Correct Answer: Engaging in inclusive and participatory design practices
Explanation: Engaging in inclusive and participatory design practices can help mitigate bias in AI algorithms by involving diverse stakeholders, including those who may be affected by bias, in the development process to identify and address potential biases early on.
Correct Answer: Reinforcement of racial or socioeconomic biases
Explanation: Bias in AI algorithms in criminal justice systems can reinforce racial or socioeconomic biases by disproportionately targeting or penalizing certain groups, leading to unfair treatment and exacerbating existing disparities in the criminal justice system.
Correct Answer: Ensuring representation of diverse populations in training data
Explanation: Ensuring representation of diverse populations in training data is essential in addressing bias in AI algorithms in healthcare applications, as it helps prevent underrepresentation or misrepresentation of certain groups and ensures that AI models generalize well across different demographic groups.
Correct Answer: Reinforcement of socioeconomic disparities and exclusion
Explanation: Bias in AI algorithms in financial services can reinforce socioeconomic disparities and exclusion by perpetuating historical patterns of discrimination and limiting access to financial opportunities for certain groups based on factors such as race, gender, or income level.
Correct Answer: Designing algorithms with fairness-aware objectives and metrics
Explanation: Designing algorithms with fairness-aware objectives and metrics can help mitigate bias in AI algorithms by incorporating fairness constraints into the model development process and explicitly optimizing for fairness alongside accuracy and other performance metrics.
Correct Answer: Lack of transparency in algorithmic decision-making processes
Explanation: Lack of transparency in algorithmic decision-making processes is one of the challenges in addressing bias in AI algorithms in social media platforms, as it makes it difficult for users and external researchers to understand how algorithms work and detect potential biases.
Correct Answer: Protecting sensitive personal information from unauthorized access
Explanation: One of the primary concerns regarding data privacy when using AI is protecting sensitive personal information from unauthorized access, misuse, or exploitation.
Correct Answer: Implementing strong encryption techniques to protect data in transit and at rest
Explanation: Implementing strong encryption techniques to protect data in transit and at rest can help address data privacy concerns when collecting and storing personal data for AI applications by safeguarding data from unauthorized access or interception.
Correct Answer: Increased vulnerability to identity theft and fraud
Explanation: One of the risks associated with data privacy concerns in AI applications is increased vulnerability to identity theft and fraud, as personal data may be exposed or compromised, leading to potential misuse or exploitation.
Correct Answer: Obtaining explicit consent from individuals before collecting their personal data
Explanation: Obtaining explicit consent from individuals before collecting their personal data is essential in addressing data privacy concerns when deploying AI systems, as it ensures that individuals are aware of and agree to the collection and use of their data for specific purposes.
Correct Answer: Respecting individuals’ rights to control their personal data
Explanation: One of the ethical considerations associated with data privacy concerns in AI applications is respecting individuals’ rights to control their personal data, including their right to consent to data collection, access their data, and request its deletion or correction.
Correct Answer: Implementing differential privacy techniques to protect individual privacy
Explanation: Implementing differential privacy techniques to protect individual privacy can help mitigate data privacy concerns when training AI models on sensitive datasets by adding noise to the data to prevent the identification of individual records while preserving the overall statistical properties of the dataset.
Correct Answer: Legal and regulatory penalties for non-compliance
Explanation: One of the potential consequences of data privacy breaches in AI applications is legal and regulatory penalties for non-compliance with data protection laws and regulations, which may result in fines, lawsuits, or reputational damage for organizations responsible for the breach.
Correct Answer: Implementing data anonymization techniques to protect individual privacy
Explanation: Implementing data anonymization techniques to protect individual privacy is essential in addressing data privacy concerns when sharing personal data with third parties for AI analysis, as it removes or masks identifying information from the data to prevent the identification of individuals.
Correct Answer: Preventing unauthorized access and data breaches
Explanation: One of the primary concerns regarding cybersecurity in AI systems is preventing unauthorized access and data breaches, which could lead to the theft, manipulation, or misuse of sensitive information or AI models.
Correct Answer: Conducting regular security audits and vulnerability assessments
Explanation: Conducting regular security audits and vulnerability assessments can help enhance cybersecurity in AI systems during the development and deployment process by identifying and addressing potential security weaknesses, loopholes, or vulnerabilities.
