Category: Ethics
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Generative AI, plagiarism, and “cheating”
Back in January, I wrote a post called Beyond Cheating, reflecting on the ChatGPT bans that were rolling out across various Australian states and the “cheating” narrative that had accompanied the chatbot since its release. In that earlier post, I argued that banning and blocking generative AI would only contribute to the digital divide –…
Leon Furze
academic dishonesty, academic evaluation, Academic Integrity, AI advantages, AI and academic culture, AI and cheating, AI and plagiarism, AI and student workload, AI Assessment Scale, AI detection bias, AI detection software, AI disadvantages, AI ethics, AI Guidelines, AI in analytical essays, AI in classrooms, AI in educational policy, AI in essay writing, AI in Humanities, AI in secondary education, AI in skill demonstration, AI in tertiary education, Assessment Design, authentication methods, ChatGPT, Contract cheating, digital divide, digital literacy, digital technology, distance learning, education, educator perspectives, experiential tasks, formative assessment, GAI, Generative AI, GPTZero, lockdown browsers, non-native English writers, online courses, online learning, oral assessments, out-of-class assessments, proctoring software, summative assessment, supervised assessments, Turnitin, unsupervised assessments, viva, written tasks -
UNESCO Guidelines for Generative AI: Practical Applications for Schools
Following Digital Learning Week in Paris, the United Nations Educational, Scientific and Cultural Organization published a comprehensive document containing guidelines for Generative AI (GAI) in education and research, and exploring the implications for policy. The guidelines are linked to the UN Sustainable Development Goals through Goal 4: ensure inclusive and equitable quality education and promote…
Leon Furze
Academic Integrity, AI benefits, AI challenges, AI competencies, AI controversy, AI impact, AI in Schools, AI training, Assemblies, assessment, Classroom tech, community, creativity, cultural bias, curriculum, Cybersecurity, digital literacy, edtech, education, Equity, ethics, feedback, GAI ethics, GAI policy, Generative AI, Global impact, Guidelines, inclusion, Informed consent, innovation, Learning tools, Monitoring, Parent engagement, Pedagogy, Personalised learning, policy, Professional Development, School policy, Stakeholders, student engagement, students, Sustainability, Teacher development, teachers, Tech adoption, Tech regulation, training, UNESCO, Workshops -
Teaching AI Ethics: Power
This is the final post in a nine-part series exploring AI ethics, originally outlined in this post. Each post goes into detail on the ethical concern and provides practical ways to discuss these issues in a variety of subject areas. Here’s a full list of the rest of the series: This post on Power has…
Leon Furze
AI development., AI ethics, AI outputs, AI training, algorithmic bias, biased datasets, community needs, data bias, discrimination, environmental impact, ethical concerns, ethical guardrails, facial recognition, Fairness, hegemony, Justice, power, predictive policing, responsible AI use, social services, societal biases -
Teaching AI Ethics: Human Labour
This is the eighth post in a series exploring the nine areas of AI ethics outlined in this original post. Each post goes into detail on the ethical concern and provides practical ways to discuss these issues in a variety of subject areas. For the previous post on affect recognition, click here. When people think…
Leon Furze
AI development., AI ethics, AI outputs, AI training, algorithmic bias, biased datasets, community needs, data bias, discrimination, environmental impact, ethical concerns, ethical guardrails, facial recognition, Fairness, Justice, predictive policing, responsible AI use, social services, societal biases -
Teaching AI Ethics: Affect Recognition
This is the seventh post in a series exploring the nine areas of AI ethics outlined in this original post. Each post goes into detail on the ethical concern and provides practical ways to discuss these issues in a variety of subject areas. For the previous post on datafication, click here. As artificial intelligence continues…
Leon Furze
AI development., AI ethics, AI outputs, AI training, algorithmic bias, biased datasets, community needs, data bias, discrimination, environmental impact, ethical concerns, ethical guardrails, facial recognition, Fairness, Justice, predictive policing, responsible AI use, social services, societal biases -
Teaching AI Ethics: Datafication
This is the sixth post in a series exploring the nine areas of AI ethics outlined in this original post. Each post goes into detail on the ethical concern and provides practical ways to discuss these issues in a variety of subject areas. For the previous post on privacy, click here. “Datafication” is a term…
Leon Furze
AI development., AI ethics, AI outputs, AI training, algorithmic bias, biased datasets, community needs, data bias, discrimination, environmental impact, ethical concerns, ethical guardrails, facial recognition, Fairness, Justice, predictive policing, responsible AI use, social services, societal biases -
Teaching AI Ethics: Privacy
This is the fifth post in a series exploring the nine areas of AI ethics outlined in this original post. Each post goes into detail on the ethical concern and provides practical ways to discuss these issues in a variety of subject areas. For the previous post on copyright, click here. There are growing concerns…
Leon Furze
AI, AI development., AI ethics, AI outputs, AI training, algorithmic bias, biased datasets, community needs, data, data bias, defmation, discrimination, ethical concerns, ethical guardrails, Europe, facial recognition, Fairness, GDPR, Justice, laws, personal data, predictive policing, privacy, responsible AI use, social services, societal biases -
Teaching AI Ethics: Copyright
This is the 4th post in a series exploring the nine areas of AI ethics outlined in this original post. Each post goes into detail on the ethical concern and provides practical ways to discuss these issues in a variety of subject areas. For the previous post on Truth, click here. This is the first…
Leon Furze
AI development., AI ethics, AI outputs, AI training, algorithmic bias, biased datasets, community needs, data bias, discrimination, environmental impact, ethical concerns, ethical guardrails, facial recognition, Fairness, Justice, predictive policing, responsible AI use, social services, societal biases -
Teaching AI Ethics: Truth and Academic Integrity
This is the third post in a series exploring the nine areas of AI ethics outlined in this original post. Each post goes into detail on the ethical concern and provides practical ways to discuss these issues in a variety of subject areas. For the previous post on Environmental concerns, click here. The concept of…
Leon Furze
AI development., AI ethics, AI outputs, AI training, algorithmic bias, biased datasets, community needs, data bias, discrimination, environmental impact, ethical concerns, ethical guardrails, facial recognition, Fairness, Justice, predictive policing, responsible AI use, social services, societal biases -
Teaching AI Ethics: Environment
This is the second post in a series exploring the nine areas of AI ethics outlined in this original post. Each post goes into detail on the ethical concern and provides practical ways to discuss these issues in a variety of subject areas. For the first post on bias and discrimination, click here. The original…
Leon Furze
AI development., AI ethics, AI outputs, AI training, algorithmic bias, biased datasets, climate, climate change, climate crisis, community needs, data bias, data center, data centre, discrimination, electricity, energy, environment, environmental impact, ethical concerns, ethical guardrails, facial recognition, Fairness, Justice, predictive policing, responsible AI use, social services, societal biases