Digital and Computational Studies
Department website: http://departments-programs/dcs/
Overview
The nature of Digital and Computational Studies (DCS) is bidirectional. The first direction relies on the traditional questions asked by the entirety of the Liberal Arts, including, and especially, questions that surround humanity. Inevitably when one is talking about, and studying, technology it is critical to return to the human dimension – how digital artifacts are changing us and changing the world. It is not in the nature of DCS to study any technology in a vacuum but to look at digital artifacts from as broad a perspective as possible. The second direction involves using computational techniques to help us ask and answer questions about digital artifacts that would not be possible without such techniques. These techniques include Artificial Intelligence (AI), text analysis, network analysis, spatial information systems and programming in general.
DCS Analysis includes:
- Artifacts: objects of study, which are shared with many fields in the liberal arts. The questions explored include asking how digital objects are interpreted in physical, social, historical, and cultural contexts.
- Architectures: the infrastructures that give rise to the objects, their use, or their study, which are also shared with other fields. The questions explored include consideration of the consequences of these associated infrastructures, data, technology, and labor for understanding the object.
- Abstractions: the models built and theories tested through those models. The questions explored include asking what different models reveal about objects and what common ground exists between different fields that use those models.
- Agency: interpretation and decision-making. The questions explored include examination of how computation or the existence of a digital object shape who can make decisions, how results are interpreted, or how empowerment to act or express knowledge are influenced under the above conditions.
- Accountability: consequences and responsibility. An evaluative and critical exploration of ethical considerations of artifacts and the unintended outcomes of their deployment.
Objects are not merely analyzed—they are also created. A significant part of the student experience in DCS is collaborative and creative across fields of expertise. This creation can connect with virtually any discipline on campus.
Learning Goals
- Critically evaluate existent and emergent digital technologies through the DCS analytical framework.
- Design, create and deploy alternative digital technology emphasizing its positive impact on the common good.
- Productively integrate DCS methods and tools into other epistemological fields and practices in the liberal arts and daily life.
- Practice critical data assessment and agile project design.
- Communicate effectively when sharing DCS research and topics.
Options for Majoring or Minoring in the Program
Students may elect to coordinate a major in digital and computational studies with any other department/program major. Students pursuing a coordinate major may not normally elect a second major. Non-majors may elect to minor in digital and computational studies.
Mohammad T. Irfan, Program Director
Monica Gallego, Program Coordinator
Professor: Eric L. Chown
Associate Professors: Crystal Hall, Mohammad T. Irfan (Computer Science)
Assistant Professors: Fernando Nascimento, Vianney Gomezgil Yaspik
Adjunct Lecturer: Aaron Gilbreath (spring semester)
Digital and Computational Studies Coordinate Major
Students coordinate their study of digital and computational studies (DCS) with any department/program at Bowdoin that offers a major. To satisfy the requirements for the coordinate major in DCS, students must complete the eight credits detailed below as well as the major requirements within their coordinated department/program.
| Code | Title | Credits |
|---|---|---|
| Required Courses: | ||
| DCS 1100 | Introduction to Digital and Computational Studies | 1 |
| DCS 2450 | Technology and the Common Good | 1 |
| DCS 3900 | DCS Capstone Implementation and Design | 1 |
| Select one 3000-level DCS course a | 1 | |
| Select one of the following: | 1 | |
| GIS and Remote Sensing: Understanding Place | ||
| Social and Economic Networks | ||
| Artificial Intelligence in the World | ||
| Digital Text Analysis | ||
| Select three more DCS courses of your choice. b | 3 | |
- a
Independent studies (numbered 2970-2999 and 4000-4049) and honors projects (numbered 4050 or higher) will not fulfill this advanced seminar requirement.
- b
These three DCS courses should intentionally connect to the coursework in the student's coordinated major discipline to foster exploration of their complementary nature and must be selected in consultation with a faculty advisor in the Digital and Computational Studies Program. With prior approval from the program director, courses offered outside of DCS may be used to fulfill this requirement.
Digital and Computational Studies Minor
| Code | Title | Credits |
|---|---|---|
| DCS 1100 | Introduction to Digital and Computational Studies | 1 |
| Four other courses in DCS, at least three of which should be at the 2000 level or above | 4 | |
- Courses count toward the major or minor if grades of C- or better are earned.
- One course taken with the Credit/D/Fail grading option may count toward the major or minor as long as a CR (credit) grade is earned.
