Knowing Better Than the AI: How the Dunning-Kruger Effect Shapes Reliance on Human-AI Decision Making

Artificial Intelligence (AI) is increasingly helping people with all kinds of tasks, due to its promising capabilities. In some tasks, an AI system by itself will take over tasks, but in other tasks, an AI system making decisions on its own would be undesired due to ethical and legal reasons. In those cases, AI can still be of help by forming...

Creating a Unified Structure for Positive and Negative Common Sense Knowledge

Common sense is knowledge that most humans have, but machines do not. Generally, computer knowledge bases make use of positive (known) knowledge. However, in addition to positive common sense knowledge, there is also negative. Negative knowledge represent facts that are known to be untrue, like "a cat does not have fins". This knowledge is...

Mapping User Intents in Web Search Queries to Types of Commonsense Knowledge

Commonsense knowledge is a type of knowledge consisting of facts that humans use every day. Humans make queries in search engines with different user intents, and some of them can be answered by knowledge tuples. Different types of knowledge are stored differently in the knowledge bases. Being aware of the types of commonsense knowledge required...

A Uniform Model for Generative and Discriminative Commonsense Knowledge Tuples

Commonsense knowledge plays a key role in human intelligence. It is knowledge possessed by most humans that helps them in everyday situations. One possible way is to store the knowledge in four types. Each piece is either positive or negative, and generative or discriminative. For efficient retrieval and storage, a uniform model is needed....

Obtaining Query-specific Similar Concepts with BERT-based retrieval for Commonsense Knowledge Gameboard

Commonsense knowledge based question answer- ing is a recent topic that has seen a surge in inter- est. Yet most models obtain general data, this pa- per looks at obtaining query-specific similar con- cepts using first and second-order proximity to- gether with BERT-based retrieval. Using these query-specific concepts new commonsense knowl- edge...

A Comprehensive Taxonomy of User Intents for Search Queries

Search engines operate as an oracle between user queries and information access: the user types the input and receives back the information requested. To accomplish the task, search engines need to interpret human language and, most importantly, comprehend the underlying user intents of a query. With this process, they can retrieve the most...

Effectiveness of Automatic and Semi-Automatic Methods to Collect Common Sense Knowledge

Common sense knowledge (CSK) comes naturally to humans, but is very hard for computers to comprehend. However it is critical for machines to behave intelligently, and as such collecting CSK has become a prevalent field of research. Whilst a lot of research has been done to develop CSK acquisition methods, not much work has been done to survey...

A systematic comparison of commonsense knowledge usages between natural language processing (NLP) and computer vision (CV)

Commonsense knowledge is the key of human intelligence in generalizing their knowledge to deal with complex tasks. Over the past years, a lot of research has been done in both natural language processing (NLP) and computer vision (CV) on leveraging commonsense knowledge to improve AI models. However, no systematic comparisons of existing work...

A Survey of Commonsense Knowledge Organization, Structuring and Categorization

Commonsense knowledge (CK) in artificial intelligence (AI), is an expanding field of research. Because CK is intrinsically implicit, current datadriven machine learning models are still far from competent compared to humans in commonsense reasoning tasks. To minimize the gap between machine learning models with the goal of artificial general...

A Survey of Crowdsourcing Methods for Commonsense Knowledge Collection

Commonsense knowledge is information that all humans own and use to interpret common situations and react to them accordingly. This kind of information is necessary for the training of artificial intelligence models to reach a performance as close as possible to human performance. Researchers have developed methods that use crowdsourcing to...