Special Topics in Information
Specific topics, hours and credit may vary from section to section, year to year. May be repeated for credit with change in content.
In this course, we will survey a broad range of “alternative” thinkers — including, but not limited to, Mahatma Gandhi, Rabindranath Tagore, Ivan Illich, Paulo Freire, and E.F. Schumacher — and try to derive some potential implications of each of their ideas for the design and use of technological artifacts. For each, we will try to understand their perspectives on technology, society, and human development and the underlying values that drive these perspectives, and to apply these values to practical design considerations. The course will consist of weekly readings, discussion, and regular design activities.
Specific topics, hours and credit may vary from section to section, year to year. May be repeated for credit with change in content.
This course will explore how legal, ethical, and economic frameworks enable and constrain security technologies and policies. As digital technologies penetrate deeply into almost every aspect of human experience, a broad range of social-political-economic-legal-ethical-military and other non-technical considerations have come to envelope the cybersecurity landscape. Though cybersecurity itself is a technical discipline, these non-technical considerations constrain it, enable it, and give it shape. We will explore the most important of these elements. The course will introduce some of the most important macro-elements (such as national security considerations and the interests of nation-states) and micro-elements (such as behavioral economic insights into how people understand and interact with security features). Specific topics include policymaking (on the national, international, and organizational level), business models, legal frameworks (including duties of security, privacy issues, law enforcement access issues, computer hacking, intellectual property, and economic/military/intellectual property espionage), standards making, and the roles of users, government, and industry.
As new sources of digital data proliferate in developing economies, there is the exciting possibility that such data could be used to benefit the world’s poor. Recent examples from the research literature show how satellite imagery and deep learning can be used to identify and target pockets of extreme poverty; how mobile phone metadata can help track and stop the spread of malaria and Ebola; how social media analytics can improve disaster response; and how machine learning algorithms can help smallholder farmers optimize planting and harvesting decisions – to name just a few examples.
Through a careful reading of recent research papers and through hands-on analysis of large-scale datasets, this course introduces students to the opportunities and challenges for data-intensive approaches to international development. Students should be prepared to dissect, discuss, and replicate academic publications from several fields including development economics, machine learning, information science, and computational social science. Students will also conduct original statistical and computational analysis of real-world data, and are expected to have prior graduate training in machine learning, econometrics, or a related field.
Many products of human invention — political speeches, product reviews, status updates on Twitter and Facebook, literary texts, music and paintings — have been analyzed, not uncontroversially, as “data”. In this graduate-level course (open to all departments, especially those in the humanities and social sciences), we will pursue two ends: we will investigate the landscape of modern quantitative methods for treating data as a lens onto the world, surveying a range of methods in machine learning and data analysis that leverage information produced by people in order to draw inferences (such as discerning the authorship of documents and the political position of social media users, charting the reuse of language in legislative bills, tagging the genres of songs, and extracting social networks from literary texts). Second, we will cast a critical eye on those methods, and investigate the assumptions those algorithms make about the world and the data through which we see it, in order to understand their limitations and when to apply them. How and when can empirical methods support other forms of argumentation, and what are their limits? Many of these techniques are shared among the nascent communities of practice known as “computational social science”, “computational journalism” and the “digital humanities”; this course provides foundational skills for students to conduct their own research in these areas. No computational background is required.
This is an introductory course on design, problem solving and innovation. While the principles generalize to any context, this course focuses on solutions that take the form of digital goods and services.
This is a team-based, experiential learning course. Students who take this course should expect to:
Work with a team that includes different backgrounds, interests, and personal motivations. As a cross-listed course, teams may or may not include students from different schools across the University (depending upon enrollment).
Experience a process for identifying and prioritizing opportunities to innovate. The process scales from an entrepreneur working alone to Fortune 500 firms managing an innovation portfolio.
Practice applying qualitative processes (including customer interviews, paper prototyping, and remote user-testing) to characterize the "job to be done," isolate a "minimum viable problem," and iterate your design prototypes.
Practice applying quantitative processes (including analysis of keyword searches, digital ad campaigns, and funnel analysis) to characterize the "job to be done," isolate a "minimum viable problem," and iterate your design prototypes.
Formulate hypotheses and then design and execute experiments in a Lean cycle of build, measure and learn.