Correct Answer: Increased susceptibility to malicious attacks and exploits
Explanation: One of the risks associated with cybersecurity threats in AI systems is increased susceptibility to malicious attacks and exploits, which could compromise the integrity, confidentiality, or availability of AI systems and data.
Correct Answer: Implementing strong encryption and access controls
Explanation: Implementing strong encryption and access controls is essential in addressing cybersecurity concerns when deploying AI systems that process sensitive information, as it helps safeguard data from unauthorized access, interception, or tampering.
Correct Answer: Respecting individuals’ rights to privacy and data protection
Explanation: One of the ethical considerations associated with cybersecurity in AI systems is respecting individuals’ rights to privacy and data protection, including their right to have their personal information safeguarded from unauthorized access, misuse, or exploitation.
Correct Answer: Following industry-standard security frameworks and guidelines
Explanation: Following industry-standard security frameworks and guidelines can help mitigate cybersecurity risks in AI systems by implementing secure development practices and incorporating best practices for security throughout the development lifecycle.
Correct Answer: Legal and regulatory penalties for non-compliance
Explanation: One of the potential consequences of cybersecurity breaches in AI systems is legal and regulatory penalties for non-compliance with data protection laws and regulations, which may result in fines, lawsuits, or reputational damage for organizations responsible for the breach.
Correct Answer: Implementing strong encryption and access controls
Explanation: Implementing strong encryption and access controls is essential in addressing cybersecurity concerns when sharing AI models or data with external partners or collaborators, as it helps protect sensitive information from unauthorized access or interception during transmission or storage.
Correct Answer: Potential disruption of essential services and operations
Explanation: One of the risks associated with cybersecurity threats in AI systems deployed in critical infrastructure is the potential disruption of essential services and operations, which could have significant societal, economic, or national security implications.
Correct Answer: Decreased demand for skilled workers in certain industries
Explanation: One of the potential effects of AI on the job market is a decreased demand for skilled workers in certain industries as automation and AI technologies replace or augment tasks traditionally performed by humans.
Correct Answer: Manufacturing
Explanation: The manufacturing sector is likely to experience job displacement due to the adoption of AI and automation, as these technologies can automate repetitive tasks and streamline production processes, leading to reduced demand for human labor.
Correct Answer: Difficulty in reskilling and upskilling workers
Explanation: One of the challenges posed by AI’s impact on the job market is the difficulty in reskilling and upskilling workers to adapt to new job roles and technological advancements, particularly for those whose jobs are at risk of automation.
Correct Answer: Individuals with limited access to education and training
Explanation: Individuals with limited access to education and training are particularly vulnerable to job displacement caused by AI and automation, as they may lack the skills and resources necessary to transition to new job roles or industries.
Correct Answer: Greater flexibility and work-life balance for employees
Explanation: One of the potential benefits of AI’s impact on the job market is greater flexibility and work-life balance for employees, as automation and remote work opportunities enable more flexible work arrangements and schedules.
Correct Answer: Transportation
Explanation: The transportation industry is likely to see job creation as a result of AI adoption, particularly in areas such as autonomous vehicles, logistics optimization, and traffic management systems.
Correct Answer: Reduced demand for creative and analytical skills
Explanation: One of the concerns associated with AI’s impact on the job market is the reduced demand for creative and analytical skills, as automation and AI technologies focus on automating routine tasks that require less cognitive input.
Correct Answer: Emotional intelligence
Explanation: Emotional intelligence is becoming increasingly valuable in response to AI’s impact on the job market, as it involves skills such as empathy, communication, and interpersonal relationships that are difficult to automate.
Correct Answer: Higher levels of unemployment and underemployment
Explanation: One of the potential consequences of job displacement caused by AI and automation is higher levels of unemployment and underemployment, as workers may struggle to find new job opportunities that match their skills and qualifications.
Correct Answer: Healthcare
Explanation: The healthcare sector is likely to experience job growth due to the adoption of AI and automation, as these technologies can improve patient care, diagnostic accuracy, and treatment outcomes, leading to increased demand for healthcare professionals.
Correct Answer: Investing in workforce development and skills training programs
Explanation: One of the ways organizations can mitigate the negative impact of AI on the job market is by investing in workforce development and skills training programs to help workers transition to new job roles and industries.
