Ethics and Social Justice for AI in Data Science

The advances of AI raise several critical questions about human values and ethics, highlighting the need for researchers and developers to consider the ethical implications and the risks of neglecting them. In the past few years, student researchers have developed an AI model that allows users to test their surveys for possible breaches of subject confidentiality. This allows the users to gauge the ethicality of their proposal. This summer, we have expanded on this research and launched an interactive model for students and researches to assess their current work for ethical and social justice implications. Using Langchain and Figma, we have created an interactive chatbot which allows users to receive feedback on their project regarding the ethical and social considerations of their work

Meta-analysis of AI Research in Journalism: Challenges, Opportunities and Future Research Agenda for Arab Journalism

The use of artificial intelligence tools in newsrooms is revolutionary and controversial as well. Despite the promising opportunities provided by AI to enhance digital journalism practice, it also raises several legal, professional, and ethical considerations. Research about AI in Arab media is a promising area of interest that increasingly attracts Arab scholars. However, there is a need for systematic and purposive growth in future research about AI and Arab media, that considers the socio-cultural and economic contexts of Arab countries and meets the priorities and needs of Arab media organizations. Accordingly, this paper provides researchers with an overview of the main challenges and debates in the field of AI and journalism studies. This study applies a systematic review of a sample of English and Arabic-written studies from 2014 to 2022 about the implications, challenges and considerations of using AI in newsrooms. Based on the analysis, the study proposed a future research agenda about AI and Arab journalism

Transforming Problematic Into Positive: Practice-Based Recommendations for Resolving Paradigmatic and Methodological Conflicts in Appreciative Inquiry

Researchers have employed Appreciative Inquiry (AI) in a variety of methodological contexts, in a variety of settings, and toward a variety of outcomes. For practitioners seeking to both identity and amplify the best of what is, AI has been a sort of multi-functional toolset, improving outcomes both small and grand. Amidst this successful history of the application of Appreciative Inquiry (AI), little attention has been given to some of the limitations or even risks of applying its practices to whatever extent and toward whichever outcomes. The models supplied by AI may prove problematic in several ways, among them: ontological realism, epistemological objectivism, the potential for axiological denial and ethical deception, the potential for methodological discord, a posture rooted in problems, blind spotting, and a neglect of the integral nature of things. This paper brings together the theoretical premises of Appreciative Inquiry methodologies, emerging considerations from transdisciplinarity and consciousness studies, and practical applications from a recent AI project, so as to construct considerations and recommendations for AI practitioners for resolving some of the methodological and paradigmatic conflicts that may arise

Designing a realistic peer-like embodied conversational agent for supporting children\textquotesingle s storytelling

Advances in artificial intelligence have facilitated the use of large language models (LLMs) and AI-generated synthetic media in education, which may inspire HCI researchers to develop technologies, in particular, embodied conversational agents (ECAs) to simulate the kind of scaffolding children might receive from a human partner. In this paper, we will propose a design prototype of a peer-like ECA named STARie that integrates multiple AI models - GPT-3, Speech Synthesis (Real-time Voice Cloning), VOCA (Voice Operated Character Animation), and FLAME (Faces Learned with an Articulated Model and Expressions) that aims to support narrative production in collaborative storytelling, specifically for children aged 4-8. However, designing a child-centered ECA raises concerns about age appropriateness, children\textquotesingle s privacy, gender choices of ECAs, and the uncanny valley effect. Thus, this paper will also discuss considerations and ethical concerns that must be taken into account when designing such an ECA. This proposal offers insights into the potential use of AI-generated synthetic media in child-centered AI design and how peer-like AI embodiment may support children\textquotesingle s storytelling.Comment: 6 pages with 2 figures. The paper has been peer-reviewed and presented at the "CHI 2023 Workshop on Child-centred AI Design: Definition, Operation and Considerations, April 23, 2023, Hamburg, German

Beyond Fair Pay: Ethical Implications of NLP Crowdsourcing

The use of crowdworkers in NLP research is growing rapidly, in tandem with the exponential increase in research production in machine learning and AI. Ethical discussion regarding the use of crowdworkers within the NLP research community is typically confined in scope to issues related to labor conditions such as fair pay. We draw attention to the lack of ethical considerations related to the various tasks performed by workers, including labeling, evaluation, and production. We find that the Final Rule, the common ethical framework used by researchers, did not anticipate the use of online crowdsourcing platforms for data collection, resulting in gaps between the spirit and practice of human-subjects ethics in NLP research. We enumerate common scenarios where crowdworkers performing NLP tasks are at risk of harm. We thus recommend that researchers evaluate these risks by considering the three ethical principles set up by the Belmont Report. We also clarify some common misconceptions regarding the Institutional Review Board (IRB) application. We hope this paper will serve to reopen the discussion within our community regarding the ethical use of crowdworkers.Comment: To be published in NAACL-HLT 2021. 12 pages, 1 figure, 3 table