Teams will learn general principles of product/service design in the context of tools, methods, and concepts specific to the Web-based environment. Both desktop and mobile products and services are prototyped in the Web context to leverage common development and testing resources. For purposes of the course, the product or service should be aimed at consumers in the range 25 - 45. We define this target audience so that we can use classmates as preliminary subjects of interviews, testing, and surveys. For the purposes of this course, the product or service need not have a compelling business model. The focus is on creating a product or service that solves a real problem, not necessarily creating a new business.
This course teaches a process-oriented approach to product and service design with heavy emphasis on user experience design. Students interested in design aesthetics, semiotics and cognitive psychology should look elsewhere. Neither is this a class about technology. The course syllabus does not include tutorials on specific software packages. Students interested in technical questions such as platform selection and scaling should look elsewhere.
The mobile landscape is constantly changing — new devices, new operating systems, new applications. Even seasoned designers are overwhelmed by the chaos, sometimes creating less than optimal designs that are soon outdated. But the successful designs, the ones that surprise and delight their users, look beyond the here and now.
Designing Mobile Experiences will start with an overview of current device and OS differences, featuring guest lecturers with deep Android and iOS expertise. The second part of the course will lay the foundation to create mobile application designs that can truly stand the test of time. Some of the topics we’ll cover include: exploratory mobile research, gesture design, and touch design. The latter part of the course will introduce ways to bring apps to life through animation, sound, and prototyping.
Course material will be covered through lectures, in class activities, readings, and a group project. Early in the semester students will pitch mobile application ideas; they will spend the rest of the term iteratively designing the app with their teammates. Ongoing design critiques will be provided by the instructor, classmates, and industry leaders.
Priority for attending this class is given to I School students. Programming mobile applications will not be covered in the course.
This seminar will explore the educational technology (Edtech) sector from policy, design, and legal lenses. Edtech is among the most exciting fields for personalization because such tools may enhance learning. But in practice, Edtech is often poorly implemented. An OECD report recently found that “student performance is mixed at best” from the incorporation of internet and communication technologies in the classroom. At least four different privacy regulatory regimes touch Edtech, yet enthusiasm for the field remains high, with venture funding now reaching almost $2b for the sector. This seminar, following a problem-based learning approach, will explore the Edtech field in depth. What can we realistically expect from Edtech? How can Edtech be used most efficaciously? How do we regulate student privacy and why? How can technology serve the regulatory requirements and ends of policy?
This course introduces students to experimentation in the social sciences. This topic has increased considerably in importance since 1995, as researchers have learned to think creatively about how to generate data in more scientific ways, and developments in information technology have facilitated the development of better data gathering. Key to this area of inquiry is the insight that correlation does not necessarily imply causality. In this course, we learn how to use experiments to establish causal effects and how to be appropriately skeptical of findings from observational data.
The ability to manipulate, explore, and analyze structured data sets is foundational to the modern practice of data science. This course introduces students to data analysis using the Python programming language, especially the core packages NumPy and pandas. Student learn to operate on data, think critically about features they uncover, and organize results into a persuasive analysis. Best practices for writing code in a functional style are emphasized throughout the course. A set of weekly programming assignments reinforces and builds upon the techniques presented in lecture. The course culminates in a final project in which students write a professional quality analysis based on their own research questions.
This course forms the second half of a sequence that begins with INFO 206. It may also be taken as a stand-alone course by any student that has extensive Python experience.
This one-credit reading group, sponsored by the Center for Long-Term Cybersecurity, will discuss contemporary cybersecurity policy problems. The seminar will focus on future trends in technology, as well as the economy and politics, and how those are affecting cybersecurity policy. Topics may include encryption, autonomous vehicles, and the ethics of artificial intelligence. Students would be required to attend weekly 50-minute sessions, present short papers on the readings, and write response pieces.
This course addresses the fast-growing area of social and environmental measurement using technologies such as mobile devices, "Internet of Things" (or "Web of Things") style sensors, and remote sensing. We will take a project-based approach, with a classroom discussion each week, followed by a tutorial / practicum in BIDS. Note that the focus of this course is on data collection and management. Teams will likely do some basic visualization and exploratory data analysis; statistics and/or machine learning are not expected. We will leverage support from the Social Science Matrix, the D-Lab, BIDS, CEGA, and Berkeley Research Computing to provide necessary training, hardware, and compute resources. This course is being offered as a part of the Data Science Collaborative at the Berkeley Institute of Data Science (BIDS).
