Automated Decision-Making Technology (ADMT)
What is Automated Decision-Making Technology (ADMT)?
Automated Decision-Making Technology (ADMT) refers to systems that use automated logic, including algorithms, scoring models, or machine-learning tools, to make evaluations or decisions about individuals with limited or no human intervention. Examples include fraud scoring tools, risk classifiers, eligibility screens, content recommendations, and systems that predict consumer behavior.
Why does ADMT matter?
ADMT influences how consumers experience online services and how businesses evaluate risk, eligibility, or engagement. Because automated systems may introduce bias, fairness concerns, or unexpected impacts, CCPA regulations include notices, opt-outs, and access rights that explain what ADMT does and how it affects individuals. Businesses using ADMT may also need to document safeguards, conduct risk assessments, and provide a mechanism for consumers to request details or appeal certain decisions.
FAQs about ADMT
Scoring models, automated classifiers, recommendation engines, eligibility filters, fraud detection systems, and predictive audience tools.
No. Any automated logic that evaluates individuals may qualify, whether or not it uses advanced AI.
CPRA rules include rights to access meaningful information, opt out of certain automated decisions, and request human review when decisions significantly affect them.
Yes. Businesses may need to explain the purpose, the data used, and how automated logic influences outcomes.
Automated decisions that influence access to services, eligibility screenings, pricing, employment-related evaluations, or fraud assessments.
High-risk ADMT often requires a risk assessment documenting purpose, potential harms, and safeguards.
Yes. Businesses may need to revisit their logic, datasets, and outcomes to maintain accuracy and fairness.
Yes, when profiling is used to predict behavior or assign individuals to advertising audiences.