Machine Platform Crowd by McAfee and Brynjolfsson , 2017

1. Machine Platform Crowdby McAfee and Brynjolfsson, 2017 Summary of Book – Part 3 by Charles Tappert, CSIS, Pace University The information presented here, although greatly condensed, comes almost entirely from the course textbook.

2. The Triple Revolution • Machine versus Human Mind (Part 1) • Alpha Go by Google DeepMind defeats top player • Platforms versus Products (Part 2) • Uber owns no vehicles, Facebook creates no content, Airbnb owns no real estate • Crowd versus Core (Part 3) • GE’s crowd sourcing development process for its Opal ice maker

3. Part 3: Chap 10That escalated quickly: the emergence of the crowd • The crowd – defined as the startlingly large amount of human knowledge, expertise, and enthusiasm distributed all over the world online • The counterpart to the crowd is the core – defined as the knowledge, processes, expertise, and capabilities that companies have built up internally and across their supply chains

4. Part 3: Chap 10That escalated quickly: the emergence of the crowd • The difference between the Web and the world’s libraries highlights how dissimilar the crowd is from the core • Of the estimated 130 million books published, about 30 million are in the Library of Congress (largest) • The Web is bigger with even more on private sites • 2015 Includes 25 million books thanks primarily to Google • 2015 Over 45 billion webpages

5. Part 3: Chap 10That escalated quickly: the emergence of the crowd • The crowd is far more unruly than the core • It is inherently and deliberately decentralized and uncontrolled, enabling freedom of expression and innovation, which are potentially great • However, the uncontrolled nature of the crowd brings with it two difficult problems • Hard to find things in the ocean of information • Search engines have basically solved that problem • Some crowd members misbehave – fake news, etc. • Maybe machine learning systems can detect problems

6. Part 3: Chap 10That escalated quickly: the emergence of the crowd • The core remains relevant and useful • But the crowd has become an increasingly powerful force in this era of robust platforms • Although messy, the crowd is not unstructured • Its structure appears over time as a result of the interactions of its members

7. Part 3: Chap 10That escalated quickly: the emergence of the crowd • Crowd created collections accumulate the contributions of many people and spontaneous generate new kinds of knowledge • This was first pointed out by economist Hayek in a 1945 article “The Uses of Knowledge in Society” when debates were raging over whether centrally planned economies (like the Soviet Union) worked better than free market economies where planning is done by an undirected, decentralized crowd

8. Part 3: Chap 10That escalated quickly: the emergence of the crowd • Crowd sourcing can create highly useful products like Linux • Studying Linux’s history reveals some important principles for bringing the crowd together • Openness, noncredentialism, verifiable and reversible contributions, clear outcomes, self-organization, and geeky leadership

9. Part 3: Chap 10That escalated quickly: the emergence of the crowd • Crowd sourcing can create highly useful products like Linux • Studying Linux’s history reveals some important principles for bringing the crowd together • Openness, noncredentialism, verifiable and reversible contributions, clear outcomes, self-organization, and geeky leadership

10. Part 3: Chap 11Why the expert you know is not the expert you need • Some innovative scholars wanted a faster way to sequence genomes of human white blood cells, which are the body’s main defense against bacteria, viruses, and other antigens • At the time, two algorithms existed • MagaBLAST by NIH annotated 1 million sequences in 4.5 hours with 72% accuracy • idAb by Beth Israel Deaconess Medical Center did same in 48 minutes with 77% accuracy

11. Part 3: Chap 11Why the expert you know is not the expert you need • In 2013, the scholars posted a challenge on Topcoder, an online platform for computationally intense problems • Topcoder had a community of 400,000 coders • The data were divided into three datasets – public set for training, private set for testing, another private set for obtaining final scores • The contest ran for 14 days • 122 people/teams (69 countries) made 654 submissions

12. Part 3: Chap 11Why the expert you know is not the expert you need • The results were amazing • Eight submissions reached 80% accuracy, which the experts considered maximum for the dataset • The submissions at least as accurate as idAbran at an average of 89 seconds, 30 times faster • The three fastest ran in 16 sec, 180 times faster • The total prize money was $6,000

13. Part 3: Chap 11Why the expert you know is not the expert you need • Are these results exceptional or typical? • Over 700 challenges were run for NASA • Only one failure – crowd didn’t work on problem • Results on all others met or vastly exceeded the internal solutions that existed • Over and over again, the recognized core experts are beaten by uncredentialed and inexperienced members of the crowd • This is a pretty amazing finding!

