Automated Decision-Making (ADM)
Automated Decision-Making (ADM) enables systems to make data-driven choices without human intervention, improving speed, accuracy, and efficiency in business operations.
TL;DR (Too Long; Didn't Read)
ADM uses data and algorithms to make decisions automatically, reducing delays and enhancing precision.
Definition of Automated Decision-Making (ADM)
Automated Decision-Making (ADM) refers to the process of making choices using computer algorithms and data analysis without direct human input. This technology enhances efficiency, reduces bias, and enables real-time decision-making in areas like finance, healthcare, and customer service.
“ADM turns data into instant, automated decisions.”
Synonyms
Prescriptive data analysis, machine decision-making, computerised decision-making, data-driven decision-making, decision automation, algorithmic decision-making. These synonyms emphasise the use of data-driven insights and automated algorithms to support and execute decisions.
Antonyms
The opposite are decisions in which humans are directly involved. This antonym emphasises processes that are deeply rooted in human intuition, expertise, and direct involvement. Traditional types of decision-making, also known as manual decision-making, intuitive decision-making, or human-led decision-making, are based on the nuanced judgement, emotional intelligence, and ethical considerations that humans bring to complex problem-solving situations.
In a Broader Perspective
Different Flavours
An automated decision may vary from supporting human decision-makers to completely autonomous systems that respond right away - the so-called level of automation. Automated decision-making can be further broken down into application domain, degree of autonomy, ethical and legal considerations, approach, and impact.
Classic ADM Example: E-mail Spam Filter
The use of spam e-mail filters in e-mail systems is a classic example of decision automation. Based on predefined rules and algorithms, spam filters automatically analyse incoming e-mail messages and decide whether to deliver them to the inbox or divert them to a spam or junk bin. This automated decision process allows e-mail users to have a cleaner inbox, save time, and reduce their vulnerability to phishing, malware, and other unwanted e-mail attacks. To remain successful against new spam strategies and growing threats, the spam filter adapts and updates its rules and algorithms over time.
Other ADM Applications
Automated decision-making is also used in many fields other than spam filters, including healthcare (for medical diagnoses and treatment recommendations), e-commerce (for product recommendations), and autonomous vehicles (for route planning and collision avoidance). More than 70 other examples »