David is arrested for murder. Two police officers are escort…
Questions
Dаvid is аrrested fоr murder. Twо pоlice officers аre escorting David in the back of their police car on the way to the station for questioning. On the drive to the station, one officer says to the other “I sure hope that gun isn’t by the school over there for a small child to find and hurt themself with!” “That would be a shame.” Replied the other officer. “Okay!” cried David. “I’ll tell you where the gun is buried! Just don’t let those poor children get hurt!” David then showed the officers where he buried the gun, which was indeed by a nearby school. The officers then transported David to the station for questioning. Once there, the officers asked David how he murdered his victim and why. At this point, David realized he might be in over his head and said “I think I want my attorney now…” “Do you really?” Inquired the officers. “Maybe…” said David. The officers continued questioning David and he made even more admissions about the murder. David is now on trial for murder. David, through his attorney, seeks to suppress both 1) his admissions regarding where to find the gun as well as the finding of the gun and 2) his further admissions at the police station. You are the judge in this case. Explain how you would rule on both issues. Explain why.
AI Fаilure in Self-Driving Cаr Scenаriо: An AI system cоntrоls a self-driving car. During heavy rain, the car struggles to correctly detect lane markings, causing it to behave erratically.The AI vision module was trained mainly on clear, dry-weather datasets. No real-world rainy conditions were simulated or included in training.10.1. Short Answer: Identify two major machine learning issues that caused the car’s lane detection failure. (Be specific: e.g., generalization error, dataset bias, etc.) (2 points) 10.2. True/False: Give reasoning for your answer. (1 point) Overfitting to dry-weather images is a likely cause of the car's poor generalization during rain. 10.3. Short Answer: (2 points) Suggest one immediate operational mitigation that could be deployed while improving the AI model long-term.10.4. Multiple Choice: (1 point)In a functional safety analysis (ISO 26262 or similar), what would be the risk level of the erratic driving during rain?A) Low Risk — because it's rareB) Medium Risk — because it happens only during rainC) High Risk — because it could cause injury or deathD) No Risk — since the system is autonomous and learns 10.5. True/False: Give reasoning for your answer.(1 point) If the AI fails during rain and causes an accident, liability could potentially fall on the developers who trained the system. 10.6. Essay (8–10 sentences): (3 points) Explainable AI (XAI) refers to a set of methods and techniques that make AI models more transparent and understandable to humans. Describe how Explainable AI (XAI) techniques could be applied to better understand why the lane detection model fails during rain and how this insight could guide safer model updates.