AI-Driven Learning Analytics in STEM Education

In recent years, the integration approach of Artificial Intelligence (AI) is called for many disciplines, it also STEM education has paved the way for transformative advancements. This paper provides an example of AI-driven learning analytics within the context of STEM education. It provides a thorough analysis of the AI-driven STEM curriculum and its associated paradigm. Additionally, it highlights the obstacles and possible threats that educators and institutions face when implementing technological innovations in the classroom. The serves as a valuable resource for educators, researchers, and policymakers seeking to harness the power of AI-driven learning analytics to enhance STEM education. The transformative potential of AI is now shaping the future of STEM learning environments while advocating for a responsible and ethical approach to data-driven education. Ethical concerns and moral considerations should be discussed in school AI and STEM education

Enhancing Institutional Assessment and Reporting Through Conversational Technologies: Exploring the Potential of AI-Powered Tools and Natural Language Processing

This study explores the potential of conversational technologies, AI-powered tools, and natural language processing (NLP) in enhancing institutional assessment and reporting processes in higher education. The traditional approach to assessment often involves labor-intensive manual analysis of extensive data and documents, which burdens institutions. To address these challenges, AI-powered tools, such as ChatGPT, LangChain, Poe, Claude, and others, along with NLP techniques, are investigated in relationship to their ability to improve institutional assessment practices and output. By leveraging these advanced technologies, assessment officers and institutional effectiveness, researchers can engage in dynamic conversations with data, transforming spreadsheets and documents from static artifacts into interactive resources. These tools streamline communication, collaboration, and decision-making processes, empowering committees and working groups to achieve their goals effectively. Additionally, the potential applications of NLP in analyzing vast amounts of institutional data, including student feedback, faculty evaluations, and institutional documents, shall be discussed. Language models enable the extraction of meaningful insights from unstructured data sources, facilitating real-time decision-making processes. Ethical considerations related to data privacy, mining, and compliance with regulations like FERPA are crucial aspects addressed in this study. The contribution of this research lies in uncovering the transformative impact of conversational technologies, AI-powered tools, and NLP techniques on institutional assessment and reporting. By embracing these advancements responsibly and ensuring alignment with ethical principles, institutions can unlock the full potential of these tools, facilitating more efficient, data-driven decision-making processes in higher education. The study showcases how conversational technologies, AI-powered tools, and NLP techniques offer new possibilities for improving institutional assessment and reporting practices. By integrating these technologies responsibly and addressing ethical considerations, institutions can enhance their assessment processes and make more informed decisions based on comprehensive, real-time insights

Generative AI tools in art education: Exploring prompt engineering and iterative processes for enhanced creativity

The rapid development and adoption of generative artificial intelligence (AI) tools in the art and design education landscape have introduced both opportunities and challenges. This timely study addresses the need to effectively integrate these tools into the classroom while considering ethical implications and the importance of prompt engineering. By examining the iterative process of refining original ideas through multiple iterations, verbal expansion, and the use of OpenAI’s DALL E2 for generating diverse visual outcomes, researchers gain insights into the potential benefits and pitfalls of these tools in an educational context. Students in the digital at case study were taught prompt engineering techniques and were tasked with crafting multiple prompts, focusing on refining their ideas over time. Participants demonstrated an increased understanding of the potential and limitations of generative AI tools and how to manipulate subject matter for more effective results. The iterative process encouraged students to explore and experiment with their creative ideas, leading to a deeper understanding of the possibilities offered by AI tools. Despite acknowledging the ethical concerns regarding copyright and the potential replacement of artists, students appreciated the value of generative AI tools for enhancing their sketchbooks and ideation process. Through prompt engineering and iterative processes, students developed a more detail oriented approach to their work. The challenge of using AI generated images as final products was conceptually intriguing, requiring further investigation and consideration of the prompts. This study high-lights the potential benefits and challenges of integrating generative AI tools into art and design classrooms, emphasizing the importance of prompt engineering, iterative processes, and ethical considerations as these technologies continue to evolve

Impact of artificial intelligence (AI) in enhancing productivity and reducing stress among students

The rapid growth of chatbots and artificial Artificial intelligence (AI) has brought about a new time of learning and exploration. This research article investigates the profound implications of AI in education, focusing specifically on its impact on student productivity and stress reduction. Through a systematic literature review, 15 articles were analyzed, covering the period from 2017 to 2023. The findings highlight the potential of AI-powered educational tools to revolutionize traditional education paradigms by personalizing the learning experience, automating administrative tasks, and providing intelligent support. AI enables effective addressing of the challenges faced by students in today\u27s educational environment, including mounting workloads and pressures. Students are empowered with effective learning strategies by optimizing time utilization through intelligent scheduling, task management, and performance analysis. Furthermore, AI-powered chatbots and virtual mentors are crucial in offering emotional support, effectively reducing students\u27 anxiety levels. Ethical considerations such as data privacy, algorithmic bias, and equitable access to AI tools are addressed. Collaboration among educational institutions, policymakers, and researchers is emphasized as vital to harnessing AI\u27s power for a positive and inclusive learning environment. This research article contributes to the growing body of knowledge on AI\u27s impact on education, providing valuable insights for further exploring and implementing AI-driven solutions in educational settings