AI in Policing and Big Data Insights

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Questions and Answers

Which type of AI application is discussed in relation to policing?

Predictive policing

What does AUC (Area Under the Curve) represent in machine learning classification problems?

It measures the model's ability to distinguish between classes.

According to the lecture, what is the binary classification problem in this application?

Classifying whether an individual may commit a crime or not.

What is the main goal of an early intervention system (EIS) in policing?

To prevent crime before it occurs. Signup and view all the answers

The lecture advocates for a user-centric approach in designing digital platforms, focusing on the needs of which group to ensure safety for all?

The community. Signup and view all the answers

Which approach to data de-identification involves irrevocably deleting personal information from datasets?

Data destruction. Signup and view all the answers

Which regulatory framework is particularly focused on in the lecture concerning data privacy in the era of big data?

GDPR (General Data Protection Regulation). Signup and view all the answers

Which technology has significantly improved the accessibility of legal information to the general public over recent years?

Online legal databases. Signup and view all the answers

Which United Nations' definition did Katrina Denver reference during the discussion?

Human rights related to the use of technology. Signup and view all the answers

What concern is raised in the lecture about the impact of personalized algorithms on user behavior?

They can create echo chambers and reinforce biases. Signup and view all the answers

What is the primary focus of the concept of surveillance capitalism?

Monetization of personal data. Signup and view all the answers

How do web servers identify and personalize users' experiences?

By tracking user behavior and preferences. Signup and view all the answers

In the old world shopping experience, what was the main constraint for shoppers and store owners?

Limited access to product information. Signup and view all the answers

Which of the following is an example of soft fraud?

Exaggerating damages in an insurance claim Signup and view all the answers

What is the primary advantage of 'privileged learning' in AI?

Improved decision-making through better insights. Signup and view all the answers

What is the purpose of Explainable AI in Shift's fraud-detection algorithm?

To make AI decisions transparent and understandable. Signup and view all the answers

What is the main challenge faced by the insurance industry due to digitization?

Increased data privacy concerns. Signup and view all the answers

I was a good student and gave good feedback to my classmates.

False Signup and view all the answers

In the context of artificial intelligence, what does 'overfitting' refer to?

A model that learns noise in the training data rather than the actual pattern. Signup and view all the answers

Which of the following is NOT one of the three V's of big data mentioned in the text?

Verification Signup and view all the answers

What is the primary advantage of using big data in the context of AI?

Enhanced decision-making capabilities. Signup and view all the answers

What is the purpose of the Turing test in the context of AI?

To determine if a machine can exhibit intelligent behavior indistinguishable from a human. Signup and view all the answers

Which term describes the ability of an AI model to perform well on tasks that it has never encountered during training?

Generalization. Signup and view all the answers

In the context of AI, what is meant by 'general AI'?

An AI that possesses the ability to understand, learn, and apply intelligence across a wide range of tasks. Signup and view all the answers

What is the main goal of artificial intelligence (AI)?

To create machines that can perform tasks that typically require human intelligence. Signup and view all the answers

What is the main value of big data?

It provides insights and supports informed decision-making. Signup and view all the answers

What type of data is characterized by being collected in a non-standard way?

Unstructured data. Signup and view all the answers

What is the key difference between big data and classical data science?

The volume and complexity of data handled. Signup and view all the answers

What is the distinguishing line between big data and alternative data?

Big data pertains to large datasets, whereas alternative data refers to non-traditional data sources. Signup and view all the answers

What are the three key characteristics of big data according to Doug Laney's three V's?

Volume, velocity, and variety. Signup and view all the answers

Which skill set is essential for someone working with AI technologies in the age of big data?

Data analysis and machine learning expertise. Signup and view all the answers

What technology does ShotSpotter use to detect shots fired?

Acoustic sensors. Signup and view all the answers

What was Ralph Clark's significant change to the ShotSpotter business model?

Shifting from selling equipment to offering a subscription service. Signup and view all the answers

How many 0s does a zettabyte have?

<ol start="21"> <li></li> </ol> Signup and view all the answers

What technology allows us to access and interact with large amounts of data spread across various locations globally?

Cloud computing. Signup and view all the answers

Which class of artificial intelligence models is primarily responsible for generating deep fakes?

Generative adversarial networks (GANs). Signup and view all the answers

What is the term used for a type of artificial intelligence technology that creates hyper-realistic images and videos of non-existent entities?

