[02/Magdalena/08]

Data lineage

Anonymization of personal data

Securing and limiting access to data

True

False

True

Securing and limiting access to data = Ensuring data is protected from unauthorized access Deleting, anonymization or pseudonymization of personal data = Methods to remove or obscure identifiable information Data lineage = Tracking and documenting the origin and movement of data Auditability = Ability to track and review activities and changes to data

Deleting = Removing data from storage Anonymization = Transforming data to prevent identification of individuals Pseudonymization = Replacing identifying information with a pseudonym Auditability = Tracking and reviewing activities and changes to data

Securing and limiting access to data = Protecting data from unauthorized access Data lineage = Documenting the origin and movement of data Auditability = Ability to track and review activities and changes to data Deletion = Removing data from storage

California Consumer Privacy Act (CCPA) = Gives consumers the right to know what information businesses collect about them and how it is used Algorithmic Accountability Act of 2022 = Would require large technology companies to conduct impact assessments of their algorithms General Data Protection Regulation (GDPR) = Requires organizations to obtain consent from users before collecting their data and provide users with the right to have their data erased Data Governance = Involves developing and implementing policies, procedures, and controls to ensure the accuracy, security, and privacy of data

Regulatory Challenges = Include obtaining consent from users, providing access to their data, and ensuring data is erased Ethical Implications = Data-driven applications have the potential to be used for good or harmful purposes Compliance = Organizations need to consult with legal counsel to ensure they are following all applicable regulations Responsible and Ethical Deployment = Important for organizations developing and deploying data-driven applications

User Consent = Obtaining permission from users before collecting their data Data Access = Providing users with the ability to view and retrieve their data Data Erasure = Giving users the right to have their data removed Opt Out = Allowing users to choose not to have their information sold to third parties

Data Auditing = One of the requirements for data to be auditable Data Lineage = Process of tracking and documenting the movement of data Data Anonymization = Method of removing identifiable information from personal data Data Pseudonymization = Method of replacing identifiable information with pseudonyms

Data-driven Applications = Have the potential to be used for good or harmful purposes Algorithmic Accountability = Involves conducting impact assessments of algorithms Transparency = Large technology companies are required to provide this about how their algorithms work Data Privacy = Users have the right to know what information businesses collect about them and how it is used

Data Security = Involves securing and limiting access to data Data Accuracy = One of the key aspects of data governance Data Privacy = Users have the right to know how their data is being used Data Governance Framework = Provides a structure for managing and protecting data

California Consumer Privacy Act (CCPA) = User consent and the right to opt out General Data Protection Regulation (GDPR) = User consent and the right to be forgotten Algorithmic Accountability Act of 2022 = Transparency about how algorithms work Data Governance = Ensuring the accuracy, security, and privacy of data

User Consent = One of the requirements for collecting data Data Access = Users have the right to view and retrieve their data Data Erasure = Users have the right to have their data removed Opt Out = Users can choose not to have their information sold to third parties

Data Protection = Involves ensuring the security and privacy of data Data Governance = Involves developing and implementing policies, procedures, and controls to ensure the accuracy, security, and privacy of data Data Privacy = Users have the right to know what information businesses collect about them and how it is used Data Auditing = Process of examining data to ensure it meets specific criteria

California Consumer Privacy Act (CCPA) = User consent and the right to know how data is used General Data Protection Regulation (GDPR) = User consent and the right to have data erased Algorithmic Accountability Act of 2022 = Transparency about how algorithms work Data Governance = Involves developing and implementing policies, procedures, and controls to ensure the accuracy, security, and privacy of data

Privacy = Concerns about how personal data is collected, stored, and used Security = Concerns about the potential for cyberattacks and data breaches Bias = Concerns about unfair or discriminatory outcomes due to biased applications Transparency = Difficulty in understanding how data-driven applications work

Healthcare = Uses data-driven applications for patient care and research Finance = Uses data-driven applications for risk analysis and fraud detection Retail = Uses data-driven applications for inventory management and customer analytics Criminal Justice = Uses data-driven applications for predictive policing and sentencing

General Data Protection Regulation (GDPR) = Imposes strict requirements on organizations that collect and process personal data Data Breach = A security incident where sensitive, protected, or confidential data is accessed or disclosed without authorization Data Lineage = The life cycle of data, including its origins and where it moves over time Data Anonymization = The process of removing or modifying personally identifiable information from data sets

Bias = High-stakes contexts such as criminal justice and financial services Transparency = Understanding how the applications work and how data is being used Privacy = Collection and storage of large amounts of personal data Security = Applications that are often targeted by cyberattacks

Data-driven applications = Applications that rely on data to make decisions Regulatory challenges = Issues that arise due to legal and regulatory requirements Data breaches = Security incidents where sensitive data is accessed or disclosed without authorization Bias in applications = Unfair or discriminatory outcomes due to biased algorithms or data

Privacy = Industries that collect and store large amounts of personal data Security = Industries that are often targeted by cyberattacks Bias = Industries that use data-driven applications in high-stakes contexts Transparency = Industries where it is important for users and regulators to understand how the applications work

Data-driven applications = Applications that rely on data to make decisions Regulatory challenges = Issues that arise due to legal and regulatory requirements Data breaches = Security incidents where sensitive data is accessed or disclosed without authorization Bias in applications = Unfair or discriminatory outcomes due to biased algorithms or data

Healthcare = Uses data-driven applications for patient care and research Finance = Uses data-driven applications for risk analysis and fraud detection Retail = Uses data-driven applications for inventory management and customer analytics Criminal Justice = Uses data-driven applications for predictive policing and sentencing

Bias = High-stakes contexts such as criminal justice and financial services Transparency = Understanding how the applications work and how data is being used Privacy = Collection and storage of large amounts of personal data Security = Applications that are often targeted by cyberattacks

Privacy = Concerns about how personal data is collected, stored, and used Security = Concerns about the potential for cyberattacks and data breaches Bias = Concerns about unfair or discriminatory outcomes due to biased applications Transparency = Difficulty in understanding how data-driven applications work

The California Consumer Privacy Act (CCPA)

Obtaining consent from users before collecting their data

Data-driven applications can be used for harmful purposes

Data must be anonymized or pseudonymized

The Algorithmic Accountability Act of 2022

Providing users with access to their data

Conducting impact assessments of algorithms

Ensuring data security and limiting access to data

Obtaining consent from users before collecting their data

Developing and deploying applications in a responsible and ethical manner

Lack of transparency

Criminal justice

Data breaches

GDPR

Data collection

Unfair outcomes

Healthcare

Data misuse

Lack of understanding

Data breaches

True

False

False

False

True

False

True

False

False

False

True

True

True

False

False

True

False

True

False

False