1
LANGUAGE TECHNOLOGY & SOCIAL IMPLICATIONS
© by Rachelle Broeren
CONTENT
Week 1 Ethics and Technology ............................................................................................................... 2
Lecture 1 ..................................................................................................................................................... 2
Reading week 1: Fair Warning .................................................................................................................... 3
Seminar week 1 .......................................................................................................................................... 3
Pre-recorded lecture week 1 – Smart solutions ......................................................................................... 7
Week 2 - How does ‘smart’ technology work? Evaluation metrics .......................................................... 8
Reading week 2 – Fairness and machine learning ...................................................................................... 8
Video by Mitchell - Bias in the Vision and Language of Artificial Intelligence ............................................ 9
Video by Isabell - You Can’t Escape Hyperparameters and Latent Variables: Machine Learning as a
Software Engineering Enterprise .............................................................................................................. 12
Lecture 2 – Language technology and its social implications ................................................................... 13
Seminar week 2 ........................................................................................................................................ 21
Week 3 – Understanding the Impact of (language) technology ............................................................. 23
Pre Recorded lectures week 3 .................................................................................................................. 23
Reading: Filter Bubble – Eli Pariser ........................................................................................................... 32
Reading: Challenging Google Search filter bubbles in social and political information: Disconfirming
evidence from a digital methods case study (Courtois et al., 2018) ........................................................ 33
Reading: Perceived threats from social bots: The media's role in supporting literacy - (Schmuck & von
Sikorski, 2020) .......................................................................................................................................... 33
Seminar week 4 ........................................................................................................................................ 35
Week 5 - Natural language processing, Natural language Generation ................................................... 36
YouTube video – Computational linguistics: Crash Crouse Linguistics ..................................................... 36
Reading: The social impact of natural language processing. Hovy, D., & Spruit, S. L. (2016). ................. 37
Reading: What to do about non-standard (or non-canonical) language in NLP. Plank, B. (2016) ........... 38
Lecture week 5 - Natural language processing & natural language generation ....................................... 39
Seminar week 5 ........................................................................................................................................ 46
Week 6 - Applications and implications of language technology ........................................................... 49
Reading: On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? - Bender et al. (2021)
.................................................................................................................................................................. 49
Reading: Gender and Dialect Bias in YouTube’s Automatic Captions (Tatman, 2017) ............................. 49
Lecture week 6 part 1 - Voice interfaces .................................................................................................. 50
Lecture week 6 part 2 - Virtual assistants and chatbots .......................................................................... 53
LANGUAGE TECHNOLOGY & SOCIAL IMPLICATIONS
© by Rachelle Broeren
CONTENT
Week 1 Ethics and Technology ............................................................................................................... 2
Lecture 1 ..................................................................................................................................................... 2
Reading week 1: Fair Warning .................................................................................................................... 3
Seminar week 1 .......................................................................................................................................... 3
Pre-recorded lecture week 1 – Smart solutions ......................................................................................... 7
Week 2 - How does ‘smart’ technology work? Evaluation metrics .......................................................... 8
Reading week 2 – Fairness and machine learning ...................................................................................... 8
Video by Mitchell - Bias in the Vision and Language of Artificial Intelligence ............................................ 9
Video by Isabell - You Can’t Escape Hyperparameters and Latent Variables: Machine Learning as a
Software Engineering Enterprise .............................................................................................................. 12
Lecture 2 – Language technology and its social implications ................................................................... 13
Seminar week 2 ........................................................................................................................................ 21
Week 3 – Understanding the Impact of (language) technology ............................................................. 23
Pre Recorded lectures week 3 .................................................................................................................. 23
Reading: Filter Bubble – Eli Pariser ........................................................................................................... 32
Reading: Challenging Google Search filter bubbles in social and political information: Disconfirming
evidence from a digital methods case study (Courtois et al., 2018) ........................................................ 33
Reading: Perceived threats from social bots: The media's role in supporting literacy - (Schmuck & von
Sikorski, 2020) .......................................................................................................................................... 33
Seminar week 4 ........................................................................................................................................ 35
Week 5 - Natural language processing, Natural language Generation ................................................... 36
YouTube video – Computational linguistics: Crash Crouse Linguistics ..................................................... 36
Reading: The social impact of natural language processing. Hovy, D., & Spruit, S. L. (2016). ................. 37
Reading: What to do about non-standard (or non-canonical) language in NLP. Plank, B. (2016) ........... 38
Lecture week 5 - Natural language processing & natural language generation ....................................... 39
Seminar week 5 ........................................................................................................................................ 46
Week 6 - Applications and implications of language technology ........................................................... 49
Reading: On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? - Bender et al. (2021)
.................................................................................................................................................................. 49
Reading: Gender and Dialect Bias in YouTube’s Automatic Captions (Tatman, 2017) ............................. 49
Lecture week 6 part 1 - Voice interfaces .................................................................................................. 50
Lecture week 6 part 2 - Virtual assistants and chatbots .......................................................................... 53
