 212 Harnessing the world supermind’s “circadian rhythm” for innovation processes ............................... 214 Conclusion ............................................................................................................................................... 218 E Pluribus Unum .................................................................................................................................... 219 References .............................................................................................................................................. 222 3 Augmented Collective Intelligence Acknowledgments The following people and organization have played an important role in the creation of this document. MIT Center for Collective Intelligence (CCI): Prof. Thomas Malone, founder of the center and Patrick J. McGovern Professor of Management at the MIT Sloan School of Management - for the many years of work generating research and fostering interest in collective intelligence; Kathleen Kennedy (executive director); Peter Gloor and Rob Laubacher (research scientists) and the rest of the CCI team including Annalyn Bachmann; as well as MIT Media Lab’s David Kong (director of community biotech initiative). Genpact’s CEO NV “Tiger” Tyagarajan and CHRO Piyush Mehta for their sponsorship of the world’s first known attempt to use network intelligence to reskill tens of thousands of people and make them a more adaptive workforce. Microsoft Asia’s president Ahmed Mazhari for his practical ideas on applying collective intelligence. Others provided input and feedback throughout. Among them: Peter Temes at the Institute for Innovation in Large Organizations (ILO) for insightful research on large enterprise adoption of predictive markets; Eric Alexandre and his thoughts on ecosystems; April Strategy’s Flavio Poli; Genpact’s Jay Scanlan for his insightful critique of parts of this document, and Sanjay Srivastava for his practical work on AI for the flow of work; Nesta’s Aleks Berditchevskaia for the focus on sharing knowledge about collective intelligence; Tejasvita Saran for her help in the application of social media to network analysis; University of Florence’s PhD Enrico Imbimbo for his curation of relevant materials; Jason Compton for editing part of the manuscript. 4 Augmented Collective Intelligence About the author It is all in the network: this report benefits from my exposure to both real-life management of large complex organizations, and academia’s unconstrained thinking. I am an innovation professional focused on large organizations, who’s spent a career harnessing the power of networks to generate and implement new ideas. As Chief of Innovation and part of our executive management team, I oversee the innovation