Best Practices for Ethical Data Use in Educational Technology

Guidance for a more Ethical AI 💡This guide, "Designing Ethical AI for Learners: Generative AI Playbook for K-12 Education" by Quill.org, offers education leaders insights gained from Quill.org's six years of experience building AI models for reading and writing tools used by over ten million students. 🚨This playbook is particularly relevant now as educational institutions address declining literacy and math scores exacerbated by the pandemic, where AI solutions hold promise but also risks if poorly designed. The guide explains Quill.org's approach to building AI-powered tools. While the provided snippets don't detail specific tools, they highlight the process of collecting student responses and having teachers provide feedback, identifying common patterns in effective coaching. #Bias: AI models are trained on data, which can contain and perpetuate existing societal biases, leading to unfair or discriminatory outcomes for certain student groups. #Accuracy and #Errors: AI can sometimes generate inaccurate information or "hallucinate" content, requiring careful fact-checking and validation. #Privacy and #Data #Security: AI systems often collect student data, raising concerns about how this data is stored, used, and protected. #OverReliance and #Reduced #Human #Interaction: Over-dependence on AI could diminish crucial teacher-student interactions and the development of critical thinking skills. #Ethical #Use and #Misinformation: Without proper safeguards, AI could be used unethically, including for cheating or spreading misinformation. 5 takeaway #Ethical #Considerations are #Paramount: Designing and implementing AI in education requires a strong focus on ethical principles like transparency, fairness, privacy, and accountability to protect students and promote equitable learning. #Human #Oversight is #Essential: AI should augment, not replace, human educators. Teachers' expertise in pedagogy, empathy, and the ability to foster critical thinking remain irreplaceable. #AI #Literacy is #Crucial: Educators and students need to develop AI literacy, understanding its capabilities, limitations, potential biases, and ethical implications to use it responsibly and effectively. #Context-#Specific #Design #Matters: Effective AI tools should be developed with a deep understanding of educational needs and learning processes, potentially through methods like analyzing teacher feedback patterns.  Continuous Evaluation and Adaptation are Necessary: The impact of AI in education should be continuously assessed for effectiveness, fairness, and unintended consequences, with ongoing adjustments and improvements. Via Philipp Schmidt Ethical AI for All Learners https://lnkd.in/e2YN2ytY Source https://lnkd.in/epqj4ucF

Reading and reflecting on, "The #Ethical Framework for #AI in #Education," from the University of Buckingham, which puts forward a framework to guide procurement and use of AI in education based on consultation across stakeholders. It includes nine objectives and associated criteria and checklist items to maximize the benefits of #AIED and minimize risks. The nine objectives follow. 1. Achieving Educational Goals. AI should be used to achieve well-defined educational goals based on societal, educational, or scientific evidence that this is for the benefit of learners. 2. Broad Forms of #Assessment. AI should be used to assess and recognize a broader range of learners' talents and abilities. 3. Administration and Workload. AI should be used to increase the capacity of organizations while respecting human relationships. 4. Promoting #Equity. AI systems should be used in ways that promote equity between different groups of learners and not in ways that discriminate against any group of learners. 5. Respecting Autonomy. AI systems should be used to increase the level of control that learners have over their learning and development. 6. Balancing #Privacy. A balance should be struck between privacy and the legitimate use of data for achieving well-defined and desirable educational goals. 7. Ensuring Transparency and Accountability. Humans are ultimately responsible for educational outcomes and should therefore have an appropriate level of oversight of how AI systems operate. 8. Informed Participation. Learners, educators, and other relevant practitioners should have a reasonable understanding of artificial intelligence and its implications. 9. Involving Stakeholders in Ethical Design. AI resources should be designed by people who understand the impacts these resources will have. https://lnkd.in/eFvXqgZp

After transitioning from teaching, one major difference became evident: organizations prioritize profit over people. While I understand the necessity for businesses to be profitable, what surprised me was the extent of its implications. In education, where the focus is on students, prioritizing people over profit is foundational. For educators, this principle is ingrained. With the growing presence of AI, it's crucial to pause and ask practical, applicable questions before investing. Seeking professional guidance becomes essential, not just in policy but also in cultivating understanding. From an ethical AI perspective, here are five pertinent questions I'd ask: 1️⃣ How does this AI application mitigate bias and ensure fairness in student evaluations and assessments? 2️⃣ What steps are taken to ensure transparency and accountability in the AI algorithms used? 3️⃣ How is consent given, and what data privacy standards are applied in collecting and utilizing student data? 4️⃣ What measures are in place to continuously monitor and evaluate the performance of systems? 5️⃣ How do you promote collaboration between educators, technologists, and ethicists to ensure AI technologies align with ethical principles and educational goals? It's time to uphold integrity and humanity in the pursuit of educational innovation. #ethicalai #aiineducation #educationalleadership #aiimagegeneration

