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📚 Exciting News for Parents and Caregivers! 📚Join us on November 9th from 1-2pm for an empowering training session on Supporting Reading Comprehension In The Home 🏡📖. We understand the importance of helping children with ASD thrive in their reading journey. 🌟In this session, you'll:🔸 Explore the different stages of literacy development.🔸 Gain insights into how ASD affects reading comprehension.🔸 Discover powerful tips and strategies to boost comprehension right at home. 🏠💡Our expert, Susanna Launder, is here to guide you through this enriching experience. For more information, simply drop her an email at slaunder@fau.edu 📧.Let's come together to make reading a joyful and rewarding experience for every child! 📚❤️Register https://FAUCARDReadingComp2023.eventbrite.com#ReadingComprehension #ASD #LiteracyMatters #ParentingTips #EmpowerChildren #EducationForAll #UnlockPotential

Olivia Rothberg: "A Microsatellite Assessment of Southeast Florida's Gopher Tortoise Populations "Committee Chair: Colin Hughes, Ph.D.Committee Members: Evelyn Frazier, Ph.D. , Colin Hughes, Ph.D., and Jon Moore, Ph.D.November 9, 2023 at 2:00 p.m. ESTVirtual via Zoom Contact Chair for details.

Artificial Intelligence, Criminal Justice, and Risk Assessment:The Right to An Explanation Objection to Opaque Recidivism Prediction AlgorithmsRisk assessment tools like COMPAS (Correctional Offender Management Profiling for Alternative Sanction) use sophisticated algorithms to calculate the probability that an offender will commit an additional crime within a certain number of years of the date of the assessment. These calculations are based on information about the offender and their past conduct. Courts and parole boards frequently use such algorithms when making decisions about parole, probation, bail, and even sentencing. The inner workings of these tools remain inaccessible to the defendants whose fate is in part determined by them when the algorithms in question belong to a private corporation (as is the case with COMPAS) or are driven by advanced forms of machine learning that generate unfathomably complex predictive models. In such cases, it seems plausible to conclude that using the algorithms in these ways is morally objectionable because it seems plausible to suppose that defendants have a moral right to receive an explanation of the reasoning that led to the decisions that were made in their cases and that the opacity of such algorithms prevents them from receiving one.In this talk, I will discuss two arguments that have been offered in defense of this right to an explanation objection to using opaque risk assessment tools in these ways. The first maintains that using them for these purposes is analogous to other practices that clearly violate a defendant’s due process rights. The second maintains that using them in these ways violates a requirement of state transparency that is a necessary condition for political legitimacy. I will try to show that both arguments are unsuccessful. In addition, I will offer what I believe to be a novel argument in defense of the claim that defendants do not have a right to an explanation of the reasoning that led to the decisions that were made in their cases about parole, probation, bail, and sentencing. The argument is based on the claim that offenders do not have a right to have jurors explain the reasoning that led to their decision to vote to convict them and that if this is so, then they also lack the right to have courts and parole boards explain the reasoning that led to their decisions about parole, probation, bail, and sentencing. This conclusion about the merits of the right to an explanation objection may prove disturbing, but I will argue that the implications of the alternative position are even harder to accept.

Mathematics of Data ScienceWilliam E. Hahn, Ph.D.Office: Wimberly Library, Room 103 (Sandbox)Email: whahn@fau.eduCourse Objectives/Student Learning Outcomes1. Understand the fundamentals of neural networks and deep learning algorithms2. Learn various methods used to construct, train, evaluate and deploy mathematical models3. Analyze different types of input data including image data4. Utilize Python libraries such as PyTorch for building data science notebooksCourse Number: MAP-2192CRN: 14640Credits: 3 credits

🌟 Join our Independent Living Skills Workshop! 🌟🗓️ Dates: 11/2, 11/9, 11/16, 11/30, 12/7, 12/14 ⏰ Time: 5:00pm - 6:15pm (via Zoom)Are you ready to enhance your independence? Join us for a transformative journey at our upcoming Independent Living Skills Workshop! 🌈 This engaging and interactive workshop will equip you with essential life skills to navigate daily challenges with confidence.🔑 Learn practical skills for: ✅ Budgeting and financial literacy ✅ Time management and organization ✅ Cooking and nutrition tips ✅ Basic home repairs and maintenanceDon't miss out on this incredible opportunity to gain valuable skills that will empower you in every aspect of life. To register or learn more, reach out to Alexzandria May at amay8@fau.edu.📢 Hurry, limited spots available! Reserve your spot today! 📢#EmpowerWithSkills 🚀 #IndependentLivingWorkshopEmbrace the future with confidence! 🌟🏡🕰️

🌟 Exciting Learning Opportunity Alert! 🌟Join us for a transformative experience with "On Their Own: Supporting Independence in Autistic Students Using Activity Systems." 🧩📅 When: All throughout November📌 Where: Online - Accessible anytime!📧 Contact: Mercedes Pagano at paganom@fau.edu 📞 Call: (561)-212-8058In this pre-recorded event, you'll unlock a world of insights:1️⃣ Gain a deep understanding of why activity systems are remarkably effective in nurturing independence.2️⃣ Dive into the research base of the activity system and discover its powerful potential.3️⃣ Learn practical strategies to implement the activity system, fostering independence in the classroom, home, and the community. 🏠🏫🌆Empower yourself with knowledge that can make a real difference in the lives of autistic students. 🧡💙Don't miss this opportunity to make a positive impact! 🌠Register https://pepsasupporting.eventbrite.com