Case study: A state health system deploys AI-driven personalized medicine for diabetes care. Patients opt in to share electronic health records, continuous glucose monitor data, and lifestyle surveys. The AI model predicts which medication plan is most likely to stabilize blood sugar and sends clinicians alerts when a patient’s readings suggest elevated risk.

Benefits: The program reduces preventable hospitalizations by catching problems earlier, and it supports overworked clinics by prioritizing high-risk patients. Patients in remote areas receive more consistent follow-up through telehealth. A 2023 U.S. government advisory notes that health AI can improve efficiency when used with human oversight and clear evaluation.

Harms: Centralizing sensitive health and sensor data increases the consequences of a breach. Even de-identified datasets can sometimes be re-identified by combining them with other information. Ethical concerns also arise: if an insurer or employer gains access, predictions could be used to discriminate, so strict access controls matter. The system occasionally recommends a plan that conflicts with a clinician’s judgment because it learns patterns that do not reflect a patient’s unique context, underscoring limits of data-driven inference.

Based on the case study, which statement best summarizes the dual impact of AI-driven personalized medicine in the passage?

Case study: A school district adopts a social media platform-style app for announcements, student clubs, and parent-teacher messaging. The app’s feed is curated by a recommendation algorithm (a set of rules learned from data) that promotes posts likely to get reactions. It offers translation and automatic captioning, helping multilingual families and students with hearing differences. Teachers post homework reminders, and emergency alerts reach phones immediately.

Benefits: Communication improves: parents who work multiple jobs can still message teachers asynchronously, and clubs recruit members quickly. Pew Research Center surveys consistently show a large majority of U.S. teens use social media, so the district meets families where they already communicate. Rapid updates reduce missed assignments and improve attendance at events.

Harms: The same engagement-focused design can amplify misinformation and rumor, because sensational posts often get more reactions. Researchers link heavy social media use to mental health concerns for some adolescents, including sleep disruption and anxiety, though effects vary by individual. The district also learns that the vendor collects behavioral data (clicks, time spent) to personalize content, raising privacy issues, especially for minors. A student-created false account spreads a fabricated “school closure” post, causing confusion and missed class.

Considering the described technology, in what ways does the school’s social-media-style app improve and challenge societal norms as mentioned in the passage?

Case study (Artificial Intelligence in Healthcare, ~505 words): A regional hospital system deploys an AI tool called ScanAid to help radiologists review chest X-rays and CT scans. ScanAid uses machine learning, meaning it learns patterns from large sets of labeled medical images to estimate the likelihood of conditions such as pneumonia or a collapsed lung. When a new scan arrives, the system highlights areas it deems suspicious and assigns a risk score. The hospital integrates ScanAid into its workflow so that high-risk cases move to the front of the review queue.

The benefits appear quickly. In the emergency department, clinicians receive faster preliminary flags, which helps prioritize patients who may need urgent treatment. Administrators report shorter average turnaround times for imaging results, and radiologists say the tool reduces “missed findings” on busy nights by acting as a second set of eyes. This aligns with real-world momentum: the U.S. Food and Drug Administration has authorized hundreds of AI-enabled medical devices, many aimed at imaging, reflecting a broad belief that computing can improve efficiency and decision support.

Yet the hospital also confronts serious risks. ScanAid requires large quantities of patient data for training and ongoing monitoring. Even if names are removed, data can sometimes be re-identified when combined with other information, raising privacy concerns. The system’s vendor stores model updates in the cloud, and a security audit warns that misconfigured access controls could expose sensitive scans. In addition, clinicians discover performance gaps: the tool flags fewer abnormalities in patients from a smaller rural clinic that uses older imaging machines. A quality team suspects the training data underrepresents those machine types, a form of algorithmic bias (systematic error that disadvantages certain groups or settings). Finally, some physicians worry about “automation bias,” where staff may over-trust a computer’s score and overlook contradictory clinical evidence.

The hospital responds by requiring human sign-off on all diagnoses, conducting bias tests across equipment types, and encrypting data in transit and at rest. Still, leaders acknowledge that the same computing innovation that boosts speed and consistency also introduces new ethical dilemmas around data security, fairness, and accountability.

Based on the case study, what are two benefits and two risks associated with AI diagnostics as described in the passage?

Case study (Cloud Computing): A mid-sized architecture firm moves from on-site servers to a cloud provider to store design files and run rendering software. Cloud computing means the firm rents computing power and storage over the internet, scaling up during deadlines and scaling down afterward. Employees collaborate in real time on shared models, and the firm uses automated backups across multiple data centers. According to a 2023 Flexera report, a large majority of organizations use public cloud services, reflecting how common this shift becomes. The firm also adopts cloud-based email and video meetings, enabling remote work for employees who live far from the main office.

Benefits: Managers cite cost reduction because they avoid purchasing new servers every few years. Project teams share large files quickly with clients, and version history reduces mistakes from emailing outdated attachments. During a heat wave that causes a local power outage, staff continue working from home because the cloud services remain available.

Harms: The dependency on the provider creates vulnerabilities. A misconfigured access setting exposes a folder of client blueprints, raising confidentiality concerns. When the provider experiences an outage, the firm cannot access key files for several hours, delaying a deadline. The firm also faces “vendor lock-in”: switching providers would require time-consuming data migration and retraining. Considering the described technology, how does cloud computing positively and negatively impact society according to the passage?