In recent reflections on the surge of AI within the edtech landscape, an alarming trend becomes evident: the barrier to entry is significantly lower than it was during the Web 2.0 rush of the late 2000s. Unlike the previous era where products were often built from scratch, requiring substantial innovation and development, the core components of AI—such as large language models (LLMs) and comprehensive data sets—are already widely available. This shift means that companies can more easily package these technologies, adorning them with flashy branding and aggressive public relations campaigns, without necessarily contributing foundational innovations to the field. This context magnifies the importance of Ken Shelton's critical questions, as they bring into focus not just the what and how of AI in education, but also the who and why behind these technologies. It urges educators and stakeholders to: 1️⃣ Examine Data Sets and Supervision: What data sets does your organization use? Do these data sets bear labels, and are they supervised? The integrity and bias of data sets underpin the outcomes AI technologies produce, making transparency around these elements non-negotiable. 2️⃣ Scrutinize Diversity in Design: How does your design and decision-making team's diversity reflect the multifaceted identities of our student body? The perspectives and experiences of those creating AI solutions must resonate with, and reflect, the diversity of those impacted by these technologies. Understanding to what extent these teams' lived experiences align with our students' realities is crucial in creating equitable educational tools. 3️⃣ Question Impact and Transformation Goals: What impact does your organization aim to achieve within the education sector? Beyond mere functional contributions, how do your efforts seek to challenge and transform existing norms? A critical examination of how these technologies plan to dismantle historical and institutional barriers is imperative. In the fast-evolving AI landscape, the ease of entry underscores the necessity for vigilance, not mere skepticism. Ken Shelton's critical questions serve as essential due diligence, ensuring we embrace new AI technologies with informed enthusiasm. These inquiries help us discern genuine educational advancements from mere novelties, guiding us towards solutions that are equitable, inclusive, and truly transformative. By demanding clarity on data integrity, team diversity, and impact, we advocate for a future where technology aligns with our educational values and goals. #ai #aiethics #edtech #education #innovation #vigilance #educationalequity #criticalthinking #digitalcitizenship

There are already hundreds of new Generative AI Edtech companies and products on the market. Some great, some terrible and many in-between. So how can you vet GenAI EdTech companies to ensure that their product is safe, reliable, effective, and fit-for-purpose? To help we've put together our Top Six Questions to guide these conversations. You can download the PDF version and get the reasons "why" for each questions at this link: bit.ly/3qnP0ma. 1️⃣ We know that generative AI (GenAI) is a new technology with extensive limitations. How does your product indicate when it's uncertain or requires human review? What controls do you have in place to identify and lower hallucinations?   2️⃣ It’s important that the tools we use do not cause harm to our students or teachers. What steps are you taking to identify and mitigate biases in your AI models? How will you ensure fair and unbiased outputs? 3️⃣ Protecting student data privacy and ensuring ethical use of data is a top priority for our school. What policies and safeguards can you share to address these concerns? 4️⃣ Our educators need to validate and trust AI-generated content before use. What human oversight and quality control measures do you use? How do you ensure feedback from teachers/students is being collected and actioned? 5️⃣  We need evidence that your AI tool will improve learning outcomes for our student population and/or effectively support our teachers. Can you provide examples, metrics and/or case studies of positive impact in similar settings? 6️⃣ : Our school needs to accommodate diverse learners and varying technical skills among staff. How does your tool ensure accessibility and usability for all our students and staff? What PD is available? AI for Education #genai #edtech #aiforeducation #schoolleaders #AI

Defining a framework for HigherEd Policy for Teaching & Learning Transformational advances in AI have created an urgent need for students to be prepared for a data- and AI-driven world. Simultaneously these tools have the potential to transform higher ed from a “one-size fits all” place- and time-driven archaic system to a modern, personalized, highly accessible, engaged, and agile knowledge enterprise enabling learning at scale. However, the rapid evolution of these tools and technologies has left academia behind as related to processes, norms, and policies as related to the use of AI in teaching and learning, as well as in the consideration of aspects such as plagiarism, original thought, attainment of competency in a subject/discipline and assessment of performance. Between the two extremes of doing nothing and blindly embracing AI as a panacea for all of HigherEd’s ills, there is an increasing need for the establishment of institutional-level policies for the development, implementation, and use of AI tools/platforms for teaching and learning. However, it is important that any #framework for development and implementation of AI in #HigherEd start with the basic consideration of #ethics, #responsibility, and #equity. From a systems perspective, #ethicalAI provides the values, principles, and foundations; #responsibleAI ensures use of tactics that meet those guidelines; and #equitableAI assures the implementation of strategy for the benefits of AI to accrue to all learners, both in terms of gaining access to knowledge and in enabling its use for #socioeconomic mobility. Building on a foundation of these three levels, and once the purpose of AI has been determined in the context of the specific type of institution and the nuances of the learner population that is intended to be served, a framework for higher-ed policy can be developed using the four pillars of (1) #governance, (2) #ethics and #accountability, (3) #pedagogy, and (4) #operations. The prioritization enables emphasis to be on the specific context of the institution through governance, as well as the nuances of mission and the local context in which the tools would operate through pedagogy. The article published in eCampus News provides a framework for this based on foundations in ethical, responsible and equitable AI. #Innovation #AI #HigherEd #Framework #Policy #Teaching #Learning