- One first-year writing seminar may count toward the major or minor.
- A maximum of two independent studies can count toward the major at either the intermediate or advanced level. Independent studies do not count toward the minor.
- The director of digital and computational studies works with students to discuss double-counting cross-listed courses with other departments or programs.
- With prior approval, two courses from a one-semester study-away program may be counted toward the major; three courses may be counted toward the major from a yearlong program. One course from a one-semester study-away program may be counted toward the minor.
Information for Incoming Students
Digital and Computational Studies addresses topics that span disciplines across campus, uniting them through computational thinking, data analysis, critique of digital objects, and creative problem solving. In particular, computation is not presented merely as a technique to be exploited, but as an object of study with corresponding strengths and weaknesses. Students in DCS classes have the opportunity to work on digital projects, many of them in collaboration with other students.
The following course is open to first-year students and count towards the requirements for the DCS coordinate major or minor: DCS 1100 Introduction to Digital and Computational Studies. The following courses, when offered, are also open to first year students and typically count toward electives for the DCS coordinate major or minor: DCS 1020 How to Read a Million Books, DCS 1500 Understanding and Deploying Computational Methods, ECON 1099 Using “Big Data” to Investigate and Suggest Solutions to Economic and Social Problems and PHIL 1336 Ethics for a Digital World. All of these courses assume no background in any of the subjects covered, ranging from humanities, social sciences, computer science, and mathematics. Several DCS courses are cross-listed with other disciplines. They may be open to first-year students, and may count as electives.
Confronts the challenges of having too many things to read and limited attention spans to persuade someone that a written interpretation is valid. Explores different methods of reading (i.e. close, surface, text mining, thematic) at different scales, from 1 book to millions of data points from Bowdoin's library collections. Activities evaluate both the process and rationale for different reading and writing methods. Assumes no knowledge of programming.
Terms offered: 2022 Fall Semester
This first-year writing seminar explores how digital games represent the past. We begin by focusing on the emergence of digital culture in recent decades, seeking to understand the role electronic simulations play in our lives. We move on to exploring the representation of history in commercial video games, from Sid Meier’s Civilization series, to Assassin’s Creed IV: Black Flag. Why are video games such a popular way of depicting past events? What constraints does the digital game format impose on these representations? How are these constraints conditioned by the nature of these games as commercial products sold in a global marketplace? Finally, how should we approach some games’ representation of difficult histories—those that may involve war, colonialism, and racism? Along the way, we will learn how to access campus information sources, use intellectual property responsibly, and write essays for the college level. This course includes a weekly required evening lab for dedicated gaming time and film screenings. This course originates in History and is crosslisted with: Digital and Computational St. (Same as: HIST 1025)
Terms offered: 2022 Fall Semester
Examines the impact of digital artifacts, networked interaction, and computational analysis on the ways in which we establish new knowledge, engage in creative and social practices, and understand the self. Studies how the combination of large-scale digital data and computational modeling methods shape our agency as decision-makers. Emphasis on how the Liberal Arts shape and are shaped by these processes. Coursework includes quantitative analysis, machine learning, text and network analysis, critical readings in the field, and short, exploratory projects. Assumes no knowledge of programming or any software that will be used.
Terms offered: 2021 Fall Semester; 2022 Spring Semester; 2022 Fall Semester; 2023 Spring Semester; 2023 Fall Semester; 2024 Spring Semester; 2024 Fall Semester; 2025 Spring Semester; 2025 Fall Semester
What sorts of questions can and should be answered using digital and computational methods? How can such methods in conjunction with data can reveal new insights and questions about the world? How do we construct models to help us better understand social phenomena? Covers topics such as data gathering, validation, analysis, and presentation, as well as statistics and programming. Provides substantive experience in digital and computational methods, and a critical lens for understanding and evaluating what computers can (and cannot) bring to the study of our world.