Specific topics, hours and credit may vary from section to section, year to year. May be repeated for credit with change in content.
This course considers at the Internet of Things (IoT) as the general theme of real-world things becoming increasingly visible and actionable via Internet and Web technologies. The goal of the course is to take a top-down as well as a bottom-up approach, thereby providing students with a comprehensive understanding of the IoT: from a technical viewpoint as well as considering the societal and economic impact of the IoT.
By looking at a variety of real-world application scenarios of the IoT and diverse implemented applications, the various understandings and requirements of IoT applications become apparent. This allows students to understand what IoT technologies are used for today, and what is required in certain scenarios. By looking at a variety of existing and developing technologies and architectural principles, students gain a better understanding of the types of technologies that are available and in use today and can be utilized to implement IoT solutions. Finally, students will be given the opportunity to apply these technologies to tackle scenarios of their choice in teams of two or three, using an experimental platform for implementing prototypes and testing them as running applications. At the end of the semester, all project teams will present their completed projects.
In this seminar we will investigate the frontier of the concept of leadership by exploring how data analytics can help leaders develop and perform better, and enable stakeholders to better track and govern the conduct of leader behaviors.
Data analytics is making inroads into all areas of the economy, including management. Yet the practice of leadership is still seen as an art, not a science. As a result, research on leadership has been restricted by limited data and limited perspectives. That may change with advances in data analytics. Yet that brings up fascinating issues such as can leadership ever be reduced to data analysis? And, if it can, should it be?
In particular, we will explore the concept of leadership development through the lens of analytics by trying to answer the following question: How can smarts “apps” help leaders practice leadership competencies, get feedback on their behaviors, and modify their behaviors in order to improve?
Topics to be included: leadership development, theories of personal development, “nudging” theory, deliberate practice theory, social feedback technology, and the examination of existing "apps" and online tools that can be applied to leadership analytics.
This workshop will be a discussion seminar, where we will all prepare the material for the class and discuss it as a group.
Marketers want to deliver timely and relevant messages to their customers in support of brand building, acquisition, cross-sell, and retention. Though there are a wide array of channels, tools, and technologies available to multi-channel, multi-product marketers, the path to success is not an easy one.
The most formidable challenges include:
- What Are the Delivery Tools and Technologies Available to Marketers?
- Where and How to Spend Marketing Dollars Most Effectively?
- What Metrics Should Be Set to Gauge Success?
- What Data Are Available to and Generated by the Ecosystem?
The tools, metrics, and data used to execute and evaluate marketing spend can be described as the marketing analytics “ecosystem.” A common industry term is the “marketing technology stack.”
This class will provide a topical overview to the ecosystem and by the end of the class, have an understanding the connectivity between the marketing technology stack, the data utilized, data generated and useful metrics. This background is essential for students interesting in how marketing can drive successful outcomes for customers and for the business.
Visual and multi-modal media are central to much of what we do in the I School and related disciplines. Data collection, reports, and presentations, face-to-face and distant, online and off, often rely heavily on visual and audio media. Because we are a media-literate society, with accessible hardware and software plus easy online distribution, it seems that everyone “knows" how to make and critique such media. However, our knowledge about how to effectively make, use, and present these media trails far behind our ability to create hours and gigabytes of content. Furthermore, it’s useful to consider how these resources are changing not just professional and research practice.
In this seminar, we will address both theoretical and practical issues of capturing and creating narratives with video, audio, and still images. We will draw on photojournalism, visual narrative, visual anthropology, visual studies, and related areas. We will get hands-on experience creating and editing our own media. This is not a technical course; nor is it a media production how-to. But you will get experience with media technologies while we reflect on them with the help of theoreticians and scholars in relevant areas.
This course is relevant to students in professional schools and to doctoral students interested in and qualitative research, including user experience research; technology designers who produce video scenarios and concept videos; and anyone concerned with collecting and presenting information via multiple media.
No prior experience is necessary, but students who are already grappling with visual (and audio) media will find this course especially useful. I School students are likely to find this course useful for the doing and presenting of final projects.
