The Conference for Machine Learning Innovation

An Interdisciplinary Approach to Artificial Intelligence Testing: Development of an Artificial Intelligence Quotient (A-IQ)

Session
Join the ML Revolution!
Thank you for joining
See you in 20201!
Join the ML Revolution!
Thank you for joining
See you in 20201!
Join the ML Revolution!
Register until December 12:
✓ML Intro Day for free
✓Raspberry Pi or C64 Mini for free
✓Save up to $580
Register Now
Join the ML Revolution!
Register until December 12:
✓ML Intro Day for free
✓Raspberry Pi or C64 Mini for free
✓Save up to $580
Register Now
Join the ML Revolution!
Register until November 7th:
✓Save up to € 210
✓10% Team Discount
Register Now
Join the ML Revolution!
Register until November 7th:
✓Save up to € 210
✓10% Team Discount
Register Now
Infos
Tuesday, June 19 2018
11:30 - 12:30
Room:
Asam 2

Humanity is more than ever confronted with artificial intelligence (AI), yet it is still challenging to find a common ground. By adopting the term intelligence, it has inherited a myriad of issues from the history of psychological intelligence research. AI research inevitably requires an interdisciplinary approach. Our research project aims to understand, measure, compare and track changes of AI capabilities. Therefore, an Artificial Intelligence Model is derived, understood as a system of capabilities to solve problems. It integrates seven categories: explicit knowledge, language aptitude, numerical and verbal reasoning, working memory, divergent and critical thinking. Forms of thinking are classified following Bloom’s Taxonomy. The Artificial Intelligence Scale is developed, reflecting academic IQ-testing procedures. The evaluation through multiple question and answer categories and individual weighting of both is unique, resulting in the A-IQ score. 

Tests are executed with digital assistants, independent of their ecosystem: Google Now, Siri (Apple), Cortana (Microsoft) and Alexa (Amazon). Results indicate best overall performance by Siri due to strong working memory skills. Among other results on category level, Cortana leads at explicit knowledge. None exhibit critical or creative thinking skills. A solution to automate A-IQ testing is proposed. Weaknesses and implications for future research and practice are discussed.

This Session originates from the archive of Diese Session stammt aus dem Archiv von MunichMunich . Take me to the program of . Hier geht es zum aktuellen Programm von Online Edition Online Edition .

This Session originates from the archive of Diese Session stammt aus dem Archiv von MunichMunich . Take me to the program of . Hier geht es zum aktuellen Programm von Munich Munich .

This Session originates from the archive of Diese Session stammt aus dem Archiv von MunichMunich . Take me to the program of . Hier geht es zum aktuellen Programm von Singapore Singapore .

This Session originates from the archive of Diese Session stammt aus dem Archiv von MunichMunich . Take me to the program of . Hier geht es zum aktuellen Programm von Berlin Berlin .

This Session Diese Session originates from the archive of stammt aus dem Archiv von MunichMunich . Take me to the current program of . Hier geht es zum aktuellen Programm von Online Edition Online Edition , Munich Munich , Singapore Singapore or oder Berlin Berlin .

Behind the Tracks