Correct Answer: Providing access to lifelong learning opportunities
Explanation: Providing access to lifelong learning opportunities is one of the key strategies for reskilling and upskilling workers in response to AI and automation, allowing individuals to continuously acquire new skills and adapt to changing job requirements.
Correct Answer: Offering flexible training programs tailored to individual needs
Explanation: Offering flexible training programs tailored to individual needs can facilitate reskilling and upskilling efforts for employees by accommodating different learning styles, preferences, and skill levels.
Correct Answer: Enhanced job satisfaction and employee morale
Explanation: One of the benefits of investing in reskilling and upskilling programs for employees is enhanced job satisfaction and employee morale, as it demonstrates a commitment to employee development and career advancement.
Correct Answer: Establishing mentorship programs to support skill development
Explanation: Establishing mentorship programs to support skill development can help ensure the success of reskilling and upskilling initiatives by providing employees with guidance, support, and personalized learning experiences.
Correct Answer: Difficulty in measuring the return on investment (ROI) of training
Explanation: One of the challenges organizations may face when implementing reskilling and upskilling programs is difficulty in measuring the return on investment (ROI) of training, as it can be challenging to quantify the impact of training on business outcomes and performance metrics.
Correct Answer: Partnering with educational institutions to develop tailored training programs
Explanation: Partnering with educational institutions to develop tailored training programs can help organizations address the skills gap created by AI and automation by ensuring that employees have access to relevant and up-to-date training resources and curriculum.
Correct Answer: Reluctance from employees to participate in learning activities
Explanation: Reluctance from employees to participate in learning activities is one of the potential barriers to implementing effective reskilling and upskilling programs, as employees may resist change or perceive training as unnecessary or irrelevant to their job roles.
Correct Answer: Providing opportunities for cross-functional collaboration and learning
Explanation: Providing opportunities for cross-functional collaboration and learning can help organizations foster a culture of continuous learning and skill development by encouraging knowledge sharing, innovation, and interdisciplinary problem-solving.
Correct Answer: Enhanced competitiveness and agility in the marketplace
Explanation: One of the benefits of reskilling and upskilling programs for organizations is enhanced competitiveness and agility in the marketplace, as it enables them to adapt to technological advancements, industry changes, and emerging trends more effectively.
Correct Answer: Protecting individuals’ rights and privacy in the use of AI systems
Explanation: One of the primary purposes of legal and regulatory frameworks for AI is to protect individuals’ rights and privacy in the use of AI systems, ensuring that AI technologies are developed and deployed in a manner that respects ethical principles and legal requirements.
Correct Answer: Ensuring transparency and accountability in AI decision-making
Explanation: Legal and regulatory frameworks for AI often address ensuring transparency and accountability in AI decision-making, aiming to make AI systems more interpretable, understandable, and accountable to stakeholders.
Correct Answer: Inability to adapt existing laws and regulations to AI-specific issues
Explanation: One of the challenges in developing legal and regulatory frameworks for AI is the inability to adapt existing laws and regulations to AI-specific issues, such as accountability for autonomous systems, liability for AI-related harms, and data protection in AI applications.
Correct Answer: Establishing interdisciplinary task forces to study AI’s societal impacts
Explanation: Governments can address legal and regulatory challenges associated with AI by establishing interdisciplinary task forces to study AI’s societal impacts, engage stakeholders, and develop informed policies and regulations that balance innovation with ethical considerations.
Correct Answer: Increased risks of bias, discrimination, and unfairness in AI systems
Explanation: One of the potential consequences of inadequate legal and regulatory frameworks for AI is increased risks of bias, discrimination, and unfairness in AI systems, as there may be insufficient safeguards and oversight mechanisms to address these issues.
Correct Answer: Government agencies, industry organizations, academia, and civil society
Explanation: The development of legal and regulatory frameworks for AI often involves multiple stakeholder groups, including government agencies, industry organizations, academia, and civil society, to ensure a balanced and comprehensive approach to regulation.
Correct Answer: Ensuring the responsible and ethical use of personal data in AI systems
Explanation: One of the goals of legal and regulatory frameworks for AI in terms of data protection is ensuring the responsible and ethical use of personal data in AI systems, balancing innovation with privacy rights and protecting individuals’ data from misuse or exploitation.
