4.4 Health Questionbank

Source A

Source B

It is a paradox to brand a technological innovation as tainted goods by its very name. ‘Deepfake’ is a victim of its own capabilities. Negative connotations and recent incidents have pigeonholed this innovation in the taboo zone. The rise of deepfake technology has ushered in very interesting possibilities and challenges. This synthetic media, created through sophisticated artificial intelligence algorithms, has begun to infiltrate various sectors, raising intriguing questions about its potential impact on education and employability.

The dawn of deepfake technology introduces a realm of possibilities in education. Imagine medical students engaging in lifelike surgical simulations or language learners participating in authentic conversations. The potential for deepfake to revolutionise training scenarios is vast and could significantly enhance the educational experience. Beyond simulations, deepfake can transport students to historical events through realistic reenactments or facilitate virtual field trips, transcending the boundaries of traditional education. The immersive nature of deepfake content holds the promise of making learning more engaging and memorable.

Source C

However, while these potential abuses of the technology are real and concerning that doesn't mean we should turn a blind eye to the technology’s potential when using it responsibly, says Jaime Donally, a well-known immersive learning expert.

“Typically, when we're hearing about it, it's in terms of the negative – impersonation and giving false claims,” Donally says. “But really, the technology has the power of bringing people from history alive through old images that we have using AI.”

Donally, a former math teacher and instructional technologist, has written about how a type of deep fake technology called deep nostalgia technology that went viral in 2021 can allow students to form a stronger connection with the past and their personal family heritage. The technology, available on the MyHeritage app, allows images to uploaded that are then turned into short animations thanks to AI technology.

Here are some of the ways in which teachers can utilize deep fake technology in the classroom utilizing the MyHeritage app. Teachers have used the deep fake technology in the My Heritage app to bring historical figures such as Amelia Earhart and Albert Einstein to life. One teacher Donally has communicated with used an animation of Frederick Douglass (above) to help students connect with Douglass’ famous 1852 speech about the meaning of the Fourth of July to Black enslaved Americans. Another teacher has plans to use the app to have students interview a historical figure and create dialogue for them, then match the dialogue to the animation.

Donally herself has paired animations she's created with other types of immersive technology. “I layered it on top in augmented reality,” she says. “When you scan the photo of my grandfather, it all came to life. And it became something that was much more relevant to see in your real-world space.”

With proper supervision, students can use the technology to animate images of family members or local historical figures, and can experiment with augmented reality (AR) in the process. “It makes you want to learn more,” Donally says of animations created using deep fake technology. “It drives you into kind of the history and understanding a bit more, and I think it also helps you identify who you are in that process.”

Source D

Education platforms are harnessing deepfake technology to create AI tutors that provide customised support to students. Rather than a generic video lecture, each learner can get tailored instruction and feedback from a virtual tutor who speaks their language and adjusts to their level.

For example, Anthropic built Claude, an AI assistant designed specifically for education. Claude can answer students’ natural language questions, explain concepts clearly, and identify knowledge gaps.

Such AI tutors make learning more effective, accessible, and inclusive. Students feel like they have an expert guide helping them master new skills and material.

AI and deepfake technology have enormous potential to enhance workforce training and education in immersive new ways too. As Drew Rose, CSO and founder of cybersecurity firm Living Security, explains, “educators can leverage deepfakes to create immersive learning experiences. For instance, a history lesson might feature a ‘guest appearance’ by a historical figure, or a science lesson might have a renowned scientist explaining complex concepts.” Ivana Bartoletti, privacy and data protection expert at Wipro and author of An Artificial Revolution – On Power, Politics and AI envisions similar applications.

“Deepfake technologies could provide an easier and less expensive way to train and visualise,” she says. “Students of medicine and nursing currently train with animatronic robots. They are expensive and require special control rooms. Generative AI and augmented or virtual reality headsets or practice rooms will be cheaper and allow for the generalisation, if not the gamification, of simulation.”

Medical students could gain experience diagnosing and treating simulated patients, while business students could practice high-stakes scenarios like negotiations without real-world consequences. These immersive, gamified environments enabled by AI and deepfakes also have vast potential for corporate training.