This is a weekly one-hour seminar on the latest topics in the field of Natural Language Processing (also known as Computational Linguistics). Researchers from across UC Berkeley as well as visitors from out of town will present their recent work for discussion and feedback. Past topics have included multilingual language processing, analyzing social text, analyzing text using joint models, unsupervised morphology induction using word embeddings, deep learning of visual question answering, and unsupervised transcription of music and language.
In Fall 2016, we will meet every week, with alternating weeks consisting of discussions of readings and presentations of new research by local and visiting speakers.
Anyone is welcome to audit the course. Graduate students and undergraduates may enroll in this course for 1 unit of credit. In order to earn that unit of credit, students must write a synopsis of a research paper every two weeks, must attend at least 11 class meetings (and arrive on time), and must lead (or co-lead) at least one discussion of a research paper during the course of the semester.
This course covers the fundamental data structures and algorithms found in many technical interviews. These data structures include (but are not limited to): lists, stacks, queues, trees, heaps, hashes, and graphs. Algorithms, such as those for sorting and searching, will also be covered, along with an analysis of their time and space complexity. Students will learn to recognize when these data structures and algorithms are applicable, implement them in a group setting, and evaluate their relative advantages and disadvantages.
There is a burgeoning market for technologists and lawyers who can understand the application and implementation of privacy and security rules to network connected services. Privacy and Security Lab is a new course designed to promote the development of such “privacy technologists.” Students will meet twice a week, once in lecture, and the second time in a computer lab to gain hands-on skills in privacy and security analysis. The course will explore the concepts, regulations, technologies, and business practices in privacy and security, including how different definitions of “privacy” may shape technical implementation of information-intensive services; the nature of privacy and security enhancing services; and how one might technically evaluate the privacy and security claims made by service providers. There are no prerequisites and enrollment is open to law students to encourage cross-disciplinary exchanges.
This course gives participants hands-on software product design experience based on current industry practice. The course is project-based with an emphasis on iteration, practice, and critique from experienced industry designers. During the course, participants work iteratively on a series of design projects (both solo and in groups) through a full design process, including developing appropriate design deliverables and gathering feedback. We’ll also cover specific topics, including design and prototyping tools, working with and developing design systems, typical phases and deliverables of the design process, and designing in different contexts (e.g. startups vs. larger companies). There will also be guest lectures from industry experts.
There are few terrains that evoke such socio-political anxieties and ambitions as the human body. Our contemporary moment is characterized by a shift in who can understand, analyze and ‘hack’ the body. Consumer biosensors, citizen science movements such as biohacking, and patient power movements such as participatory medicine, all use technology to challenge the status quo around who can demonstrate expertise about the body. They bring both opportunities and responsibilities. How do we engage with this computational turn that now marks the everyday experience of our biology?
In this course, we will take a close look at critical debates and scholarship about the body. We will draw from art, design, theory and activism. This course will introduce and ground itself in the philosophies of critical technical practice and reflective design. That is, not only will we examine the various ways in which society conceives of the body, through the lens of data, posthumanism, nation, race, gender and dis/ability, we will also unpack how we have been personally formed by those very debates and influences. What underlying values and assumptions do you bring to engaging the body through technology? What kinds of norms are you reinforcing with your actions? What would you like to change?
This course will culminate in a set of group projects, all in conversation with each other, that we will publish online in service to a public audience. Each group project will offer a critical and reflective perspective on a theme of your choosing. You will choose a trajectory most suitable to your learning and communication preference, from three tracks:
Unpack a narrative about the body with a curated digital archive/gallery of representations (text/video/image/sound).
Articulate reflective and critical perspectives in written essay format.
Design a speculative, critical or reflective digital artifact to challenge existing values and assumptions.
Depending on your own prior experience, this class will begin, extend or support the following skills.
Intersectionality: Analyze how concepts of the body are interconnected with other systems of power. These could include, but are not limited to gender, age, ability, literacy, race, and membership in privileged knowledge institutions (universities, scientific labs, medical institutions). Demonstrate how these categories are mutually constituted and intersect with different technological engagements with the body.
Critical self-awareness: Demonstrate self-reflexivity about one’s values, ideas and goals, and how they are connected to one’s own body status and socio-economic position.
Engaged Practice: Explore how to advocate for differences in bodies, identities, marginalized communities, and non-normative practices. Understand the ways in which knowledge institutions are assigned legitimacy. Learn to recognize and support other non-traditional and diverse ways of producing knowledge about the body that are also valuable.