Terms offered: 2025 Fall Semester
Students will use 'big data' to understand and address some of the most important social and economic problems of our time. The course will give students an introduction to cutting edge research and policy applications in economics in a non-technical manner that does not require prior coursework in economics or statistics, making it suitable both for students exploring economics for the first time, and for more advanced students who are interested in the class’s topics. Social and economic problems that we will cover include equality of opportunity, education, racial disparities, criminal justice, labor market participation, entrepreneurship, health care and public health, the opioid crisis, climate change, and environmental justice. In the context of these topics, the course will also provide an introduction to basic methods in data science, including regression, causal inference, and machine learning. Students will use software packages R, Stata, Arc GIS, and Excel. This course originates in Economics and is crosslisted with: Digital and Computational St. (Same as: ECON 1099)
Terms offered: 2022 Fall Semester; 2024 Fall Semester
Computational tools, including programming, are increasingly important across the liberal arts. Such tools, however, cannot be effectively created or used without a fundamental understanding of computation. This course provides a foundation for the use of these tools in conjunction with the critical framework of DCS. A major goal of the course is to teach introductory programming, but with a focus on how programming can be used to complement and even to implement methodologies including text analysis, network analysis, GIS and visualization. Students will use these methods in the service of critically engaging with data. E.g., where computer science focuses mainly on problem solving, this course is fundamentally about exploration and often problem discovery. No prior programming knowledge is required. This course is not open to students who have taken CSCI 1101, CSCI 1103, or CSCI 2101.
Terms offered: 2022 Fall Semester; 2023 Spring Semester; 2024 Spring Semester; 2025 Spring Semester
Digital technologies make our lives easier in many ways—e.g., we can communicate with others around the world, we can order devices to play music, we can get instant directions to go basically anywhere! But is there any ethical cost to enjoying the benefits that come from these types of technologies? This course investigates a variety of ethical issues arising from and connected with digital technology. Topics covered might include privacy and big data, algorithmic bias, surveillance capitalism, social media and mental manipulation, fake news, internet shaming, and the moral status of superintelligence. This course originates in Philosophy and is crosslisted with: Digital and Computational St. (Same as: PHIL 1336)
Terms offered: 2022 Fall Semester; 2025 Spring Semester
Asks what a digital representation of a city could and should be, particularly in a moment when travel is limited, using Florence, Italy as a case study. Examines digital image, text, and spatial data about the city, juxtaposing it against non-digital primary sources, secondary critical readings, reflections on experiences of urban and other spaces, and data that we will create in class. Emphasizes shifting definitions across time, language, and digital artifacts of what and who is Florentine in these representations. Coursework happens in three phases: going “under the hood” of the popular digital artifacts that provide an experience of Florence in order to evaluate strengths and weaknesses of representation; expanding our definition of Digital Florence to find local perspectives on what the essential features of the city could be; and proposing a digital intervention that better reflects the values we have identified throughout the semester. Assumes no programming knowledge. Taught in English. This course originates in Digital and Computational Studies and is crosslisted with: Italian Studies; Urban Studies. (Same as: ITAL 2100, URBS 2100)
Terms offered: 2022 Spring Semester; 2024 Fall Semester
For several decades, journalists, media artists, activists, and scholars have sought to articulate the ways the Internet and digital culture have transformed how we live, how we think, how we communicate, and what we value. By examining materials as diverse as scholarly and popular articles, contemporary events, fiction, film, blogs, and other digital media, considers how the digital age complicates, diversifies, deconstructs, and recreates cultural and social understandings of media, gender, and sexuality. Approaches these issues from a multidisciplinary perspective, looking at insights on digital culture from such disciplines as media and communication studies, gender and sexuality studies, information studies, science and technology studies, and sociology. Topics include globalized consumption and digital labor, sexuality and intimate communications in digital culture, and the political affordances of digital spaces. Critically evaluates how digital interactions and media challenge ideas about sex, gender, sexuality, and other intersectional forms of identity. This course originates in Gender, Sexuality, and Women's Studies and is crosslisted with: Digital and Computational St. (Same as: GSWS 2223)
Explores how digital media construct societies and cultures, and in turn how social institutions, interactions, and identities get reflected in/through digital media. Draws from multiple socio-cultural contexts to take a global and transnational approach to understand sociological themes such as self, social interaction, and community; social control and surveillance; constructions of gender, sexuality, race, social class, and religion; generations; transnational migration; emotional/affective labor; and social movements and change. Challenges binary dystopian and utopian representations of digital media to cultivate a more nuanced understanding. This course originates in Sociology and is crosslisted with: Digital and Computational St. (Same as: SOC 2272)
Terms offered: 2022 Fall Semester
