| Date | Topic | Reading | Due |
|---|
| 3/27 |
Introduction, organization, overview
|
No reading assumed for first day |
|
| 3/31 |
|
|
KWLA papers: K & W due 11pm |
| 4/3 |
Language as joint activity, intersubjectivity |
Clark 1996, Baldwin 1995, Reddy 1979, Weizenbaum 1976
- Reading questions:
- What does this say about how humans use language in communication?
- How do people react to computer-generated language?
- What are the crucial differences between human-human and human-machine communicative contexts?
- What sort of extra-linguistic information do people use and/or infer in human-machine or human-human interaction?
- What can we learn about the nature of dialogue as multi-turn conversations with changing salience over time/how that differs from one-turn conversations?
| |
| 4/10 |
Presupposition, Public commitments, Coherence relations |
- Readings:
- Bender & Lascarides 2019 (access via UW libraries, items 4-6 + 66-70 + 81 + 96)
- Hamblin 1970: Not available, so look at Walton 1991 instead ("Hamblin on the Standard Treatment of Fallacies")
- Lascarides & Asher 2009 (Agreement, Disputes and Commitments in Dialogue)
- Asher & Lascarides 2013 (Logics of Conversation; print book available at Suzzallo)
- Kim et al 2021 (Which Linguist Invented the Lightbulb? Presupposition Verification for Question-Answering)
- Kaplan 1978 (Indirect Responses to Loaded Questions)
- Levinson 2000 (Presumptive meanings, access e-book via UW libraries)
- de Marneffe et al 2019 (The CommitmentBank: Investigating projection in naturally occurring discourse)
- Reading questions:
- What are the structures involved -- what is a presupposition, what is an implicature, what is an entailment?
- How do people notice that the other party hasn't gotten or has misunderstood the implicature?
- How would a probabilistic model detect implicatures? / How could a probabilistic model control implicatures arising from its output?
- What would the desirable way for an artificial agent to reject faulty premises? And how and why?
- Are there any things that should not be presupposed at all?
- By artificial agents
- By humans in general
- By humans interacting with artificial agents
- Metrics: How are presupposition detection systems evaluated?
- How do public commitments fit with accountability (including by corporations)?
| |
| 4/17 |
Negotiating meaning (sociolinguistic perspectives) |
- Readings
- Erving Goffman (1974) Frame Analysis: an Essay on the Organization of Experience
- Sally McConnell-Ginet Words Matter
- Mische, Ann. 2003. Cross-Talk in Movements: Reconceiving the Culture-Network LinkLinks to an external site.. In Social Movements and Networks: Relational Approaches to Collective Action, edited by Mario Diani and Doug McAdam, 258–80.
- Myrendal, Jenny. 2019 Negotiating meanings online: Disagreements about word meaning in discussion forum communicationLinks to an external site.. Discourse Studies
- Rebecca Clift, 2001. Meaning in Interaction: The Case of Actually, Language, Vol. 77, No. 2, pp. 245-291 https://www.jstor.org/stable/3086775
- Hayashi et al (eds) 2013. Conversational Repair and Human Understanding. CUP
https://www.cambridge.org/core/books/conversational-repair-and-human-understanding/8698A66FEC0269B9BB6B96D052709AF0
- Steele 2019 Non-binary speech, race, and non-normative gender: Sociolinguistic style beyond the binary
- Moore 2006 ‘You tell all the stories’: Using narrative to explore hierarchy within a Community of Practice
- King 2016 On Negotiating Racial and Regional Identities: Vocalic Variation Among African Americans in Bakersfield, California
- Eberhardt & Downs 2015 "(r) You Saying Yes to the Dress?": Rhoticity on a Bridal Reality Television Show
- Chun 2011 Reading race beyond black and white
- Calder & King 2022 Whose gendered voices matter?: Race and gender in the articulation of /s/ in Bakersfield, California
- Austen 2020 Production and perception of the PIN-PEN merger
- Reading questions
- How do human interlocutors manage conversational repair?
- How do human communities coordinate on meanings even as the meanings are changing?
- Can conversation analysis developed for studying human hierarchies (of power) be applied to understand biases in artificial agent output?
- What is the fine line between what counts as a generalization v. bias? What is accepted presupposition vs. what is bias?
- How do people go about developing ways of communicating/different writing styles in different online communities? How would we extend this when we interact with artificial agents?
- What factors affect the differential perception of words when used to describe people of different social categories (e.g. gender)?
- What about the design of artificial voices wrt to sociolinguistic variables -- should artificial agents have a social address? What does it mean if they just get the "default" forms?
| |
| 4/24 |
Interface design |
- Readings
- Pearl (2016) Designing Voice User Interfaces
- Shevat (2017) Designing Bots
- Hall (2018) Conversational Design
- Deibel & Evanhoe (2021) Conversations with Things: UX Design for Chat and Voice
- Jokinen & McTear (2009) Spoken Dialogue Systems (Other works by McTear: https://www.waterstones.com/author/michael-mctear/901018 )
- Balentine (2007) It's Better to Be a Good Machine Than a Bad Person: Speech Recognition and Other Exotic User Interfaces at the Twilight of the Jetsonian Age
- Vlahos (2019) Talk to Me: How Voice Computing Will Transform the Way We Live, Work, and Think
- Schlangen (2005) Modelling dialogue: Challenges and Approaches Künstliche Intelligenz .bib: https://clp.ling.uni-potsdam.de/bibliography/Schlangen-2005-2/
- Bonomo (2023) An Ethical AI Never Says "I"
- Reading questions
- What considerations are given to social address in bot design?