Creativity: Synthesize diverse perspectives, the aesthetics of writing/imagery/sound/touch, and activism to engage with issues of the body in a manner that is imaginative, inspiring and generative.
Students in this course will expand on their knowledge of techniques for exploratory data analysis (EDA) and collaborate on and contribute to a research project whose goal is to create a new framework for the EDA process.
This seminar will discuss topics of current interest in the multi-disciplinary field of ubiquitous sensing. The format will include paper discussions, invited lectures from both within and outside the class, and short written assignments. Students will also be responsible for presenting during at least one class session, either on their own research and ideas or on a selected set of papers relevant to the course topic.
This course is a graduate-level introduction to HCI research. Students will learn to conduct original HCI research by reading and discussing research papers while collaborating on a semester-long research project. The class will focus on both the positive potentials of technology as well as the negative consequences that new technologies may have on society. Each week the class will focus on a theme of HCI research and review foundational, cutting-edge, and critical theory research relevant to that theme.
Many of us are interested in looking forward towards future challenges and opportunities (near, medium, and occasionally long term) of the information economy and society. But technology prognostication has a terrible track-record. And keying on worst-case and best-case possibilities is an unrealistic, inefficient, and sometimes dangerous way to generate insight. Scenario thinking is an alternate methodology, developed first by Royal Dutch Shell for use in the energy sector after the oil shocks of the 1970s and later extended more broadly to business, government, and non-profit sectors. Scenario thinking starts from the proposition that the future is unpredictable in any meaningful sense… and that it is possible instead to systematically develop a landscape of possible futures from which useful insights can be drawn, and against which strategic action can be planned. In this seminar we will learn, practice, and develop scenario thinking for the information economy and society. We’ll explore the scientific limits of prediction; decision biases in that setting; and alternative methods for gaining and communicating insight that changes what people think and what they do. We’ll develop our own scenarios and use them to explore systematically challenges and opportunities ahead for the things we care about — business ideas, governance challenges, social change, etc. This seminar will call on a high level of energy, creativity, and open-mindedness as well as great teamwork.
Science and Technology Studies (STS) is an interdisciplinary field concerned with two areas of interest to the I School: the interaction between digital technologies and the social; and the generation of knowledge. This class will be a seminar emphasizing close reading and discussion, primarily of classic STS works, along with more current research. We’ll be particularly interested in the interaction between STS and human-computer interaction (HCI), information and communication technologies for development (ICTD), and/or new media, but exactly what we read will depend on what interests we have in common.
Course Objective: Develop new ideas and technology for making a quantum leap in improving how people learn.
This is an interdisciplinary graduate research seminar whose goal is to design technology and learning practices that will make major, significant improvements over how learning and teaching are done today. The course will have a technology-centered focus, but the most important metrics will be those related to learning gains.
As this is a graduate seminar, students will be responsible for selecting and designing the materials and the presentations in the course, with only light supervision by the instructor.
Students earning 1 unit will do the following:
- Summarize current research papers and book chapters
- Complete paper and artifact evaluations before each class
- Complete in-class assignments, including peer-assessments
- Present information clearly and concisely
- Lead class sessions
Students earning 3 units will do the following:
- The work listed above for 1 unit, and:
- Innovate in one particular area of research
- Design, implement, and release a research artifact; one of
- Working with a team to engineer something great
- Writing a research paper proposing a future approach based on a detailed analysis of existing approaches
Ph.D. students who have an interest in pushing the state of the art in education and educational technology are the intended participants of this course. It is preferred if students already have some background in learning sciences, but not required. It is also preferred that students have programming background, but also not required, if instead they come from learning sciences or some other relevant non-CS field such as psychology. The same applies to master’s students.
Undergraduates will be accepted to the course if they can demonstrate a proven interest in the topic, relevant background, and can present a recommendation from a UC Berkeley professor or equivalent. (Having taken a course with the instructor is equivalent.) Interested undergraduates should email the instructor with the name of the professor to contact for their reference, and should also include a copy of the UC Berkeley transcript and their resume.