Examines emerging digital techniques in environmental management and analysis within government, academic, and media sectors. Provides an overview of social science methods including analysis of qualitative data, text analysis, spatial analysis, survey design and analysis, and social network analysis. Topics include collaborative resource management, leveraging the power of social networks, spatial analysis, social-ecological system management, the role of volunteered information and citizen science, and expanding capacities for adaptation and resilience. Labs as part of class time provide students exposure to standard software programs used in social science research, including NVivo, ArcGIS, and Gephi and introduce the basics of R as a programming language for text analysis, and spatial analysis. (Same as: ENVS 2331)
Terms offered: 2023 Fall Semester
Geographical information systems (GIS) organize and store spatial information for geographical presentation and analysis. They allow rapid development of high-quality maps and enable powerful and sophisticated investigation of spatial patterns and interrelationships. Introduces concepts of cartography, database management, remote sensing, and spatial analysis. Examines GIS and remote sensing applications for natural resource management, environmental health, and monitoring and preparing for the impacts of climate change from the Arctic to local-level systems. Emphasizes both natural and social science applications through a variety of applied exercises and problems culminating in a semester project that addresses a specific environmental application. Students have the option of completing a community-based project. This course originates in Environmental Studies and is crosslisted with: Digital and Computational St. (Same as: ENVS 2004, URBS 2004)
Terms offered: 2021 Fall Semester; 2022 Fall Semester; 2023 Fall Semester; 2024 Fall Semester
Explores approaches by communities and regions to build resilience in the face of changing environmental and social conditions. Examines the ways communities establish policies and collaborate with state, federal, private and nonprofit sectors towards strengthening local economies, safeguarding environmental values, protecting public health, addressing issues of economic and social justice, and implementing mitigation and adaptation strategies. Provides students with firsthand understanding of how digital and computational technologies including Geographic Information Systems (GIS) are playing an increasingly important role in understanding and informing effective approaches for expanding resilience at a community level to inform policy decision. Students gain proficiency with GIS as part of the course. This course originates in Environmental Studies and is crosslisted with: Digital and Computational St. (Same as: ENVS 2301, URBS 2301)
Terms offered: 2023 Spring Semester; 2024 Spring Semester; 2025 Spring Semester; 2025 Fall Semester
Examines the social and economic aspects of today's connected world from a multitude of perspectives; namely, network science, computer science, sociology, and economics. The fundamental questions to be addressed are: What are the properties of real-world networks? What are the effects of networks on our behavioral choices like quitting smoking or eating healthy? How do cascades in networks lead to outcomes like videos going viral? How does Google search the Internet and make money doing so? Debates issues around centrality in networks. Uses game theory to study strategic interactions in networks and markets. This course originates in Digital and Computational Studies and is crosslisted with: Computer Science. (Same as: CSCI 2350)
Terms offered: 2022 Spring Semester; 2023 Fall Semester; 2024 Fall Semester; 2025 Fall Semester
As the pace of technological change continues to accelerate, it raises questions about the impacts, positive and negative, on society. Will technology make our lives more comfortable and pleasant or will it destroy human society and lead us to a catastrophic ending? The answers largely depend on our ability to consider new technology advancements in light of desires to live good lives within just institutions. Students engage with topics of current relevance such as artificial intelligence, gene editing, virtual reality, robotics, and the internet of things. Discusses the underlying technological aspects of each and the possible implications for society. Students apply philosophical and ethical concepts and frameworks to consider how technology can become a positive force for the common good and debate possible ways to evaluate and avoid undesirable effects of current and future technologies. No prior programming experience required.
Terms offered: 2022 Spring Semester; 2023 Spring Semester; 2024 Spring Semester
Mobile Devices are increasingly present in our lives. More and more 'smart,' they transform how we communicate, access information, experience our physical spaces, create and maintain friendships, monitor our health, and have fun. In this course, we will critically consider the consequences of these technological artifacts for how we define our personal identities, our interpersonal relationships, and the organization of our societies. In order to deepen our discussions, within the experiential context of DCS, we will learn how the software of mobile devices is structured, how they communicate with each other, with local sensors and other wearable devices. We will also study the physical and social architectures that connect our mobile experiences, including how they are likely to change in the coming years and their possible implications. This course does not require any prior knowledge in computer science or mobile communications.
Terms offered: 2022 Fall Semester; 2025 Fall Semester
Artificial Intelligence (AI) is changing the world. It is being widely deployed by governments, police forces, and businesses. AI algorithms are touted as being without bias, and claims are made that AI regularly outperforms humans on a wide variety of tasks. The truth is far more complex. In this class, we will examine the systems being deployed in the world, the algorithms behind them, and their impact on the world. In particular, we will focus on the relationship between the data used by AI systems and their performance. Special attention will be paid to machine learning systems and students will engage in project-based machine learning activities.
