Artificial Intelligence in Practice

Artificial Intelligence in Practice

• AI represents technologies enabling computers to perform advanced functions.
• These functions include understanding language, data analysis, and making recommendations.
• Machines perform tasks automatically, reducing the need for human supervision.

AI in Real Life Applications

• AI is revolutionizing healthcare through enhanced accuracy and efficiency in diagnostics.
• It facilitates personalized treatment plans and virtual health support
• The financial industry is being transformed by AI, particularly in fraud detection.
• AI optimizes trading strategies and personalizes financial services.
• Education benefits from AI through personalized learning experiences.
• AI automates administrative tasks and enhances educational tools.
• Improvements to crop monitoring and precision farming are ways AI is revolutionizing agriculture.
• AI enhances security with advanced threat detection as well as improved surveillance .
• AI transforms transportation with better traffic management and autonomous driving.

Key Applications of AI in Healthcare

• AI analyzes medical images like X-rays, MRIs, and CT scans to assist healthcare providers in diagnoses.
• AI algorithms identify tumors with high accuracy, facilitating early detection.
• AI aids in identifying markers for diseases such as cancer, cardiovascular issues, and neurological disorders.
• Predictive analytics utilizes historical and real-time data to foresee health outcomes and potential risks.
• AI modelscan predict patients at risk of hospital readmission.
• AI anticipates disease outbreaks by assessing patterns from sources like hospitals and public health records.
• Personalized treatment plans are suggested via AI analysis of patient data.

Key Applications of AI in Finance

• Utilizes machine learning to detect fraudulent activities within large datasets.
• Training algorithms identify fraud patterns as well as anomalies.
• Machine learning models enhance predictive accuracy and adapt to fraudulent strategies
• AI in education also works through language-learning platforms like Duolingo by integrating smart bots

Key Applications of AI in Education

• Duolingo's language-learning application is an AI-based learning platform.
• Duolingo integrates a smart bot to interact with students, like its cheerful, green owl mascot.
• Duolingo has an initial positioning test to scan user skills.
• There is a progressive readjustment of activity difficulty based on performance and results achieved.
• The goal is to maintain an optimal level of challenge, keeping learners engaged with a points-based reward system.
• Century Tech's AI platform uses cognitive neuroscience and data analytics to create customized learning plans that enhance the educational experience.
• Platforms monitor student progress, identify knowledge gaps, and provide personalized study recommendations.
• This provides support to teachers to reduce the time spent on grading, freeing them for other tasks.

Key Applications of AI in Agriculture

• Crop yield as well as price forecasts help the farmer obtain maximum profit
• AI sensors can detect weed-affected areas and precisely spray herbicides to reduce herbicide usage.
• AI provides insights on the optimal time to sow seeds for maximum productivity.
• Autonomous robots harvest large crop volumes at a faster pace.
• Machine learning/AI can monitor crop health as well as diagnose pests,soil defects and nutrient deficiencies.
• Prior information and classification of plant diseases will assist farmers in controlling the disease for a proper strategy.

Key Applications of AI in Transportation

• Predictive maintenance enables early detection of potential issues in vehicles, preventing costly breakdowns and extending lifespan.
• AI-powered chatbots enhance customer service by providing instant responses, improving customer satisfaction and efficiency.
• Autonomous vehicles, improve road safety and reduce traffic congestion.
• Insurance fraud is detected through AI, helping to monitor and analyze driver behavior to improve safety.
• Flight delays cab be predicted, improving urban mobility, in addition real-time vehicle tracksing can provide insight here
• Al can also improve Intelligent Driver Care can also monitor safety concerns for drivers and make corrections proactively .

Key Applications of AI in Security

• AI security cameras distinguish between natural elements, vehicles, animals, and humans.
• Alerts are only sent for actual intruders, avoiding alerts from tree shadows or lights.
• AI license plate recognition(LPR) has the capacity to capture digital information from images or videos
• AI can automatically manage billing for vehicles in parking scenarios
• LPR identifies expired registrations when a license plate is scanned, enabling notifications or enforcement actions.