Bartoletti notes, “A similar use case could be made for other types of learning that require risky and skill-based experiences. The Air Force uses AI as adversaries in flight simulators, and humans have not beaten the best AIs since 2015.

In healthcare, algorithms are employed for predictive diagnostics by analyzing patient data to predict diseases or suggest treatments. While these algorithms can increase efficiency, a lack of transparency and accountability in cases of misdiagnosis or bias raises ethical concerns.

Source A: The Importance of Data Storage and Memory in Computers

Data storage (like hard drives and SSDs) holds files permanently, while memory (RAM) stores temporary data, supporting the computer’s processing needs. Effective storage and memory are critical to speed and multitasking abilities in devices from smartphones to mainframes.

For example, an SSD in a laptop allows fast data retrieval, boosting performance for tasks like video editing and gaming.

Source B: Wearable Devices: Integrating Computers into Daily Life

Wearable computers, such as smartwatches and fitness trackers, integrate technology into daily life, providing health monitoring, communication, and real-time data tracking. These devices are lightweight and adaptable, making them practical for continuous use.

For instance, a smartwatch can monitor heart rate, track physical activity, and send alerts, helping users maintain their health goals.

Source C: The Impact of Moore’s Law on Technology Progression

Moore’s Law states that the number of transistors in a microchip doubles approximately every two years, boosting processing power. This principle has driven computing advancements, leading to smaller, faster, and more efficient devices.

For example, Moore’s Law facilitated the evolution from bulky desktop computers to powerful smartphones that fit in a pocket.

Source D: Haptic and Graphical User Interfaces in Computing

User interfaces (UIs) allow people to interact with computers. Graphical user interfaces (GUIs) use icons and visuals to make navigation intuitive, while haptic interfaces provide touch feedback, enhancing the tactile experience in applications like gaming and virtual reality.

For example, smartphones combine haptic feedback with touchscreens, making interactions more intuitive for users.

Voice simulation

Lyrebird voice-cloning software was created by three university students from Montreal. This technology was originally developed to change the lives of people who have lost their voice. These people can use the software to create a new voice by choosing one from samples provided in the software.

However, Lyrebird can also clone voices. Lyrebird claims that it can clone a person’s voice in just 60 seconds. Users only need to access the website, create an account, and generate a voice print by repeating a number of predetermined sentences. Although the cloning is not perfect, the developers of Lyrebird believe that both the time to clone the voice and the quality of the cloning will improve in the future.

The software allows the user to alter the speech and add emotion (such as, anger, elation, and surprise), increasing the ways in which it can be used.

The initial voice print for the cloning process requires the most time and a lot of processing power. However, creating speech from the voice print is a simple process, generating around 1000 sentences almost instantly. The voice print is saved as a compressed audio file.

Lyrebird has considered the ethical issues regarding biometrics* and acknowledges that it highlights some key societal issues. Lyrebird has taken the decision to make the software available to all in an attempt to address these issues.

* biometrics: a means of personal identification through analysis of unique physical traits or behavioural characteristics (for example, through voice patterns or fingerprints)

Source A

Source B Through this article today, we are here to share with you the various challenges in the internet of things. Security challenges- The first and foremost on the list of challenges is security. As the backbone of IoT is data storage and sharing, the biggest question arises about the security of data. Enabling every small physical object with the feature of sharing information may attract multiple raised brows. Lack of encryption- Encryption sounds like the ultimate answer to security issues. But hackers may manipulate these algorithms and turn a protective system into the most serious loophole. Lack of sufficient testing and updating- With the increasing market of IoT, production has to be faster. To compete in the race of production, manufacturers lack tests and updates. The main focus of IoT manufacturers now seems to be production, not security. Thus products lack proper and regular testing and updates. This makes IOTs prone to being attacked by hackers.