Terms offered: 2024 Fall Semester
Artificial intelligence (AI) is increasingly transforming nearly every aspect of society and our personal lives. This course invites students to explore fictional and non-fictional worlds transformed by AI and consider them in light of ethics, politics, and their impact on individuals. Students will use an array of literary and cinematic narratives to enrich their understanding of AI as it relates to those who develop it, those who use it, and those who seek to create policies governing its applications in society. AI-based artifacts will be examined from both conceptual and functional perspectives. The course will culminate with a look at how human agency can shape AI in order to move it closer to serving the common good.
Terms offered: 2023 Fall Semester; 2025 Fall Semester
Explores how digital techniques can enhance our understanding of text. Investigates how to make sense of the burgeoning number of textual sources in a timely manner and what new questions can be raised and answered by computer-based text analysis. Students learn to apply tools for analyzing large texts to problems drawn from areas throughout the liberal arts, such as psychology, philosophy, and literature. In addition, students address questions ranging from authorship of Supreme Court opinions, to using thirty years of newspapers to reexamine historical questions, to interpreting Raphael's masterpiece “School of Athens” through an analysis of Aristotle's and Plato's works. While doing so they also study the strengths and weaknesses of these approaches. No previous computer programming experience is required.
Terms offered: 2021 Fall Semester; 2023 Spring Semester; 2024 Spring Semester; 2025 Spring Semester
In this intermediate seminar we will use Geographic Information Systems to explore historical problems in 19th-century US history. We will introduce and practice basic statistical techniques, and use the class GIS database to investigate problems, construct our own historical datasets, and make our own maps. Class projects will challenge students to develop critical thinking skills in historical and computational methods, and practice effective data presentation. We will work with a wide array of history data, including information on race, ethnicity, gender, religion, agriculture, slavery, and voting behavior in the period in question. Throughout, we will probe the possibilities and limitations of GIS as a digital technology and methodological approach to historical analysis. This course is part of the following field(s) of study: United States. This course originates in History and is crosslisted with: Digital and Computational St. (Same as: HIST 2625)
Terms offered: 2021 Fall Semester; 2023 Fall Semester; 2025 Fall Semester
This anthropology course investigates overlaps in social understanding of media and technology. Investigates contemporary shifts in media landscapes where new media have come to dominate popular ideas about what qualifies as technology. Examines implications of mediation as an ever-present feature of daily life. Critically interrogates how technology and media have been differently classified depending on intended users. Additionally, the course explores how low-tech technologies, artful craft, and inclusive design could lead to more accessible, beneficial technology. Incorporates discovery of maker spaces, multimedia, and readings in anthropology, science studies, media studies, gender studies, and race and ethnicity studies. This course originates in Anthropology and is crosslisted with: Digital and Computational St. (Same as: ANTH 2251)
Terms offered: 2024 Spring Semester
Explores how artificial intelligence (AI) and machine learning innovations are transforming the field of economics. Begins with developing a conceptual understanding of key AI concepts and new methodological advancements in machine learning. Investigates how AI may affect employment and labor productivity across different sectors of the economy including health, education, and finance. Students learn about sector-specific tools and applications that leverage AI and examine the government’s role in regulating AI and designing policies to mitigate potential adverse effects. This course originates in Economics and is crosslisted with: Digital and Computational St. (Same as: ECON 2225)
Terms offered: 2024 Fall Semester; 2025 Spring Semester
The promise of the internet was that it was a world without 'prejudice or privilege.' Instead it has exacerbated the elements of privilege already prominent in society. This course examines issues of privilege in digital environments both through the lens of algorithms and through interactions with others, with a particular emphasis on social media. The course begins with an examination of supportive environments, the consequences when the supportive components fail, and the roots of those failures. We will then use that perspective to look at digital environments, examining different forms of privilege, including race, gender, age, and class among others to show how the digital environment often makes issues around privilege worse rather than better. Meanwhile, many groups are simply unable to take advantage of the digital world at all. Work for the course will consist of a series of short papers and a culminating project that takes on one form of privilege in more detail.