Correct Answer: Implementing robust enforcement mechanisms and penalties for non-compliance
Explanation: Governments can enforce legal and regulatory compliance in the AI industry by implementing robust enforcement mechanisms and penalties for non-compliance, ensuring that organizations adhere to ethical standards and legal requirements in the development and deployment of AI technologies.
Correct Answer: Protecting the rights and dignity of individuals affected by AI systems
Explanation: One of the principles commonly included in legal and regulatory frameworks for AI is protecting the rights and dignity of individuals affected by AI systems, emphasizing the importance of ethical considerations and human-centered approaches in AI development and deployment.
Correct Answer: Sharing knowledge, resources, and best practices to advance AI research
Explanation: One of the key purposes of international collaboration in the field of AI is to share knowledge, resources, and best practices among nations to advance AI research and development collectively.
Correct Answer: Ensuring ethical and responsible use of AI technologies
Explanation: International standards and collaboration in AI development can benefit by ensuring ethical and responsible use of Artificial Intelligence technologies, promoting consistency and alignment with ethical principles across different regions and jurisdictions.
Correct Answer: Difficulty in achieving consensus among diverse stakeholders
Explanation: One of the challenges in establishing international standards for Artificial Intelligence is the difficulty in achieving consensus among diverse stakeholders, including governments, industry organizations, academia, and civil society, due to differing priorities, interests, and perspectives.
Correct Answer: Establishing collaborative platforms and networks for knowledge exchange
Explanation: Establishing collaborative platforms and networks for knowledge exchange can facilitate international collaboration in Artificial Intelligence research and development by fostering communication, collaboration, and partnerships among researchers, organizations, and governments across borders.
Correct Answer: Enhancing interoperability and compatibility among Artificial Intelligence systems
Explanation: One of the benefits of international collaboration in setting Artificial Intelligence standards is enhancing interoperability and compatibility among Artificial Intelligence systems, ensuring that different technologies can work together seamlessly and exchange information effectively.
Correct Answer: Addressing global challenges and risks associated with AI deployment
Explanation: International collaboration in AI governance can benefit by addressing global challenges and risks associated with AI deployment, such as bias, discrimination, security threats, and ethical concerns, through coordinated efforts and shared responsibility among nations.
Correct Answer: Enhancing trust, reliability, and safety of AI technologies
Explanation: One of the objectives of international standards for AI is enhancing trust, reliability, and safety of AI technologies by establishing common principles, guidelines, and best practices that promote responsible and ethical AI development and deployment.
Correct Answer: Engaging in multilateral discussions and diplomatic negotiations
Explanation: Engaging in multilateral discussions and diplomatic negotiations can support the establishment of international standards for AI by facilitating dialogue, cooperation, and consensus-building among nations and stakeholders with diverse interests and perspectives.
Correct Answer: To foster trust and understanding among stakeholders
Explanation: Making AI decisions transparent and interpretable is important to foster trust and understanding among stakeholders, as it allows users to comprehend the reasoning behind AI-driven decisions and assess their reliability and fairness.
Correct Answer: Increasing complexity and obscurity in the decision-making process
Explanation: One of the challenges in making AI decisions transparent and interpretable is the increasing complexity and obscurity in the decision-making process, as AI models become more sophisticated and opaque, making it difficult to understand their inner workings.
Correct Answer: Providing clear explanations for the factors influencing AI predictions
Explanation: Providing clear explanations for the factors influencing AI predictions can enhance the transparency of AI decision-making, enabling users to understand how inputs are processed and how decisions are reached by AI systems.
Correct Answer: Fostering trust, accountability, and acceptance of AI technologies
Explanation: One of the benefits of making AI decisions transparent and interpretable is fostering trust, accountability, and acceptance of AI technologies, as it allows users to verify the fairness, reliability, and ethical soundness of AI-driven decisions.
Correct Answer: Providing clear explanations for the predictions and recommendations made by AI
Explanation: Providing clear explanations for the predictions and recommendations made by AI models should be made transparent to users and stakeholders, enabling them to understand how AI decisions are derived and assessed.
Correct Answer: Increasing the transparency of AI algorithms without compromising accuracy
Explanation: One of the challenges in making AI decisions interpretable without sacrificing performance is increasing the transparency of AI algorithms without compromising accuracy, as more transparent models may sacrifice predictive power or efficiency.