Case study (Cloud Computing): A community college migrates its learning management system (LMS) and student email to a cloud vendor. The LMS hosts assignments, discussion boards, and grades; cloud hosting means the vendor manages servers, updates, and storage while the college pays a subscription. During midterms, the system automatically scales to handle heavy traffic. Many institutions adopt similar services; EDUCAUSE surveys routinely report widespread reliance on cloud-based academic tools.

Benefits: Students access course materials from any device, and instructors post feedback quickly. The IT department spends less time replacing hardware and more time supporting teachers. Automatic updates patch known vulnerabilities faster than the college’s previous manual process.

Harms: The college becomes dependent on the vendor’s uptime; when a regional outage hits the vendor, students cannot submit assignments for hours. A misconfigured permission setting briefly exposes a folder containing advising notes, raising privacy concerns under student data protections. The subscription cost also increases after the first contract period, and switching vendors would require migrating years of courses. Which statement best summarizes the dual impact of cloud computing in the passage?

Case study (Smart Devices): A city installs “smart” streetlights with motion sensors and networked controllers. The lights dim when streets are empty and brighten when pedestrians or cars approach, aiming to reduce energy costs. A central dashboard collects status data (bulb health, power usage) and sends maintenance alerts. Similar systems appear in many municipalities as part of smart-city initiatives, and vendors often claim measurable energy savings from adaptive lighting.

Benefits: The city reports lower electricity bills and quicker repairs because crews replace failing lights before outages occur. Residents also report feeling safer on well-lit routes that brighten as they walk.

Harms: The networked design introduces new security risks: if attackers access the control system, they could disrupt lighting patterns. Privacy concerns arise because motion data, while not always personally identifying, can still reveal patterns of movement in specific neighborhoods. The city also becomes reliant on the vendor for software updates; when support is delayed, known vulnerabilities remain unpatched longer than desired. Considering the described technology, what are two benefits and two risks associated with smart devices as described in the passage?

Case study (Artificial Intelligence in Healthcare): A primary-care chain uses an AI chatbot to draft responses to patient portal messages and to suggest whether symptoms warrant urgent care. The chatbot is trained on large text datasets and clinic guidelines; it generates likely next steps, but nurses review messages before sending them. The chain adopts the tool to reduce response backlogs and to offer 24/7 guidance. Studies in medical informatics often find that automation can reduce administrative burden, though accuracy and safety require oversight.

Benefits: Patients receive faster replies and clearer instructions, and clinicians spend more time on complex cases. The system also translates messages for patients with limited English proficiency, improving access.

Harms: The chain faces privacy and security challenges because the chatbot processes sensitive health details. A staff member accidentally pastes identifiable information into an external testing environment, creating a data exposure incident. Clinicians also note that the chatbot sometimes produces confident but incorrect suggestions (a “hallucination,” meaning plausible-sounding output not grounded in facts), so overreliance could harm patients. Based on the case study, what are two benefits and two risks associated with AI in healthcare as described in the passage?

Case study (Smart Devices): A suburban family installs a smart home system: a thermostat that learns schedules, smart speakers that respond to voice commands, and connected door locks and cameras controlled by a phone app. These devices rely on sensors, wireless networking, and cloud services that process voice recordings and video clips. The thermostat uses past temperature adjustments to predict comfort preferences, and the family receives monthly energy reports. Industry surveys frequently estimate tens of billions of connected “Internet of Things” devices worldwide, indicating widespread adoption.

Benefits: The family lowers energy use by automatically reducing heating when no one is home. The door camera helps deter package theft, and elderly grandparents use voice reminders for medication. Remote control features increase convenience, especially when traveling.

Harms: The same connectivity introduces security and privacy concerns. A weak reused password allows an attacker to access the camera feed, and the family worries about who can hear stored voice recordings. A service outage temporarily disables app-based door controls, forcing the family to use physical keys. The devices also generate detailed behavioral data—when people come home, what rooms they use—which could be misused if shared with third parties. In what ways does smart home technology improve and challenge societal norms as mentioned in the passage?

Case study (Artificial Intelligence in Healthcare): A regional hospital network deploys an AI system to assist radiologists in detecting early signs of lung cancer on CT scans. The innovation uses machine learning, meaning the software learns patterns from thousands of labeled images and then estimates the probability that a new scan contains suspicious nodules. The hospital integrates the tool into its workflow: the AI highlights areas of concern, and a clinician makes the final diagnosis. A 2023 U.S. FDA announcement notes a growing number of AI-enabled medical devices cleared for clinical use, reflecting real-world adoption. The network also pilots a personalized-medicine feature that combines lab results, medication history, and wearable data (like heart rate trends) to recommend follow-up tests.

Benefits: The hospital reports shorter wait times for scan reviews and more consistent “second-look” screening in busy weeks. In one month, the AI flags subtle nodules that a fatigued overnight team might miss, enabling earlier follow-up for several patients. Administrators note efficiency gains: fewer repeat scans, faster triage, and improved access for rural clinics that can upload images for review.

Harms: The same system introduces risks. Because it requires large datasets, the hospital stores sensitive imaging and health records in a centralized repository; a ransomware attempt forces the network to temporarily disconnect systems, delaying non-urgent appointments. Ethical concerns also emerge: the training data underrepresents certain demographic groups, and clinicians worry the model may be less accurate for them (algorithmic bias, meaning uneven performance across groups). Finally, some staff fear “automation complacency,” where clinicians may over-trust the AI’s highlights and overlook unmarked abnormalities. Based on the case study, what are two benefits and two risks associated with AI in healthcare as described in the passage?