AI: A Clearer Path to Early Intervention and Student Success The U.S. Department of Education’s recent guidance on the responsible use of artificial intelligence (AI) is a welcome and timely signal to the education community: Innovation and equity must go hand in hand. At Navigate360, we share this vision—where AI is used not to replace people, but to empower them. Where data isn't used to label students, but to lift them. For too long, the fragmented nature of school safety, wellness, and behavioral systems has hindered our ability to act early, connect the dots, and intervene before concerns escalate. That’s why Navigate360 has invested in building a unified platform that gives schools and districts comprehensive visibility into early concerning behaviors and other key risk indicators. By responsibly integrating AI into our NavigateOne platform, we help educators: 1. Identify students in need of additional support through predictive analytics that consider academic patterns, behavior trends, attendance, and other risk signals. 2. Connect siloed data points like changes in peer relationships, online activity patterns, or escalating behaviors into a clearer picture of a student’s needs. 3. Equip school staff with alerts, insights, and tools that support timely, compassionate, and effective intervention—without increasing administrative burden. This is not about surveillance. It’s about situational awareness. It’s not about punishment. It’s about prevention and support. The Department’s affirmation that AI-powered tools are allowable under federal formula and discretionary grant programs opens a door for school leaders to pursue solutions that align with their mission to educate and protect every student. It’s also a reminder that any AI initiative must be rooted in transparency, equity, and educator empowerment. We applaud this leadership and are committed to helping schools navigate the path forward—ethically, responsibly, and with the clear goal of ensuring every learner feels safe, seen, and supported. Let’s continue to lead with empathy, act with urgency, and use the best of technology to elevate the best in people. #AI #SchoolSafety #ZeroIncidents #PreventionFirst

Exciting news! 🚀 This week, Washington became the fifth state to unveil a strategy for integrating AI into public schools. 🙌 Here's why I think this sets a great precedent for other states/countries: 🤖 Human → AI → Human: Students and educators are encouraged to always begin with human inquiry, apply AI tools, and then evaluate and edit results. Focusing the narrative on human-centered approach ensures we maintain the integrity of the learning experience. 🚀 Empowering Future Innovators: AI is here to stay. This initiative encourages the embedding (vs. banning) of ethical AI use in K-12 education. This ensures students are not just passive users but informed creators and critics of AI technologies, ready to navigate a future where AI is likely much more ubiquitous. 🛡️ Data Protection & Privacy: Prioritizing the safety and privacy of student data is a big piece of AI adoption and literacy. We will never be able to establish trust among educators and parents in AI unless we ensure that student information is safeguarded. Arguably the EU is ahead of the US in this regard but it’s great to see data privacy is becoming an important part of the conversation in the US as well. 🌍 Equity and Inclusion in AI: There already are huge gaps in accessibility to meaningful AI education and so I appreciate multiple callouts in the document to ensure AI education is accessible to every student, breaking down barriers and promoting inclusivity. 🚀 Professional Development for Educators: The initiative recognizes the importance of empowering teachers with the knowledge and tools to effectively integrate AI into their teaching practices. 🤔 Critical Thinking and AI Ethics: Students are encouraged to engage with AI critically, understanding the algorithms and data that power these technologies. There are real risks and biases that come with GenAI and so it’s great to see that students are encouraged to question (and shape) the impact of AI on society. 📈 Real-World Applications: It's important to remind students that despite risks there are real positive use-cases of these technologies. And hopefully getting them excited to use GenAI meaningfully in their careers. 💡 Creative Problem Solving: By understanding AI's capabilities, students are equipped to leverage technology for creative innovation. This focus on creativity ensures that the next generation is ready to use AI in novel ways (that the non-AI natives might not think of). 👨🏫 Community Engagement and Support: Parents, families, and the wider community need to be involved in understanding AI's role in education. This inclusive approach ensures a collective effort in navigating the AI landscape. AI literacy is what we stand for at ai LaMo so huge kudos to Office of Superintendent of Public Instruction and Chris Reykdal for championing such a visionary approach! #EdTech #AIineducation #WashingtonState #GenAI #education #edtechstartup