This paper contributes to the nascent research on Internet memes examined as items of (de)legitimising discourse, its empirical focus being memes addressing NFTs (non-fungible tokens). The mystifying NFT trade became hype in 2021, attracting massive media coverage and stimulating heated discussion across social media, which includes memetic content production. This study explores the multimodal discourses of (de)legitimisation in NFT memes. Based on a dataset of relevant 993 memes extracted manually from an automatically generated corpus of 1628 Twitter memes, a deductive-inductive multimodal analysis proves the original dichotomy (underlying the polarised views expressed through memes) insufficient. Seven memetic patterns dictated by (de)legitimisation stances are identified. In addition to NFT-legitimising and NFT-delegitimising categories, ambiguous equipotential (de)legitimisation memes, two categories of memes with blended (de)legitimising stances and two categories of elusive-stance memes are distinguished. The notion of ‘quasi-legitimisation’ is proposed to capture the memetic categories that normalise the thorny concept of NFTs.
How AI models should deal with political topics has been discussed, but it remains challenging and requires better governance. This paper examines the governance of large language models through individual and collective deliberation, focusing on politically sensitive videos. We conducted a two-step study: interviews with 10 journalists established a baseline understanding of expert video interpretation; 114 individuals through deliberation using InclusiveAI, a platform that facilitates democratic decision-making through decentralized autonomous organization (DAO) mechanisms. Our findings reveal distinct differences in interpretative priorities: while experts emphasized emotion and narrative, the general public prioritized factual clarity, objectivity, and emotional neutrality. Furthermore, we examined how different governance mechanisms - quadratic vs. weighted voting and equal vs. 20/80 voting power - shape users' decision-making regarding AI behavior. Results indicate that voting methods significantly influence outcomes, with quadratic voting reinforcing perceptions of liberal democracy and political equality. Our study underscores the necessity of selecting appropriate governance mechanisms to better capture user perspectives and suggests decentralized AI governance as a potential way to facilitate broader public engagement in AI development, ensuring that varied perspectives meaningfully inform design decisions.