Influence of Human Information Behavior on AI

• Human information behavior refers to how people seek, use, and share information.
• Key aspects include information seeking, use, and sharing.
• AI systems rely heavily on human-generated data for training and functioning.
• Understanding the influence of human information behavior is crucial for developing ethical AI.
• Information seeking is the process of actively searching for information to fulfill a specific need.
• Information seeking is using search engines, databases, or libraries to find information.
• Information seeking also comes from expert peers, or social networks.
• Browsing news websites to stay updated is another option.
• Information use is interpreting, analyzing, and applying the acquired information to achieve something specific.
• Information sharing is distributing or disseminating information to others such through conversations, blogs and collaboration

Data Collection and Quality

• Human-generated data is the foundation for AI training.
• The quality and accuracy of this data affect AI performance, leading to better outcomes overall.
• Data quality is the ability of a dataset to serve an intended purpose.
• If the data is of poor quality, there is a problem which will not help achieve goals.

Data Quality Pillars

• Accuracy is how correct the data is.
• Completeness is the presence of all needed data.
• Uniformity of data across systems is consistency, the availability and relevancy of data is timeliness.
• Conformance to rules and standards is validity; and no duplicate records is uniqueness

Bias in AI Systems

• AI inherits biases present in human-generated data.
• Types of bias include selection, confirmation, measurement, stereotyping, and out-group homogeneity bias.
• Selection bias occurs when the data used to train an AI system is not representative, and confirmation bias happens when an AI system is tuned to rely too much on pre-existing beliefs in the data.
• Measurement bias occurs when the data collected differs systematically from the actual variables of interest.
• Stereotyping bias occurs when an AI system reinforces stereotypes, while outgroup homogeneity bias occurs when an AI system is less capable of distinguishing between those who are not part of the majority group.

Enhancing AI with Positive Human Influence

• Ensure diverse data collection, promote ethical practices, and maintain transparency.
• Collect data from origins, geographic locations, demographic groups, and types of data.
• Adhere to principles and standards to ensure that AI development and deployment respect human and societal values.

Advantages of Artificial Intelligence

• Automation enhances business processes by minimizing manual tasks and boosting operational efficiency.
• Al-powered chatbots handle customer inquiries, providing responses.
• Al predictive maintenance in manufacturing reduces downtime by scheduling repairs based on real-time data.
• AI reduces human error by automating processes as well as ensuring accuracy through machine learning. AI enhances decision-making by analyzing data in order to make more informed decisions AI personalizes customer experiences, tailors recommendations, enhances engagement,and increased loyalty.
• AI ensures continuous support and services for operational efficiency during all hours of operation
• AI enhances accuracy by using advanced algorithms and data analysis, and is improving both the work and the products/output.
• Natural language processing facilitates language translation in virtual assistants.
• AI algorithms extract valuable insights that support decision-making, identifying patterns/trends. Establishing new AI-specific job titles leads to professionals that can perform with skilled excellence.

Disadvantages of Artificial Intelligence

• There are some disadvantages like the lack of qualified professional to apply the skills efficiently in a complex Al environment.
• If Al provides loan applications, the underlying rationale may be misunderstood and the application will be turned down
• Al systems sometimes lack the necessary data to make proper decisions
• AI algorhthms fail to understand and respond to human emotions appropriately which cause insensitivity.
• When Al automation systems cant solve complex issues, the wait time increases.

Maintenance and Cost Disadvantages

• AI models need constant adjustments, which can be costly
• Al system costs are very high considering the components that are involved and must continue for up-to-date information for its application.
• Al is only available to systems where data is available but this is not always the case and it may provide unhelpful outputs .
• AI systems require select and label training data, design model architectures, and fine-tune performance. This also involves moral and ethical considerations. .
• An Al algorithm can result in increased unemployment in roles that require repetitive tasks such as cashiers or stock clerks.
• Al algorithm's also often are biased and cannot ensure the protection of indvidual rights such as facial recognition in Al systems.

Security, Performance and Environmental Impacts

• They are sometimes vulnerable to forms of cyberattacks and misuse and cause traffic disruptions.
• A data breach can lead to privacy violations and identity theft.
• Limited generalization occurs when Al perofrms specific asks but fails new or varied situations.
• Computation resources creates large amount of energy and can contribute to carbon emissions and environmental degradation.