Correct Answer: Users and consumers who rely on AI-driven products and services
Explanation: Users and consumers who rely on AI-driven products and services benefit from transparent and interpretable AI decisions, as they can understand and trust the decisions made by AI systems, leading to greater acceptance and adoption of AI technologies.
Correct Answer: Employing techniques such as feature importance analysis and model explanations
Explanation: Employing techniques such as feature importance analysis and model explanations is one of the strategies for enhancing the interpretability of AI models, allowing users to understand the factors driving AI predictions and recommendations.
Correct Answer: By providing clear explanations for AI predictions and recommendations
Explanation: Organizations can ensure the transparency and interpretability
Correct Answer: To foster trust and understanding among stakeholders
Explanation: Transparency in critical applications of AI is essential to foster trust and understanding among stakeholders, enabling them to comprehend the reasoning behind AI-driven decisions and assess their reliability and fairness.
Correct Answer: Providing clear explanations for AI decisions and outcomes
Explanation: Interpretability in critical applications of AI can benefit by providing clear explanations for AI decisions and outcomes, allowing users to understand the rationale behind AI-driven decisions and evaluate their validity and impact.
Correct Answer: Increasing complexity and obscurity in the decision-making process
Explanation: One of the challenges in ensuring transparency and interpretability in critical Artificial Intelligence applications is increasing complexity and obscurity in the decision-making process, making it difficult to understand how Artificial Intelligence systems arrive at their conclusions.
Correct Answer: Providing clear explanations for the reasoning behind AI decisions
Explanation: Enhancing the interpretability of AI systems in critical applications involves providing clear explanations for the reasoning behind AI decisions, enabling users to understand the factors driving AI predictions and recommendations.
Correct Answer: Fostering trust, accountability, and acceptance of AI technologies
Explanation: One of the benefits of ensuring transparency and interpretability in critical AI applications is fostering trust, accountability, and acceptance of AI technologies, as it enables stakeholders to verify the fairness, reliability, and ethical soundness of AI-driven decisions.
Correct Answer: Users and decision-makers who rely on AI-generated insights
Explanation: Transparent and interpretable AI systems benefit users and decision-makers in critical applications, as they rely on AI-generated insights to make informed decisions and take appropriate actions based on reliable and understandable information.
Correct Answer: Providing clear explanations for AI decisions and recommendations
Explanation: One of the strategies for ensuring transparency and interpretability in critical AI applications is providing clear explanations for AI decisions and recommendations, allowing users to understand the rationale behind AI-driven outcomes and assess their validity and impact.
Correct Answer: By fostering a culture of openness, accountability, and ethical responsibility
Explanation: Organizations can address the challenges of transparency and interpretability in critical AI applications by fostering a culture of openness, accountability, and ethical responsibility, emphasizing the importance of clear communication, transparency, and ethical conduct in AI development and deployment.
Correct Answer: To enhance human capabilities and productivity with AI assistance
Explanation: Human-AI collaboration technology is becoming increasingly important to enhance human capabilities and productivity with AI assistance, allowing individuals to leverage AI algorithms to augment their decision-making processes and accomplish tasks more efficiently.
Correct Answer: Enhancing human capabilities and productivity with AI assistance
Explanation: Integrating AI into human workflows is an aspect of human-AI collaboration technology that focuses on enhancing human capabilities and productivity with AI assistance, enabling individuals to work more effectively and efficiently.
Correct Answer: Enhancing human-AI interactions and cooperation in various tasks
Explanation: One of the goals of human-AI collaboration technology is enhancing human-AI interactions and cooperation in various tasks, enabling seamless collaboration between humans and AI systems to achieve common goals.
Correct Answer: Fostering trust, transparency, and communication between humans and AI
Explanation: Effective human-AI collaboration technology prioritizes fostering trust, transparency, and communication between humans and AI, ensuring that users understand AI capabilities and limitations and can collaborate with AI systems effectively.
Correct Answer: Enhancing human abilities and performance with AI assistance
Explanation: One of the benefits of human-AI collaboration technology is enhancing human abilities and performance with AI assistance, allowing individuals to leverage AI algorithms to complement their skills and accomplish tasks more effectively.
Correct Answer: Ensuring that humans have the final say in critical decision-making tasks
Explanation: The aspect of human-AI collaboration technology that emphasizes the importance of human oversight and control ensures that humans have the final say in critical decision-making tasks, maintaining accountability and responsibility for outcomes.
