A Framework of Enhanced Performance: People's Interactions With Cognitive Assistants

A Framework of Enhanced Performance: People's Interactions With Cognitive Assistants

Md. Abul Kalam Siddike (University of Dhaka, Dhaka, Bangladesh), Jim Spohrer (IBM Research, San Jose, USA), Haluk Demirkan (University of Washington-Tacoma, Tacoma, USA) and Youji Kohda (Japan Advanced Institute of Science and Technology, Nomi, Japan)
DOI: 10.4018/IJSSOE.2018070101

Abstract

While cognitive computing-enabled smart computers are growing in people's daily lives, there are not many studies that explain how people interact and utilize these solutions, and the impact of these smart machines to people's performance to do things. In this article, a theoretical framework for boosting people's performance using cognitive assistants (CAs) was developed and explained using the data analysis from 32 interviews. The results show that people interaction with CAs enhance their levels of cognition and intelligence that help them to enhance their capabilities. Enhanced capabilities help people to enhance their performance.
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Introduction

There is no doubt that computers are increasingly capable of doing things that make humans more knowledgeable and productive. Today smart machines are able to recognize patterns, perform rule-based analysis from very large amounts of data, solve both structured and unstructured problems, recognize voices, process natural language, learn, and interact with other computers and humans (Siddike et al., 2018; Siddike et al., 2017).

Apple’s Siri, Google’s Now, Amazon’s Echo, IBM’s Watson (Figure 1) and many other smart machines, and cognitive tools, are beginning to reach a level of utility that provide a foundation for a new generation of assistants, cognitive assistants (CAs) (Spohrer and Banavar, 2015). CAs are new decision support tools that are able to augment human capabilities and expertise (Spohrer, 2016; Spohrer et al., 2017; Spohrer, Siddike and Kohda, 2017).

CAs can provide people high-quality recommendations and help them make better data driven decisions (Demirkan et al., 2015). People problem solving capabilities significantly augmented by the interaction of people and CAs (Spohrer and Banavar, 2015; Spohrer and Siddike, 2017). Cognitive computing and sensor technologies have begun to emerge to augment and scale the capabilities of people in specific ways (Kelly III and Hamm, 2013; Pentland, 2008). Smart machines can potentially progress from cognitive tools to assistants to collaborators to coaches, and be perceived differently depending on the role that they play in a service system (Spohrer and Siddike, 2017).

Figure 1.

Cognitive assistants

IJSSOE.2018070101.f01

People have limited life spans and limited cognitive capabilities in decision making that are considered as “bounded rationality” (Simon, 1997). As knowledge accumulates in society, Jones (2005) identified the condition known as the “knowledge burden.” In addition, there is a “half-life of knowledge” in any innovation-oriented society (Arbesman, 2013). Furthermore, today people flooded with data, information and knowledge (Baltes and Staudinger, 2000; Nonaka and Takeuchi, 2011; Sternberg, 2003). To address some of these challenges, researchers have been working on “knowledge factories” known for teaching (learning), discovery (research) and application of knowledge (entrepreneurship and policy making) (Spohrer, Giuiusa, Demirkan and Ing, 2013). People also focus on acquiring special type of knowledge from experience and a sense of humor to cope with life’s challenges. In fact, social-emotional-learning (SEL) skills are increasingly viewed as important predictors of character development as well as success in acquiring STEM (Science-Technology-Engineering-Mathematics) skills (Elias 2009). When data is growing exponentially, people need more resilient and sustainable approaches to address personal and professional challenges and opportunities. Today for example, cognitive computing has begun to emerge to augment and scale the capabilities of people in specific ways (Kelly III and Hamm, 2013; Pentland, 2008). With cognitive assistants, people have an opportunity to analyze large amount of data very fast, and make much more efficient, effective and accurate decisions.

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