TY  - CHAP
A1  - Brühl, Volker
T1  - Artificial intelligence: perspectives for the financial industry
T2  - Whither artificial intelligence? Debating the policy challenges of the upcoming transformation ; 3
N2  - Artificial Intelligence (AI) will be one of the key technologies driving the future competitiveness of numerous industries. However, the term "AI" is defined in a variety of ways. AI could be understood as an umbrella term for technologies and systems that carry out tasks otherwise only executable with human intelligence. This requires specific skills that fall into the broad categories of "Sense", "Comprehend", "Act" and "Learn". Through machine learning, modern AI systems can be trained to adapt to changes in their environment, self-optimise and hence achieve better results than earlier versions of AI systems that were based on clearly defined, pre-programmed rules. Based on AI methods, rational and autonomous agents can be developed that collect and analyse relevant information from their environments, come to optimal conclusions based on certain performance parameters and eventually perform physical actions (e.g. robotics) or virtual actions (e.g. chat bots). Machine learning algorithms ensure that the information base of the system is continuously updated so that performance of the system is optimised in an iterative process.
Y1  - 2018
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/51034
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-510342
SN  - 2626-9597
SP  - 21
EP  - 24
PB  - Mercator Science-Policy Fellowship-Programme
CY  - Frankfurt am Main
ER  -