Deep fake technology. Signup and view all the answers

What is the role of the 'test' in AI training?

To evaluate the model's performance on unseen data. Signup and view all the answers

What is the main challenge of working with big data?

Data quality and management. Signup and view all the answers

Which of the following is Not mentioned as a contributing factor to energy consumption in large models?

User engagement Signup and view all the answers

Why are some large language models increasingly adopting smaller, more efficient architectures?

To reduce energy consumption and improve processing speed. Signup and view all the answers

What is a core feature of transformer models contributing to their effectiveness?

Attention mechanism. Signup and view all the answers

What breakthrough did word embeddings like Word2Vec achieve?

Converting words into vector representations for better semantic understanding. Signup and view all the answers

In the early wave of natural language processing, what was a significant limitation of statistical models?

They lacked the ability to understand context. Signup and view all the answers

What kind of governance is suggested for implementing AI in public services?

Transparent and accountable governance. Signup and view all the answers

Study Notes

AI in Policing

AI application in policing: Early intervention system (EIS)
AUC (Area Under the Curve): Represents the model's ability to distinguish between classes, higher AUC indicates better accuracy
Binary classification problem: Identifying individuals at risk of future criminal activity
Goal of EIS: To prevent future crime through early intervention and support
User-centric approach: Focus on the needs and concerns of communities and individuals to ensure safety for all
Data de-identification: Irrevocably deleting personal information from datasets
Regulatory framework: General Data Protection Regulation (GDPR)
Technology for legal information: Internet and online legal databases

Big Data

United Nations' definition: Big data as a new kind of challenge for human rights
Concern about personalized algorithms: Potential for manipulation and reinforcement of existing biases
Surveillance capitalism: The commodification of personal data for profit and control
Web server identification: Through cookies, IP addresses, and browsing history
Constraint in old world shopping: Limited information availability and product options
Soft fraud: Examples include manipulating insurance claims
Privileged learning in AI: Ability to use sensitive data for model training without directly exposing data to the model
Explainable AI in fraud detection: Provides transparency and human oversight for algorithm decisions
Challenge for insurance industry: Adapting to the digital environment and managing risk

Artificial Intelligence (AI)

Overfitting: Model performs well on training data but poorly on unseen data
Three V's of big data: Volume, Velocity, and Variety
Fourth V of big data: Veracity
Advantage of big data in AI: Increased data availability for training more accurate and sophisticated models
Turing test: Evaluates a machine's ability to exhibit intelligent behavior indistinguishable from a human
Generalizability: An AI model's ability to perform well on tasks it hasn't encountered during training
General AI: AI capable of performing any intellectual task that a human can
Goal of AI: To build machines that can perform tasks that typically require human intelligence
Value of big data: Insights and predictions, improved decision making
Non-standard data: Data collected haphazardly and inconsistently
Key difference between big data and classical data science: Volume and complexity of data
Distinguishing line between big data and alternative data: Traditional data sources vs. non-traditional sources (e.g., social media)

Big Data and AI: Applying Technologies

Key characteristics of big data: Volume, velocity, and variety
Essential skill set for AI in big data: Data science, machine learning, and AI expertise
ShotSpotter technology: Acoustic sensors to detect gunshots
Ralph Clark's change: Shifting focus from selling the technology to providing a service with data insights
Zettabyte: One followed by 21 zeros
Technology for accessing large data: Cloud computing
AI models generating deep fakes: Generative Adversarial Networks (GANs)
Technology creating hyper-realistic images and videos: Generative AI or Generative Adversarial Networks
Role of the "test" in AI training: Evaluating model performance on unseen data
Main challenge of big data: Managing and processing large amounts of data
Contributing factors to energy consumption in large models: Computation, model size, data storage
Reason for smaller model architecture: Efficiency and reduced computational burden
Core feature of transformer models: Attention mechanism to understand relationships within text
Word2Vec breakthrough: Creating word embeddings to represent words as vectors, capturing semantic meaning
Limitation of early NLP models: Struggled with complex language understanding
Governance for AI in public services: Human-centered, ethical, and transparent

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Description

Explore the intersection of artificial intelligence and big data in policing. This quiz delves into early intervention systems, data privacy regulations like GDPR, and the implications of big data on human rights and community safety. Test your understanding of these critical contemporary issues.