Andreas Weigend | Social Data Revolution | Fall 2014
School of Information | University of California at Berkeley | INFO 290A-03

Session

Topic

30 Sep
Social Data

Today, in a single day, humans today create and record more data than all of mankind managed to produce from its beginnings to the year 2000 The early generation of Internet companies such as Amazon and Google pioneered algorithms including item-based collaborative filtering and PageRank to refine these data to help users make better decisions, changing how a billion people buy items and find information. In this class, we will examine the birth of the Social Data Revolution in the cradle of e-commerce and online advertising, and consider its present and future.

The physical world today is permeated with sensors: mobile phones, wireless routers, payment systems, traffic cameras, electronic door keys. The class focuses on what can be learned about people through the massive amounts of data these connected devices are feeding the cloud with, allowing the same analytical techniques built for a digital world to be applied to our physical world, turning academic exercises into daily reality. We look into the ways in which data have entered, created by, and changed our lives, and consider a future filled with networked sensors.

Greg Tanaka, CEO of Bay Sensors, will share how physical stores are using cameras, microphones and other sensors for decisions ranging from staffing (taking into account everything including the scheduled national TV advertising campaign, weather forecast, and football schedule, how many people are needed in the store) to planogram (where to put what on the shelves), and pricing. If we had all the data available, how would you use the micro-emotions on the customer's face that the camera is picking up?
07 Oct
Social Graph

At its heart, the Social Data Revolution is a communication revolution that is transforming our economies and societies. Complex networks are formed through the interactions between individuals. Almost all their interactions with each other and the world leave digital traces. By studying human behavior on digital networks like Facebook, we acquire insights and techniques to understand and to influence people.

If you were Amazon, Facebook or a dating app, what experiments would you want to conduct? How do ideas propagate in a network? How are identity, reputation and trust created online? How has the notion of who we are, our identity, changed as social technology drives the transition from conspicuous consumption to ubiquitous communication? And in what ways has this changed our ideas and ideals of friendship and relationships?

Simon Zhang will discuss some of the data, algorithms and products of the data refinery LinkedIn.
21 Oct
Finance

When we think of using data to make better business decisions, we think of social networks and the promise of online services customized for every individual. It is easy to overlook many other forms of data that are already being constantly generated through the course of doing business. Consider MasterCard, a company with the data on billions of credit card transactions. How can we apply new techniques and ideas to these existing stockpiles of data to help people make better decisions, whether in combating fraud or determining retail trends? We look into unleashing the hidden potential of existing information silos by transforming them into data warehouses.


Max Levchin will discuss how Affirm uses the social graph for loan decisions.
28 Oct
(Part 1)
Work

The nature of the relationship between employers and employees has remained largely unchanged since the Industrial Revolution. Corporate employment is an ingrained part of the cultures of many developed countries. However, the Internet is creating new opportunities and redefining work in the post-industrial economy. In the online outsourcing model demonstrated by companies like oDesk and the flexible work schedules of Silicon Valley tech workers, we see the physical constraints of employment being eroded in various ways. At the same time, availability of new forms of data is transforming how workers are evaluated and how they evaluate their employers. Are all forms of data fair game for the employer, or do we still need time to establish new norms of what personal data belonging to the workers should be protected? We consider the balance of power between the two sides and how that is shifting in ways that are enabled by data.
28 Oct
(Part 2)
Sociometrics

For many decades, workplaces have been focusing on extracting the highest possible performance from individuals. From finding the individual with the perfect specifications to equipping them with information, technical and environmental infrastructure, efforts were centered on optimizing the individual’s work practice. However, the paradigm is changing. Industries now believe that individuals do not work alone, nor do they perform the best when they do. Companies spend millions of dollars on transforming their work space to be collaboration friendly and design community events encouraging informal interactions. But how do we know if their beliefs are actually true? And even if we know it is true, how do we justify how much they should invest on collaboration? Using sociometrics, a quantitative method for measuring social interactions, we unveil the value of collaboration. With quantified data on who people meet, the context they meet, and how they interact, we now have the ability to model the social factor of work. With all the data about how people collaborate, how can we achieve higher performing teams? How would evaluation of workers change? What other factors other than performance are related to the topic of collaboration?
28 Oct (Part 3)
Learning

In many ways, our current education system evolved to answer the needs of the post-Industrial Revolution economy – to train disciplined workers adept in a variety of standard skills. But just as corporate employment is being transformed by the Social Data Revolution, so will education. The present Massive Open Online Courses (MOOCs) are still not too far removed from the industrial model of mass-produced unidirectional teaching. When the goal of making all course materials freely available online has finally been realized, what comes after? With all the personalized data we have, how can we make education more effective? Is it possible to objectively measure the potential of a student, and if it were possible, should we do it? How will social data transform the relationships between students and teachers, and between students and students? Which functions of the institution of college will remain, which will be transformed, and which will cease to exist?
04 Nov
Fitness

Our well-being as humans is being augmented by data. Take a look on Kickstarter and you will find dozens of projects proposing wearables and sensors that will help us live better lives. Companies like 23andMe are applying analytics to understanding our genes and making the results shareable and social. Even the healthcare insurance system, cumbersome and full of legacy baggage, is gradually succumbing to the avalanche of data-driven business decisions that will transform the industry. As wearable sensors provide a deeper look into our daily routines, will understanding data better help us live healthier lives? How do we tell the difference between data that are easy to collect and data that actually help us understand the state of our health better? Is some information better than no information?
18 Nov
Data Ownership and the Future of Data

At the heart of the future direction of the Social Data Revolution lies the critical concept of data ownership. Who is in control of the data that we produce in our digital wake? And in our understanding of privacy as it relates to our digital data, what kind of implicit trade-offs are we really making? How much are we willing to pay for privacy? We also consider copyright and its manifestation in the digital world. Do we own the data that we inevitably create in our daily lives? In what sense can we exercise meaningful control over what we produce, both intentionally and incidentally, online? In asking these questions, we look towards the future of data.

Pete Warden, founder of Jetpac (now part of Google), will us his take on the question of data ownership and share some of his experiences working in the industry.