- What are the factors we would evaluate voice or chat interfaces on?
- When is a dialogue system useful vs a hinderance?
- Can we imagine designing NL tools in a way that is not necessarily conversational? What would that look like?
- Could there be different design conventions for task- or intent-based chatbots vs. open-ended LLM based chatbots?
- What user data is appropriate to collect with what levels of transparency and how to build in consent?
- Data from one user to facilitate interaction with them v. data to be used across users
- Who are the users that the designers are imagining? Are they considering children, etc?
- How do these authors design user studies?
| Term paper proposals due |
| 5/1 |
Value Sensitive Design |
- Readings (further options on https://vsdesign.org/publications/)
- Hendry, D. G., Friedman, B., & Ballard, S. (2021). Value sensitive design as a formative framework. Ethics and Information Technology, 23(1), 39-44.
- Hendry, D. G. (2020). Designing Tech Policy: Instructional Case Studies for Technologists and Policy Makers. Tech Policy Lab, University of Washington.
- Young, M., Magassa, L., & Friedman, B. (2019). Toward inclusive tech policy design: a method for underrepresented voices to strengthen tech policy documents. Ethics and Information Technology, 21(2), 89-103.
- Logler, N., Yoo, D., & Friedman, B. (2018). Metaphor Cards: A How-to-Guide for Making and Using a Generative Metaphorical Design Toolkit. Proceedings of the 2018 Designing Interactive Systems Conference, 1373-1386.
- Yoo, D. (2018). Stakeholder Tokens: a constructive method for value sensitive design stakeholder analysis. Ethics and Information Technology.
- Friedman, B., Hendry, D. G., & Borning, A. (2017). A Survey of Value Sensitive Design Methods. Foundations and Trends in Human-Computer Interaction, 11(2), 63-125.
- Magassa, L., Young, M., & Friedman, B. (2017). Diverse Voices: A how-to guide for creating more inclusive tech policy documents. Tech Policy Lab, University of Washington.
- Yoo, D., Huldtgren, A., Woelfer, J. P., Hendry, D. G., & Friedman, B. (2013). A value sensitive action-reflection model: evolving a co-design space with stakeholder and designer prompts. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 419-428.
- Friedman, B., & Hendry, D. (2012). The envisioning cards: a toolkit for catalyzing humanistic and technical imaginations. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 1145-1148.
- Woelfer, J. P., & Hendry, D. G. (2011). Designing ubiquitous information systems for a community of homeless young people: precaution and a way forward. Personal and Ubiquitous Computing, 15(6), 565-573.
- Freier, N. G. (2007). Children distinguish conventional from moral violations in interactions with a personified agent. CHI '07 Extended Abstracts on Human Factors in Computing Systems, 2195-2200.
- Nathan, L. P., Klasnja, P. V., & Friedman, B. (2007). Value scenarios: a technique for envisioning systemic effects of new technologies. CHI '07 Extended Abstracts on Human Factors in Computing Systems, 2585-2590.
- Friedman, B. (1996). Value-sensitive design. ACM Interactions, 3(6), 16-23.
- Friedman, B. (1995). "It's the computer's fault": reasoning about computers as moral agents. Conference Companion on Human Factors in Computing Systems, 226-227.
- Reading questions, TBD
- What is the definition of value sensitive design?
- How can we apply value sensitive design techniques in the design or evaluation of chatbots/voice assistants/other systems that interact using NL?
- What's in common and what is different across the methods of value sensitive design?
- How can organizations making LLM chatbots take into account the values of diverse users and the stated values of the company while maintaining broad appeal?
- Tension between supporting user values and the goal of being "politically neutral"
- How do you elicit participants' values, without steering or influencing them?
- How do policy and tech design influence each other?
- Given recent tech developments, what is missing from current tech policy?
- How do we make the business case for bringing value sensitive design into designing chatbots?
- What does value sensitive design have to say about how to run user studies?
- How do these studies manage participant privacy?
| |
| 5/8 |
Term project peer discussions |
| Term paper outline due (5/9) |
| 5/15 |
Black Mirror Writer's Room |
|
|
| 5/22 |
Regulatory proposals |
- Readings
- Reading questions, TBD
- What systems are considered "AI systems" for the scope of these laws?
- What are the risks (relevant to interactive text systems) that the legislation appears to be targeting?
- Are they looking at risks to individuals, communities, civilization, and over what kinds of time scales?
- According to these proposals, who has accountability for the output of natural language generation systems?
- What are the legal consequences for violations of these laws?
- Do the regulations apply to: system builders, system users, media coverage, other?
- How general are the regulations? Do they call out specific use cases/disciplines of "AI"?
- For the regulations not yet in effect, what will the impact be on existing already deployed products?
- Do the regulations account for factuality problems with text generating machines and how to they address this?
- Are the proposals additional laws or changes to existing ones to account for "AI"? (Ex: slander, identity theft, medical malpractice...)
- To what extent do these proposals address data theft?
- How does copyright apply to synthetic media based on others' art?
| Term paper draft due |
| 5/29 |
No class [Memorial Day holiday] |
| |
| 5/30 |
|
| KWLA papers due
Comments on partner's paper draft due |
| 6/8 |
|
| Term papers due |