Terms offered: 2021 Fall Semester; 2025 Spring Semester
Introduces students to the fundamental statistical concepts and computational tools for analyzing data and making data-driven decisions. Topics include data acquisition, wrangling, exploratory analysis, visualization, statistical modeling, and communicating results. Emphasis is placed on helping students become critical consumers of statistical studies. Through hands-on projects, students will learn how to formulate questions, collect and process relevant data, build models, evaluate assumptions and limitations, and interpret findings. Ethics surrounding data privacy, bias, and transparency are also examined. Students with minimal programming experience and from any discipline are encouraged to take the class. Students that have taken econometrics or a significant number of statistics courses should speak with the instructor before registration.
Terms offered: 2024 Fall Semester; 2025 Fall Semester
This course asks how different computational text analysis can be in two cultural environments: the digital humanities as practiced in the US and informatica umanistica in Italy. Our case study for texts to study will be Italian epic poetry of the Renaissance, the equivalent of today’s Marvel comic universe in terms of range of characters, complexity of plotlines, action sequences, humor, popularity, and fan-fiction spinoffs. We will draw on the multiple language backgrounds of all students in the course and the combined skills of advanced students in DCS and Italian. We will practice collaborative, iterative research development around the geographies, networks, and textual features of our texts. Activities will include discussion, hands-on use of digital tools, assigned readings, and a culminating project. This course originates in Digital and Computational Studies and is crosslisted with: Italian Studies. (Same as: ITAL 3012)
Terms offered: 2023 Spring Semester
An in-depth investigation of an aspect of the relationship of digital technologies with human expression, history, education, ethics, the environment, or social practices. Draws on topics that may include computational analysis of digital artifacts, networks, spaces, or texts. In turn, these topics are used as a lens to examine real-world issues. Students apply the models offered by readings and the methodologies of digital and computational studies to a semester-long project that investigates an aspect of computation in the context of the instructor's area of specialization.
Sicily has long been a contested, multicultural space. At once starkly rural and vibrantly urban, environmentally barren and resource rich, economically wealthy and impoverished, the island is both a part of Italy, part of the Mediterranean, part of Europe, and apart from all of them. This course investigates digital textual representations of Sicily and Sicilian culture by residents to document and challenge prevailing images of the island created primarily by foreign tourists, mainland Italians, and regional conquerors. Combined with a planned trip to Sicily, students will compare perspectives on the ground with the results of distant and computational reading of literature, history, social media, and generative AI texts about the relationships among the built, natural, and cultural environments of Sicily. Does not require knowledge of Italian, but does require previous experience coding in Python or R. This course originates in Digital and Computational Studies and is crosslisted: Italian Studies; Urban Studies. (Same as: ITAL 3114, URBS 3114)
Provides students with advanced experience in geographic information systems (GIS) and remote sensing in environmental studies, with a focus on environmental study applications. Students will develop and pursue a semester project in spatial analysis in an area of their choosing, with an option to pursue a community-based project. Topics include research design, field collection, data creation and processing, analysis, and visualization. The course examines the ways that GIS and remote sensing are increasingly used at different scales from the local (e.g., parcel level) to global (e.g., international level) and examines the equity dimensions of spatial analysis. This course is intended for students with prior experience working with geographic information systems and/or conducting spatial analysis. This course originates in Environmental Studies and is crosslisted with: Digital and Computational St. (Same as: ENVS 3914)
Terms offered: 2024 Spring Semester; 2025 Spring Semester
Course uses geographic information systems (GIS) and R statistical software to analyze issues of inequality in the United States. Investigates the roles of maps and mapping technology in creating and reinforcing racial and economic inequality. Readings will contextualize these methods in the fields of economics, environmental studies, and sociology. Topics include environmental justice, segregation and housing policy, educational inequalities, crime and policing. Students will learn data management and statistical techniques using R, and mapping and spatial analysis using GIS. Students will produce independent projects at the end of the semester.
Terms offered: 2023 Spring Semester; 2024 Spring Semester
Project-based advanced networks course. Investigates how the historic perspective of contagion has inspired its expansive contemporary view, ranging from interventions in epidemics to diffusion in social networks to network effects on behavioral aspects like smoking, obesity, and happiness. Studies various network models and their properties. Programming projects involve implementation of network models and applying these models to large-scale, real-world networks with millions of agents, with a particular focus on critically assessing the models and algorithms using computational thinking. Projects also involve creating computer simulations to study models of residential segregation by race. Takes a critical view of the implications of various predictive algorithms, including techniques for disease prediction.