Source C A smart home is a household with internet-connected appliances you can remotely control using a tablet or smartphone. It uses smart devices such as smart TVs, smart thermostats, air conditioners, and even a robot vacuum. They are then connected together in a single network, through either hardwired or wireless systems like Zigbee, Wi-Fi, Bluetooth, and NFC, among others. Using the Internet of Things (IoT) technology, your smart appliances can communicate and share real time data with each other. This allows the devices to perform scheduled and automated tasks. IoT home gadgets bounce data back and forth with the use of sensors, learning and processing your patterns to automatically adjust themselves to your comfort. Some smart home Internet of Things applications are automatic light switches, burglar alarms, and voice-activated sound systems.

Source D A tired business person returns to their certified IoT smart home after a long working week. The smart security system senses they are alone and initiates the “Friday Night In” sequence. An intercom with a thoughtful, comforting voice suggests they might want to order in tonight. The business person unloads their things in the kitchen where the smart stove displays a selection of take-outs, rather than its default recipe guide. After the food arrives they retreat to the living room to watch some TV. The smart TV prepares a selection of Netflix marathons categorized by mood. They choose: “Looking to be cheered up? Comedy Playlist.” Before starting the program, they review a set of graphs displaying the data from their activity and diet throughout the day. A list of tips for smart living is generated, one of which reads that based on the number of consecutive nights spent alone, they might consider exploring a selection of popular dating sites instead of watching TV. With an inadvertent slip of their thumb the request is OK’d and instantly a set of profiles are displayed, each chosen from a generated list of their tracked preferences. A flurry of pings and messages from other stay-at-home hopefuls fills the screen. The smart home intercom exclaims, “You’ve got mail!” The confused and beleaguered business person fumbles for the remote and… uh-oh, the TV snaps a selfie in response to the flood of pings. Their image, sitting in their underwear eating noodles appears briefly on the screen before being whisked off into the ether. The flood of messages doubles, the system freezes causing the smart home to reboot. The house goes dark.

Google health care data

Google is developing an app to assist hospitals in monitoring kidney disease in patients. To develop this app, Google has signed an agreement with the UK’s National Health Service (NHS) that will give Google access to data on over one and a half million patients held in the NHS database.

The database includes health-related data as well as personal data, some of which is sensitive.

Google plans to use data analytics techniques and artificial neural networks (ANNs) to analyse the data and provide information that can be used to improve the app. Once the app has been developed, it will be provided to the NHS.

Human genome research

MediResearch, a US-based DNA testing company, has a relational database of human genome information. An individual’s genome data represents private information about their past, their present and, potentially, their future. This information is stored in a relational database.

The senior managers at MediResearch are considering using data analytics but are concerned this may compromise the anonymity of the individuals who have provided their DNA.

Source A: The Black Box Problem: Algorithmic Transparency and Accountability

Many complex algorithms, particularly those used in machine learning, operate as ""black boxes,"" meaning their decision-making processes are not easily understood. This lack of transparency and accountability raises ethical concerns, especially when algorithms impact individuals' lives in areas like credit scoring or criminal justice.

For example, an algorithm used for credit scoring may make decisions without revealing the factors it considered, leading to a lack of accountability.

Source B: Erosion of Human Judgment in Algorithmic Decision-Making

The rise of algorithmic decision-making can lead to a loss of human judgment, especially in areas where subjective understanding is crucial, like healthcare or social services. Over-reliance on algorithms may result in decisions that overlook nuanced human factors.

For instance, a diagnostic algorithm in healthcare might misinterpret symptoms that a human physician could recognize due to experience or intuition.

Source C: Algorithm Efficiency: Measuring Time and Space Complexity

Algorithm efficiency is critical, especially in processing large datasets. Efficiency is measured by time complexity (how fast an algorithm runs) and space complexity (how much memory it uses). Balancing these aspects is essential in applications that require speed and performance, like data processing in finance.

For example, financial trading algorithms are optimized to make quick, efficient decisions based on market data to execute trades faster than human traders.

Source D: Algorithmic Filtering and Prioritization in Social Media

Social media platforms use algorithms to filter and prioritize content, often shaping users' experiences and the information they see. These algorithms analyze user data to decide which posts appear first, influencing what trends, news, and advertisements are visible to each user.

For example, a social media algorithm might prioritize posts from close contacts and trending news topics to keep users engaged.