What People Think AI Should Infer From Faces

Engelmann, Severin; Ullstein, Chiara; Papakyriakopoulos, Orestis; Großklags, Jens

doi:10.1145/3531146.3533080

Cited by 12 publications

(4 citation statements)

References 85 publications

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“…Coders then relabelled the same corpus, yielding an intercoder reliability of 0.75. This was higher than the expected minimum for coding complicated language tasks in the literature (>0.6 -see e.g., [5,37,43,92,105,122]). Since coders' labeling practices were robust, they proceeded with the selection and labeling of further comments.…”

Section: Annotation and Model Trainingmentioning

confidence: 53%

Upvotes? Downvotes? No Votes? Understanding the relationship between reaction mechanisms and political discourse on Reddit

Papakyriakopoulos,

Engelmann,

Winecoff

2023

Preprint

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A significant share of political discourse occurs online on social media platforms. Policymakers and researchers try to understand the role of social media design in shaping the quality of political discourse around the globe. In the past decades, scholarship on political discourse theory has produced distinct characteristics of different types of prominent political rhetoric such as deliberative, civic, or demagogic discourse. This study investigates the relationship between social media reaction mechanisms (i.e., upvotes, downvotes) and political rhetoric in user discussions by engaging in an in-depth conceptual analysis of political discourse theory. First, we analyze 155 million user comments in 55 political subforums on Reddit between 2010 and 2018 to explore whether users' style of political discussion aligns with the essential components of deliberative, civic, and demagogic discourse. Second, we perform a quantitative study that combines confirmatory factor analysis with difference in differences models to explore whether different reaction mechanism schemes (e.g., upvotes only, upvotes and downvotes, no reaction mechanisms) correspond with political user discussion that is more or less characteristic of deliberative, civic, or demagogic discourse. We produce three main takeaways. First, despite being "ideal constructs of political rhetoric," we find that political discourse theories describe political discussions on Reddit to a large extent. Second, we find that discussions in subforums with only upvotes, or both up-and downvotes are associated with user discourse that is more deliberate and civic. Third, and perhaps most strikingly, social media discussions are most demagogic in subreddits with no reaction mechanisms at all. These findings offer valuable contributions for ongoing policy discussions on the relationship between social media interface design and respectful political discussion among users. 1

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Section: Annotation and Model Trainingmentioning

confidence: 53%

Upvotes? Downvotes? No Votes? Understanding the relationship between reaction mechanisms and political discourse on Reddit

Papakyriakopoulos,

Engelmann,

Winecoff

2023

Preprint

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“…And of course when creating predictive models, it is important to consider how those predictions might be used, even in unintended ways [6,85]. For example, instructors can demonstrate how AI can reflect physiognomic measuring through models learning correlations between arbitrary inputs and outputs by pointing to examples that may be even more high stakes or problematic than the course context (e.g., predicting sexual orientation from images) [29,56]. Prior research on ethics integration into computing courses often emphasizes that connecting concepts directly to that content (e.g., as part of a technical assignment) is an important strategy for illustrating that ethical consideration should be part of technical practice [30].…”

Section: Ai Introductory Courses Should Raise Ethical Issues Explicit...mentioning

confidence: 99%

“…The framing of data we find in the courses -as abstract objects that can be played around with at will -could further lower a sense of accountability in learners. As such, introductory AI courses contribute to an understanding of AI development that fails to account for the properties of the social context for which they are deployed [28,29,79]. Prediction and classification become a matter of "fitting the line to the data" rather than procedures that might be sorting people into categories [27].…”

Section: Ai Introductory Courses Should Raise Ethical Issues Explicit...mentioning

confidence: 99%

Visions of a Discipline: Analyzing Introductory AI Courses on YouTube

Engelmann,

Choksi,

Wang

et al. 2024

The 2024 ACM Conference on Fairness, Accountability, and Transparency

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Education plays an indispensable role in fostering societal well-being and is widely regarded as one of the most influential factors in shaping the future of generations to come. As artificial intelligence (AI) becomes more deeply integrated into our daily lives and the workforce, educational institutions at all levels are directing their focus on resources that cater to AI education. Yet, informal education, including online learning on social media platforms like YouTube, plays an increasingly significant role for both students and the general public. Offering greater accessibility compared to formal education, millions of individuals use YouTube for educational resources on AI today. Due to the substantial societal impact of AI, it is crucial for introductory AI courses to meaningfully address the ethical implications associated with AI. Our work investigates the current landscape of introductory AI courses on YouTube, and the potential for introducing ethics in this context. We qualitatively analyze the 20 most watched introductory AI courses on YouTube, coding a total of 92.2 hours of educational content viewed by close to 50 million people. We find that these introductory AI courses do not meaningfully engage with ethical or societal challenges of AI (RQ1). When defining and framing AI, introductory AI courses foreground excitement around AI's transformative role in society, over-exaggerate AI's current and future abilities, and anthropomorphize AI (RQ2). In teaching AI, we see a widespread reliance on corporate AI tools and frameworks as well as a prioritization on a hands-on approach to learning rather than on conceptual foundations (RQ3). In promoting key AI practices, introductory AI courses abstract away entirely the socio-technical nature of AI classification and prediction, for example by favoring data quantity over data quality (RQ4). Given the power of openly available introductory courses to shape enduring beliefs around AI and its field at the onset of a learning journey, we extend our analysis with recommendations that aim to integrate ethical reflections into introductory AI courses. We recommend that introductory AI courses

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“…Artificial intelligence intends to leverage computers and computing machines to mime the problem solving and process of decision making abilities of a human mind in a certain way. The basic way to understand the concept of artificial intelligence is that it is a field which gathers computer science and datasets which are robust to execute the problems in a proactive manner [1]. It can be stated that artificial intelligence also intends to encompass the subsidiary fields which are associated with deep learning and have been mentioned in the conjunction part of artificial intelligence in a frequent manner.…”

Section: Introductionmentioning

confidence: 99%

Impact of AI on Leveraging Knowledge for Engineers

Alfred¹

2022

TTIDMKD

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Verification for access is used in software to secure information of the user. There are some kinds of verification process, however, as per the The following study is based on the impact of AI in leveraging knowledge for engineers and the study has been served with authentic insights which are connected directly with the concept of AI. At the beginning of the study, the concept of AI has been depicted. Also, the impact of AI on the engineers to leverage knowledge been presented in the following study. The study has also depicted the basic concept of AI technology including the importance of AI technology knowledge for the engineers. Different field of engineers have been influenced by the AI technologies. Advantages and disadvantages also have been discussed over here to evaluate the consistency of the AI technologies. Ways to leveraging the knowledge of AI technology also have been focused in the study for the progression of the engineering field. Challenges faced by AI technology for the implication of AI technologies have been highlighted in the study along with strategies used by AI technology to leveraging knowledge also has been discussed here firmly. A brief interpretation of the results also has been done in this study.

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What People Think AI Should Infer From Faces

Cited by 12 publications

References 85 publications

Upvotes? Downvotes? No Votes? Understanding the relationship between reaction mechanisms and political discourse on Reddit

Upvotes? Downvotes? No Votes? Understanding the relationship between reaction mechanisms and political discourse on Reddit

Visions of a Discipline: Analyzing Introductory AI Courses on YouTube

Impact of AI on Leveraging Knowledge for Engineers

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