This course takes a multi-disciplinary approach to explore the possibilities and limitations of ubiquitous sensing technologies for physiological and contextual data. We will survey the intellectual foundations and research advances in ubiquitous computing, biosensory computing, and affective computing, with applications ranging from brain-computer interfaces to health and wellness, social computing to cybersecurity. We will cover temporal and spectral analysis techniques for sensor data. We will examine data stewardship issues such as data ownership, privacy, and research ethics. Students signing up for the 3-unit option will continue in the second half of the semester with a student-led research project.
Network studies have been described as “a terminological jungle in which any newcomer may plant a tree.” Since J.A. Barnes wrote that in 1972, newcomers have proliferated, the jungle flourished, and the ecosystem diversified dramatically. This growth is particularly evident in the region of “social networks” — though it can sometimes be hard to envisage anything social that could not be called a network. The aim of this course, then, is to try to understand what has been described as the “modern obsession” with networks, to try to decide what might be valuable and what ephemeral, and to see if we can justify such decisions. For this, we will attempt to set some recent accounts in both disciplinary and historical context. Consequently, we will look at contributions from different fields and different periods. In particular, this seminar will seek to encourage dialogue among its participants by examining the implicit dialogue among the texts we shall be reading and the fields they represent, while keeping an eye on cases where, despite the shared terminology, the works seem to have nothing to say to each other.
How do you create a concise and compelling User Experience portfolio? Applying the principles of effective storytelling to make a complex project quickly comprehensible is key. Your portfolio case studies should articulate the initial problem, synopsize the design process, explain the key decisions that moved the project forward, and highlight why the solution was appropriate. This course will include talks by several UX hiring managers who will discuss what they look for in portfolios and common mistakes to avoid.
Students should come to the course with a completed project to use as the basis for their case study; they will finish with a completed case study and repeatable process. Although this class focuses on UX, students from related fields who are expected to share examples and outcomes of past projects during the interview process (data science, product management, etc.) are welcome to join.
Digital technologies have brought consumers many benefits, including new products and services, yet at the same time, these technologies offer affordances that alter the balance of power among companies and consumers. Technology makes it easier to deny consumers access to the courts; to restrict well-established customs and rights, such as fair use and the reselling of goods; to manipulate digital fora that provide reviews of products and services; to retaliate against and/or monitor or even extort consumers who criticize them; to engage in differential pricing; to “brick” or turn off devices remotely, to cause systemic insecurity by failing to patch products; and to impose transaction costs in order to shape consumer behavior.
Fundamentally, the move to digital turns many products into services. While the law has long comprehensively regulated products under the Uniform Commercial Code and products liability regimes, artifacts and services with embedded software present new challenges. European governments are moving aggressively to establish comprehensive regulations for digital goods. But no such agenda is on the horizon in the United States.
This course will employ a problem-based learning method (PBL). Students in the course will work in small groups to generate hypotheses, learning issues, and learning objectives in digital consumer protection. Through this process we will develop a high level conception of consumer protection and its goals. We will then explore its fit in the digital realm.
Students will develop short presentations on these learning objectives to create group learning and discussion. For the culmination of the course, students will work together to generate a research agenda for the future of digital consumer protection.
This is a hands on course that will address two major challenges associated with the current shift from text-based to e-books: making them more engaging and informative through use of the capabilities of the medium, and identifying and analyzing the issues surrounding the collaborative authoring and usage of e-books in an educational context.
Course may be repeated for credit, as new issues will be explored.
(In Fall 2012, this course was offered for 1 unit.)
Much as Adam Smith saw his own age as marked by its engagement with “commerce” and thereby distinguished from all ages that had come before, it has become conventional to see our own era as a break from all that has preceded it, and thus distinguished principally by its engagement with information and computing technologies. Scholars have labeled the contemporary era as the “post-industrial,” “postmodern,” or “network society,” but probably the most widely used and enduring characterization distinguishes the present day as the “information age” or “information society.” This course will explore the notion of an “information society,” trying to understand what scholars have held to be the essential and distinguishing features of such a society, how these views compare with classic theories of society or with alternative accounts of the present age, and to what extent different conceptions of the “information age” are compatible. In pursuing this investigation, we shall bear in mind the admonition of the legal scholar James Boyle that while the idea of an “information age” may be “useful ... we need a critical social theory to understand it.” In the process of developing a critical, social, and political-economic analysis of this idea, we hope to assemble a corpus of information society readings.