Documents found
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3011.More information
Multimodality in assignments is increasingly common in higher education, thereby requiring students to demonstrate competency in the employment of multiple modes to communicate. Specifically, the field of engineering communication relies on multimodal resources to construct meaning and convey information. This article describes the integration of multimodality in a second-year software design and communication course assignment. In this assignment, students read the text, Made to Stick that enlists six principles of effective communication strategies and are expected to apply these communicative principles to a tech talk video. Students then produce a written argument which evaluates how effectively the presenter employed Made to Stick principles. Through engagement with multimodal resources, students are afforded the opportunity to practice and develop three skills of application, analysis and argumentation.
Keywords: Multimodality, engineering communication, pedagogical affordances, application
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3012.
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3013.More information
This Dialogue paper argues that the use of synthetic data can never be “ethical.” My argument imports a normative stance from media ethics that “being-ethical-means-being-accountable” (Glasser and Ettema 2008). Building from discourse ethics, this stance positions such ethics as having “the facility to argue articulately and deliberate thoughtfully about moral dilemmas, which in the end means being able to justify, publicly and compellingly, their resolution” (Glasser and Ettema 2008: 512). Crucially, this approach is dialogical and social, necessitating a space open to all affected by relational practices and processes. While the use of synthetic data in commercial institutional contexts may offer workarounds to privacy concerns regarding personally identifiable information (PII) or unpaid user labor—or seem relatively innocuous, as in the case of training computer vision algorithms in video games—this facilitates, as others in this Dialogue section argue in their respective papers, a “fix” or “solutionist” framing that elides ethics and de-politicizes synthetic data. Synthetic data therefore intensifies a pre-existing lack of accountability inherent within automated systems more generally, and through this, entrenches and compounds surveillant practices. In some arenas, the stakes are quite literally life or death, such as in the development of medical AI, and more perniciously, the migration of models from commercial to state deployment in law enforcement and military contexts. Given the foreclosure of thoughtful, articulate, and reflexive inclusive deliberation on the significant moral implications of AI’s vast and ever-growing assemblages, and synthetic data’s role in further mystifying and legitimating its seemingly unbridled development and deployment, I argue that synthetic data can never meet the standard of “ethical” practice.
Keywords: synthetic data, media ethics, accountability, Arificial Intelligence, algorithmic transparency, AI ethics, discourse ethics
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3014.More information
Keywords: synthetic data, synthetic media, syntheticity, big data, Artificial Intelligence, generative AI
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3017.
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3020.