14. Part 3: Chap 11Why the expert you know is not the expert you need • Why does this happen? • Mismatch – the core is often mismatched for the kinds of challenges it faces, while the crowd, because it’s so big, almost never is • Many problems and challenges benefit from being exposed to different perspectives • To people and teams with multiple dissimilar backgrounds, education, problem-solving approaches, intellectual and technical tool kits

15. Part 3: Chap 11Why the expert you know is not the expert you need • The crowd may change stock market trading • A number of hedge funds generate annualized returns of 12-15% • The Medallion Fund, open only to employees of Renaissance Tech, averaged >70% annual return for more than 20 years starting in the mid 1990s • Quantopian is hosting crowdsourced contests • Preliminary results are promising

16. Part 3: Chap 12The dream of decentralizing all things • Bitcoin – in 2008 a person or group going by the name Satoshi Nakamoto posted online a short paper titled “Bitcoin: a Peer-to-Peer Electronic Cash System” • It addressed the straightforward question • Why do online payments have to involve banks, credit cards, or other financial intermediaries? • Why can’t they be like cash payments • No associated fees and they preserve anonymity

17. Part 3: Chap 12The dream of decentralizing all things • Bitcoin is a cryptocurrency, not a fiat currency • It identifies, via digital signatures, who owns Bitcoins as they are used over time to pay for things online • A trusted ledger records the Bitcoins spent and the pseudo identity of both buyer and seller • In 2010 the first Bitcoin transaction occurred • 10,000 Bitcoins for a couple of pizzas

18. Part 3: Chap 12The dream of decentralizing all things • The blockchain technology of Bitcoin is now used to record all kinds of transactions • Many of these uses seemed to be motivated by a desire to decentralize activities previously concentrated, favoring the crowd over the core • The feeling was that the core had too much power and could not be trusted, and a survey found the financial services the least-trusted industry

19. Part 3: Chap 13Are companies passé? • In 2016 the purest expression of the crowd closed the largest round of crowdfunding ever • DAO = decentralized autonomous organization • Manifesto: existed “simultaneously nowhere and everywhere and operated solely with the steadfast iron will of immutable code” • Existed only as an open-source, distributed software for executing smart contracts • Support $ came – $162 mil within 28 days in 2016

20. Part 3: Chap 13Are companies passé? • The way of the DAO • Computer scientists found serious software flaws • A hacker stole 1/3 of the DAO’s money • An organization split, referred to as a “hard fork” divided the company into two parts • Ethereum and EthereumClassic continue to exist at the time the book was written • Basically, the DAO has faded away

21. Part 3: Chap 13Are companies passé? • Bitcoin’s bitter end? • In 2016 Mike Hearn, a key contributor to the programming effort, who had left Google, sold all his Bitcoins and left the project • He explained his decision in a blog – the community had failed with the system controlled by a few people, and as a result there is no longer much reason to think Bitcoin can actually be better than the existing financial system

22. Part 3: Chap 13Are companies passé? • The failure of The DAO and problems with Bitcoin indicate problems with the idea of completely decentralized organizations • Transaction cost economics and the theory of the firm are excellent bases for understanding these problems

23. Part 3: Chap 13Are companies passé? • However, technological progress and lowered transaction and coordination costs have helped new market business models to emerge • Nevertheless, economic activity is concentrating instead of dispersing • In most industries a smaller number of companies are capturing more of the value

24. Part 3: Chap 13Are companies passé? • No, companies are not passé! • Technology is progressing and the leading companies of the second machine age may look very different from those of the industrial era, but they will almost all be easily recognizable as companies

25. The Triple Revolution • Machine versus Human Mind (Part 1) • Alpha Go by Google DeepMind defeats top player • Platforms versus Products (Part 2) • Uber owns no vehicles, Facebook creates no content, Airbnb owns no real estate • Crowd versus Core (Part 3) • GE’s crowd sourcing development process for its Opal ice maker