Correct Answer: Balancing AI assistance with human expertise and judgment in tasks
Explanation: One of the challenges in designing effective human-AI collaboration technology is balancing AI assistance with human expertise and judgment in tasks, ensuring that AI systems complement human skills and capabilities without overshadowing or replacing them.
Correct Answer: By fostering a culture of openness, trust, and collaboration between humans and AI
Explanation: Organizations can maximize the benefits of human-AI collaboration technology by fostering a culture of openness, trust, and collaboration between humans and AI, encouraging effective communication, knowledge sharing, and mutual understanding in the workplace.
Correct Answer: By augmenting human skills and abilities with AI assistance
Explanation: AI contributes to enhancing human capabilities by augmenting human skills and abilities with AI assistance, allowing individuals to leverage AI technologies to complement their expertise and accomplish tasks more efficiently.
Correct Answer: Enhancing human skills and abilities with AI assistance
Explanation: Improving decision-making is an aspect of AI-enabled human capabilities that focuses on enhancing human skills and abilities with AI assistance, enabling individuals to make better-informed decisions by leveraging AI insights and predictions.
Correct Answer: Enabling individuals to tackle complex problems more effectively
Explanation: One of the benefits of enhancing human capabilities with AI is enabling individuals to tackle complex problems more effectively, as AI technologies provide additional support and insights to help address challenges and make informed decisions.
Correct Answer: Fostering trust, transparency, and communication between humans and AI
Explanation: Effective AI-enabled human capabilities prioritize fostering trust, transparency, and communication between humans and AI, ensuring that individuals can leverage AI technologies confidently and effectively.
Correct Answer: By augmenting human skills and abilities with AI assistance
Explanation: AI assistance contributes to workforce productivity by augmenting human skills and abilities with AI assistance, enabling individuals to accomplish tasks more efficiently and effectively with the support of AI technologies.
Correct Answer: Enhancing human skills and abilities with AI assistance
Explanation: Collaboration and teamwork are emphasized in AI-enabled human capabilities by enhancing human skills and abilities with AI assistance, enabling individuals to work together more effectively and leverage AI technologies to achieve common goals.
Correct Answer: Balancing AI assistance with human expertise and judgment in tasks
Explanation: One of the challenges in maximizing the benefits of AI-enabled human capabilities is balancing AI assistance with human expertise and judgment in tasks, ensuring that AI technologies complement human skills without overshadowing or replacing them.
Correct Answer: By fostering a culture of openness, trust, and collaboration between humans and AI
Explanation: Organizations can leverage AI to enhance human capabilities effectively by fostering a culture of openness, trust, and collaboration between humans and AI, encouraging effective communication, knowledge sharing, and mutual understanding in the workplace.
Correct Answer: Enabling individuals to adapt to changing environments and challenges
Explanation: One of the key benefits of AI-enabled human capabilities in the workplace is enabling individuals to adapt to changing environments and challenges, as AI assistance provides support and insights to help address emerging issues and opportunities effectively. Artificial Intelligence
Correct Answer: Generative Adversarial Network
Explanation: GAN stands for Generative Adversarial Network, which is a class of machine learning frameworks used to generate synthetic data by training two neural networks, a generator and a discriminator, in a competitive manner.
Correct Answer: To generate synthetic data samples
Explanation: In a GAN framework, the generator’s role is to generate synthetic data samples that mimic the distribution of real data, typically by transforming random noise into meaningful data representations.
Correct Answer: To distinguish between real and fake data
Explanation: The discriminator in a GAN is trained to distinguish between real data samples from the training set and synthetic data samples generated by the generator, providing feedback to the generator to improve its performance.
Correct Answer: Unsupervised learning
Explanation: The training process of a GAN is often described as unsupervised learning, as it does not rely on labeled data but instead learns to generate synthetic data distributions through adversarial training between the generator and discriminator networks.
Correct Answer: Adversarial training
Explanation: Adversarial training is the process in a GAN where the generator tries to improve its performance based on the feedback from the discriminator, engaging in a competitive game-like scenario to generate more realistic synthetic data samples.
Correct Answer: Overfitting to the training data
Explanation: One of the challenges associated with training GANs is overfitting to the training data, where the generator may learn to memorize specific samples from the training set rather than capturing the underlying data distribution.