Advances in computer science, psychology, and neuroscience have shown that humans process information in ways that are very different from those used by computers. Explores the architecture and mechanisms that the human brain uses to process information. In many cases, these mechanisms are contrasted with their counterparts in traditional computer design. A central focus is to discern when the human cognitive architecture works well, when it performs poorly, and why. Conceptually oriented, drawing ideas from computer science, psychology, and neuroscience. No programming experience necessary. This course originates in Computer Science and is crosslisted with: Digital and Computational St. (Same as: CSCI 3400)
Terms offered: 2022 Fall Semester; 2024 Spring Semester
Explores the intersection of AI and the Internet of Things (IoT) - the growing network of connected devices surrounding us, from smartwatches to environmental sensors monitoring farms or agricultural fields. We'll investigate how these technologies can help address pressing global challenges like climate change, public health, and urban development. Through hands-on experiments, applied projects, theoretical readings, and engaging discussions, students will learn how IoT systems work and how they can be designed to serve human needs and values. We'll examine critical questions about privacy, ethics, and social impact: Who benefits from IoT technologies? What role should autonomous systems play in our society? How can we ensure that digital innovations promote rather than hinder human development?
Seminar. We live in an image-saturated world: social media platforms, the news, smart phones, remote learning, video games, streaming services, emoticons. We communicate, learn, and express ourselves in a highly mediated world of visual tools and images. Yet all too often we treat images as transparent vehicles of communication, immediately comprehended and obvious to all. This class brings the art historical tools of close looking and visual analysis to the materials of the digital world, from its roots in the nineteenth-century technologies of reproduction to its current screen-based forms, with an emphasis on media and materiality. Topics will vary, but may include early mass media, including wood engraving and photography; family albums and scrapbooks; the news media; the visual architecture of the internet; social media platforms; video games, advertising; digital art; and NFTs. This course originates in Art History and is crosslisted with: Digital and Computational St. (Same as: ARTH 3835)
This course investigates philosophical issues arising from advanced forms of technology—in particular artificial intelligence and biological enhancement. We will discuss topics like the ethical implementation of AI, machine consciousness, moral obligations toward advanced machines, the nature of reality in virtual environments, living with entities that have super-human abilities, and the moral significance of the possibility of human extinction. We will read both theoretical papers in ethics, philosophy of mind, and metaphysics and papers that specifically discuss these issues in relation to the topics above. This course originates in Philosophy and is crosslisted with: Digital and Computational St. (Same as: PHIL 3420)
Terms offered: 2024 Spring Semester
Seminar. Analyzes the role of artificial intelligence and digital technologies in the modern economy, from the perspective of economic theory and empirical research. Topics include cryptocurrencies, blockchain technology, robotics, machine learning and artificial intelligence, 'big data,' social and economic networks, open-source software, intellectual property, and piracy of digital media. Assesses the extent to which such emerging technologies and processes disrupt markets, hierarchies and the state, including the organization of firms and industries, money and finance, technological innovation, productivity and growth, the law, and government policy. DCS/CS juniors or seniors may enroll with instructor permission. This course originates in Economics and is crosslisted with: Digital and Computational St. (Same as: ECON 3550)
Terms offered: 2024 Spring Semester; 2025 Spring Semester
Explores advanced statistical and machine-learning techniques using Python and STATA. Students will learn to handle complex datasets, implement sophisticated models, and address real-world problems across various disciplines. Topics include advanced data preprocessing, ensemble methods, neural networks, time series analysis, and ethical considerations in AI. Through hands-on projects, students will develop skills in designing and evaluating advanced data science solutions, with an emphasis on practical applications and ethical challenges in data analysis.
Terms offered: 2025 Spring Semester
Provides a culminating experience allowing students to connect DCS to their other chosen discipline. Guided development and implementation of data creation, methodology evaluation, contextualization of topic and results in scholarly conversations, and translation of results and implications across digital media. Students can combine the course units into a single, unifying research project or propose alternative assignments that demonstrate DCS analytical skills and connections across core DCS topics. Assigned readings will address themes in interdisciplinary research, weekly activities will focus on developing best practices, and all work will have opportunities for peer review throughout the semester.
Terms offered: 2022 Fall Semester; 2023 Fall Semester; 2024 Fall Semester; 2025 Fall Semester