LIN 105 – Topics in Language & Linguistics:
Language Technology and Society
Spring 2026, TTh 10:30-11:50am
Teaching & Learning Center 3211
Instructor: Rob Voigt
Office Hours T 1-2pm and Th noon-1pm, Kerr Hall 281
Course Description: Language technologies – large language models, chatbots, AI, whatever you want to call them – are becoming ever-more ubiquitous. In this course we will examine the bi-directional relationship between language technology and society. On one hand, these technologies are a product of society. They are mirrors that reflect the humans on whose language they are trained, for good and for ill. They can at times perform surprising feats of apparent creativity or insight, but can also display critical limitations and perpetuate troubling social biases. On the other hand, the reverse is also true – society is increasingly influenced by language technology. Human languages, behavior, and experience are changing as these technologies become more pervasive. Real potential has been demonstrated for impactful applications of language technologies that can address social issues and improve people’s lives; at the same time, real concerns have been raised about impacts on privacy, jobs, mental health, and the environment.
The content of this course will be focused on three key goals. First, we will aim to demystify language technologies by achieving a basic conceptual understanding of how they work. Second, we will read contemporary research on language technology and society to see what we know about this complex relationship and what remains to be found out. Third, we will work intensively in small groups to develop public-facing projects that engage with real-world issues in this domain. Linguistic, social scientific, and technical experience can all contribute to success in the course, but no specific background is required.
Schedule
Materials
All course materials will be available for free online and in Canvas.
Structure
Expect this course to be very hands-on! The first four weeks will be focused on reading/learning about language technologies and their relationship with society in small group and full class discussions. We will then break into project groups, and the final six weeks of the course will be focused on planning, executing, and polishing public-facing projects responsive to this relationship.
Group Discussions
During weeks 2-4, we will read primary sources about language technology and society before class and engage in structured group discussions during class. I will ask you to make comments and ask questions on Perusall (through Canvas) for each reading, which constitute the primary out-of-class assignment during this period of the quarter. During each class you will be assigned a discussion group role (more information forthcoming).
Group Projects
Weeks 5-10 will be dedicated to group projects, which can be genuinely *anything* responsive to the relationship between language technology and society. I encourage you to think outside the box and imagine what could be most exciting or impactful to you.
Some clear academic-style defaults could include a literature survey examining what is known about a particular subtopic, a research project proposal that designs and motivates an exciting direction for research, or a research paper itself that aims to answer a specific research question. But you can go way beyond this. I will gladly accept songs, performance art, vibe-coded websites, mobile apps or games, spoken word poetry, an informative series of Tik Toks, genuinely anything you want to do. The only hiccup is in the event you do something less traditionally academic like this, I will ask your team to supplement the project with a short paper justifying and motivating the work.
To execute on this we will use a scrum-style methodology that I will explain in more detail early in Week 5. The key idea is three two-week periods in which your team will plan, execute, and finalize your project. I will advise on process, meet with groups weekly, and be available for consultation throughout to help in any way I can.
The quarter will conclude during our exam time with presentations of your projects. We’ll discuss details as the time approaches – more info to come!
Evaluation
Not a fan of grades, to be honest. Research has shown that traditional numerical/letter grades decrease intrinsic motivation and joy for learning, can undermine performance, and are potentially riddled with implicit bias. For more reading on this topic:
- The Case Against Grades (Kohn 2011)
- Ungrading: an FAQ (Stommel 2020)
Therefore, grades go against my central goal for this course: getting you engaged with and excited about this topic. In the interest of maintaining a healthy working relationship with the registrar, however, I will submit final grades at the end of the quarter. Below are the forms of evaluation we’ll do.
Effortful Engagement
This is not a course where you can sit back, listen to lectures, study for a final, and pass. We’re going to be in face-to-face discussions and working together collaboratively the entire time. The whole setup fundamentally depends on your effortful engagement with what we’re doing, so that engagement is the primary metric for grading. I’ll borrow a definition of engagement from Emily Pitts Donahoe:
Being engaged in class means attending class every time you’re able; coming to class prepared for the day’s activities; contributing regularly to small- or large-group discussions; being a good classroom citizen by supporting your peers and abiding by our discussion guidelines; submitting work that represents your best effort, in a timely fashion; and submitting work that is your own, not someone else’s.
UC Davis expects on the order of 3 hours of academic work per week per credit; this is a four-credit course, so you should expect to spend 3 hours in class and up to 9 hours outside of class making progress for the course. I expect this will be somewhat less in the early part of the quarter and bursty throughout, but I will especially advocate for consistency in the distribution of your efforts.
I will not strictly track attendance; you’re adults. Don’t come to class if you’re sick, take care of yourself mentally and physically. That said, attendance is a critical aspect of engagement. You should feel that you can take a mulligan and miss one class throughout the quarter with no consequence and no need to mention it. If a situation arises where you need to miss two or more classes for illness or some other reason please be communicative with me about that, upfront and in a timely manner.
Self-Evaluation
You know at least as well as I do how the course is going for you, so we’ll have two self-evaluations, one around midterms and another at the end of the class.
In each self-evaluation I’ll ask you to reflect on your process and progress, your participation in the course, and ultimately to give yourself a grade and explain your reasoning with evidence from throughout the quarter.
For this course, my expectations for an “A” look like: complete the vast majority of readings and annotations in good faith, participate fully in small group discussions and take up the responsibilities of your assigned role, attend class every time you’re able, contribute meaningfully and consistently to your group project, and challenge yourself intellectually and creatively.
I hope to simply take your self-evaluation grades at face value, although if your self-evaluation disagrees significantly with my perception (in either direction) I may ask you to meet with me to hash out why our impressions differ.
Policy on Generative AI
This course is deeply connected to and fundamentally about generative AI technologies. You are therefore permitted (but not at all required) to use any such technologies for all work for this course in almost all cases. I have one hard-and-fast rule, which is that for all assigned readings you must firstly actually read them yourself: you can only look at an AI-generated summary after thoughtfully reading the material yourself. All other uses are allowed, subject to following core principles:
Consent on Inputs
Any information submitted to proprietary, cloud-based AI systems is potentially subject to ingestion as training data. For this and other reasons, consent is an increasingly discussed issue with regards to GenAI. For the purposes of this class, I ask that you seek consent from any parties whose data you submit to such systems. This is likely most applicable to our classroom products such as discussion notes and comments on readings created by your classmates, as well as work products from your group projects. Data that is already public (e.g., on the open internet) is exempt, and I give proactive consent for any such material I create.
Disclosure on Outputs
The flipside of the consent coin is that many argue, and indeed in many cases existing laws support, that people have a right to know when they are interacting with AI-generated or AI-mediated content. Therefore if you use generative AI tools for your work for the course you are obligated to disclose those uses to fellow students and to me. In discussions or group work this can look like a simple preface to your contribution, and for your group projects I will ask for documentation in a specific manner we’ll discuss later in the quarter.
Inclusion Statement
I am committed to creating an inclusive environment that actively values the diversity of backgrounds, identities, and experiences of everyone in the classroom. I welcome you to talk with me if you have any feedback or if there’s anything I can do to better support you. If you’d prefer to contact me anonymously you can do so using the form at the bottom of my faculty webpage.