Business Commons^™

I'M Special But A.I. Doesn't Get It, Huei Huei Laurel Teo

Dissertations and Theses Collection (Open Access)

A growing body of management research on artificial intelligence (AI) has consistently shown that people innately distrust decisions made by AI and find such decision processes simply less fair compared to decisions made by humans. My dissertation adopts a different perspective to propose that aside from fairness concerns, AI decision methods trigger perceptions in people that their individual uniqueness has not be adequately considered and this has negative consequences for their psychological or subjective well-being.

By combining theories of uniqueness, individuality, power, and well-being, I develop five studies to provide empirical evidence that aversion to AI-mediated decisions also operates through …

Changing The Focus: Worker-Centric Optimization In Human-In-The-Loop Computations, Mohammadreza Esfandiari

Dissertations

A myriad of emerging applications from simple to complex ones involve human cognizance in the computation loop. Using the wisdom of human workers, researchers have solved a variety of problems, termed as “micro-tasks” such as, captcha recognition, sentiment analysis, image categorization, query processing, as well as “complex tasks” that are often collaborative, such as, classifying craters on planetary surfaces, discovering new galaxies (Galaxyzoo), performing text translation. The current view of “humans-in-the-loop” tends to see humans as machines, robots, or low-level agents used or exploited in the service of broader computation goals. This dissertation is developed to shift the focus back …

Opportunity Identification For New Product Planning: Ontological Semantic Patent Classification, Farshad Madani

Dissertations and Theses

Intelligence tools have been developed and applied widely in many different areas in engineering, business and management. Many commercialized tools for business intelligence are available in the market. However, no practically useful tools for technology intelligence are available at this time, and very little academic research in technology intelligence methods has been conducted to date.

Patent databases are the most important data source for technology intelligence tools, but patents inherently contain unstructured data. Consequently, extracting text data from patent databases, converting that data to meaningful information and generating useful knowledge from this information become complex tasks. These tasks are currently …

Equity Trading Evaluation Strategies In Switzerland After The European Mifid Ii, Linn Kristina Karstadt

Walden Dissertations and Doctoral Studies

Swiss bank traders are affected by technological and regulatory challenges, which may affect their broker voting process and may result in a change of trading and evaluation behavior in 2018. Compounded challenges exist when broker evaluation strategies are not effective or Markets in Financial Instruments Directive (MiFID) II compliant. This qualitative, single case study, built on efficient capital market hypothesis and innovative disruption theory, was focused on effective broker evaluation strategies after MiFID II in Switzerland. The sample consisted of 4 buy-side traders, who shared their unique perspectives. Methodological triangulation was achieved through semistructured interviews, a review of the institution's …

Design And Implementation Of Two Text Recognition Algorithms, Madhumathi Yendamuri

Theses

This report presents two algorithms for text recognition. One is a neural-based orthogonal vector with pseudo-inverse approach for pattern recognition. A method to generate N orthogonal vectors for an N-neuron network is also presented. This approach converges the input to the corresponding orthogonal vector representing the prototype vector. This approach can restore an image to the original image and thus has error recovery capacility. Also, the concept of sub-networking is applied to this approach to enhance the memory capacity of the neural network. This concept drastically increases the memory capacity of the network and also causes a reduction of the …

New Algorithms For Mid-Crack Codes In Image Processing, Wai-Tak Wong

Theses

The chain code is a widely-used description for a contour image. Recently, a mid-crack code algorithm has been proposed as another more precise method for image representation. New algorithms using this new mid-crack code for image representation, restoration, and skeletonization are developed. The efficiency and accuracy can be increased obviously.

Firstly, the conversion of a binary image with multiple regions into the mid-crack codes is presented. A fast on-line implementation can be achieved using tables look-up. The input binary image may contain several object regions and their mid-crack codes can be extracted at the same time in a single-pass row-by-row …