Ethics

History

Narrative

Sociotechnical systems

Systems theory

Economics

Data and classification

Theory

Knowledge production

Control and power

Politics

Emerging technologies

Automation

Gender and sexuality

Surveillance and privacy

Reimagining

Society of tech

Reflection and practice

Equity

Action

CSE  480 Computer Ethics University of Washington Autumn 2022 This course focuses on understanding the societal and ethical implications of technology and computing. It covers historical tech issues, machine ethics, and science and technology studies. The course aims to train students to critically evaluate the socio-technical implications of their creations, with a focus on AI ethics, social good, governance, and privacy, among other topics. Be it social-media platforms, robots, or big data systems, the code Allen School students write—the decisions they make—influences the world in which it operates. This is a survey course about those influences and ways to think about them. We recognize, “the devil is in the implementation details.”

The course is divided into two parts: In the first part, we survey historical and local issues in tech, particularly those concerning data. We then engage with critical perspectives from disciplines such as machine ethics and science and technology studies as a framework for students to articulate their own beliefs concerning these systems. In the second part, we apply these perspectives to urgent issues in applied technologies; see the schedule for the topics we plan to consider this quarter.

Throughout, students hone their critical reading and discussion skills, preparing them for a life-long practice of grappling with the—often unanticipated—consequences of innovation.

We approach topics such as: AI ethics, social good, utopianism, governance, inclusion, facial recognition, classification, privacy, automation, platforms, speculative design, identity, fairness, power and control, activism, and subversive technologies.

We aim to have you feel this course experience is an essential part of your Allen School education despite being (or because it is!) very different from most CSE courses. By the end of this course students will:

- Obtain awareness of issues arising from the use of computers in contemporary sociotechnical systems
- Articulate technological harms to individuals and groups in the language of critical perspectives
- Appreciate how historical, cultural, economic, and political factors contribute to how technologies are built and designed
- View themselves as both subjects and creators of sociotechnical systems
- Understand and articulate complex arguments pertaining to values in technology
- Recognize the diversity of stakeholders and views when considering a technology
- Amplify voices and values not traditionally considered in technological development (e.g., in design processes)
- Re-imagine and speculate alternative histories and futures for using and coexisting with computers  

CSE  480 Computer Ethics

Computer Ethics

scikit-image

scikit-learn

pandas (software)

Jupyter Notebook

Code Complexity

Memory management

Python

List (abstract data type)

File Processing

pandas DataFrame

Data Science Libraries

Search

Joins

Images

Statistics

Indexes

Control Structures

Data structure

Data Visualization

Class (computer programming)

Algorithmic Efficiency

p-hacking

Tree (data structure)

NumPy

String (computer science)

Computer file

Machine learning

Object (computer science)

Geospatial Data

Convolution

Algorithmic fairness

Algorithmic Privacy

CSE 163 Intermediate Data Programming University of Washington Summer 2022 This course offers an intermediate level of data programming, focusing on different data types, data science tools, code complexity, and memory management. It emphasizes the efficient use of concepts for data programming. The world has become data-driven. Domain scientists and industry increasingly rely on data analysis to drive innovation and discovery; this reliance on data is not only restricted to science or business, but also is crucial to those in government, public policy, and those wanting to be informed citizens. As the size of data continues to grow, everyone will need to use powerful tools to work with that data.

This course teaches intermediate data programming. It is a follow on to CSE142 (Computer programming I) or CSE160 (Data Programming).

The course complements CSE143, which focuses more deeply on fundamental programming concepts and the internals of data structures. In contrast, CSE163 emphasizes the efficient use of those concepts for data programming.

In this course, students will learn:

1. More advanced programming concepts than in CSE142 or CSE160 including how to write bigger programs with multiple classes and modules.
1. How to work with different types of data: tabular, text, images, geo-spatial.
1. Ecosystem of data science tools including Jupyter Notebook and various data science libraries including scikit image, scikit learn, and Pandas data frames.
1. Basic concepts related to code complexity, efficiency of different types of data structures, and memory management.  This is class is designed as the second introductory programming course that focuses on writing programs that work with data. The prerequisites for the class require students having taken CSE 142 or CSE 160 and the class has been designed to be accessible to students from either of those backgrounds. Students that have taken 143 are welcome to take this class as it will serve as a complement to the material learned in 143 with only minor overlap.

Because this course will have students coming from many different class backgrounds, the first couple of weeks will be pretty different for students depending on what classes they have taken. Here is what we expect students to see in the first weeks based on their background:

- 142: The first two weeks might go pretty fast, but will be doable since you already know all the concepts (loops, conditionals, methods) and you are just learning all the new “words” in Python to use those concepts. This might require a little bit of extra practice early in the quarter so you are familiar with translating all the ideas you have learned in 142 to this new language. The first week has been designed to be a recap of all things 142 so you don’t also have to be learning a ton of new material while learning a new language in the first week.
 - 160: The first week will just be a bit of a review for you, but the class will start covering material you haven’t seen before starting in the second week.
- 143: You are in a similar boat as the 142 students, where you know a lot of the concepts but don’t know the Python language. You’ll probably see a few things that you saw in 143 in this class, but I think the new context of processing data in a new language will still keep it new, exciting, and challenging. 

CSE 163 Intermediate Data Programming

Computer Programming

Data Science

Optimization

Algorithmic decision-making

Algorithmic bias

Accountability

Privacy

Surveillance

Civil liberties

Artificial intelligence

Labor and automation

Platforms

Social media

Misinformation

Blockchain

Cryptocurrency

Decentralization

CS 182: Ethics, Public Policy, and Technological Change Stanford University Winter 2023 This course examines the intersections of philosophy, public policy, social science, and engineering in the context of recent computing technology and platforms. Key areas of focus include algorithmic decision-making, data privacy, AI, the influence of private computing platforms, and issues of diversity in tech. Students need to have completed CS106A. Examination of recent developments in computing technology and platforms through the lenses of philosophy, public policy, social science, and engineering.  Course is organized around five main units: algorithmic decision-making and bias; data privacy and civil liberties; artificial intelligence and autonomous systems; the power of private computing platforms; and issues of diversity, equity, and inclusion in the technology sector.  Each unit considers the promise, perils, rights, and responsibilities at play in technological developments.  ### Menu of Topics

The course will focus on six frontiers that (a) you are likely to play a role in shaping over the next decade and (b) where engagement with material from philosophy, social science, and public policy is likely to be helpful.

1. Algorithmic Decision-Making 
2. Political Economy of Tech Sector
3. Data Collection, Privacy, and Civil Liberties 
4. Artificial Intelligence and Autonomous Systems
5. Power of Private Platforms
6. Blockchain, Decentralization, and Cryptocurrency
 CS106A ### Cross-Cutting Themes

Throughout the course, we will foreground two cross-cutting themes:

- First, issues of diversity, equity, and inclusion which focus our attention on who has power, voice, and influence in shaping the design and regulation of technology.
- Second, issues of political economy which focus our attention on the interplay of markets and governments in shaping what technology gets built, who benefits from that technology, and how any harmful impacts are/are not mitigated.

CS 182: Ethics, Public Policy, and Technological Change

Ethics

3 courses cover this concept

CSE 480 Computer Ethics

CSE 163 Intermediate Data Programming

CS 182: Ethics, Public Policy, and Technological Change