What use are formal design and analysis methods to telecommunications services?

Have formal methods failed, or will they fail, to help us solve problems of detecting and resolving of feature interactions in telecommunications software? This paper contains SWOT(Strengths, Weaknesses, Opportunities and Threats) analysis of the use of formula design and analysis methods in feature interaction analysis and makes some suggestions for future research

Bias and unfairness in machine learning models: a systematic literature review

One of the difficulties of artificial intelligence is to ensure that model decisions are fair and free of bias. In research, datasets, metrics, techniques, and tools are applied to detect and mitigate algorithmic unfairness and bias. This study aims to examine existing knowledge on bias and unfairness in Machine Learning models, identifying mitigation methods, fairness metrics, and supporting tools. A Systematic Literature Review found 40 eligible articles published between 2017 and 2022 in the Scopus, IEEE Xplore, Web of Science, and Google Scholar knowledge bases. The results show numerous bias and unfairness detection and mitigation approaches for ML technologies, with clearly defined metrics in the literature, and varied metrics can be highlighted. We recommend further research to define the techniques and metrics that should be employed in each case to standardize and ensure the impartiality of the machine learning model, thus, allowing the most appropriate metric to detect bias and unfairness in a given context

Both Facts and Feelings: Emotion and News Literacy

News literacy education has long focused on the significance of facts, sourcing, and verifiability. While these are critical aspects of news, rapidly developing emotion analytics technologies intended to respond to and even alter digital news audiences’ emotions also demand that we pay greater attention to the role of emotion in news consumption. This essay explores the role of emotion in the “fake news” phenomenon and the implementation of emotion analytics tools in news distribution. I examine the function of emotion in news consumption and the status of emotion within existing news literacy training programs. Finally, I offer suggestions for addressing emotional responses to news with students, including both mindfulness techniques and psychological research on thinking processes

Lip(s) Service: A Socioethical Overview of Social Media Platforms’ Censorship Policies Regarding Consensual Sexual Content

The regulation of sexual exploitation on social media is a pressing issue that has been addressed by government legislation. However, laws such as FOSTA-SESTA has inadvertently restricted consensual expressions of sexuality as well. In four social media case studies, this paper investigates the ways in which marginalized groups have been impacted by changing censorship guidelines on social media, and how content moderation methods can be inclusive of these groups. I emphasize the qualitative perspectives of sex workers and queer creators in these case studies, in addition to my own experiences as a content moderation and social media management intern for Lips.social. This paper concludes with potential solutions to current biases in social media content moderation