scholarly journals Artificial Intelligence Affordances for Business Innovation: A Systematic Review of Literature

10.29007/jj72 ◽  
2019 ◽  
Author(s):  
Luqman Achmat ◽  
Irwin Brown
Keyword(s):  
Artificial Intelligence ◽  
Language Processing ◽  
Business Processes ◽  
User Interaction ◽  
Clear Understanding ◽  
Strategic Decisions ◽  
End User ◽  
Business Innovation ◽  
Definition Of ◽  
Review Current

Emerging technologies like artificial intelligence (AI) have begun to play an ever- more important role in business innovation. The purpose of this paper is to review current literature to identify definitions and concepts related to artificial intelligence affordances and how artificial intelligence affords business innovation. Using a systematic six-step literature review methodology conducted with an iterative disposition, seven major affordances of AI for business innovation were identified, i.e. (i) Automate business processes, (ii) Customise end user interaction, (iii) Proactively anticipate and react to changes, (iv) Augment and upskill the workforce, (v) Assist decision making, (vi) Improve risk management, and (vii) Develop and enhance intellectual property. The literature surveyed furthermore shows that there are several gaps which allow for further research. Firstly, the definition of artificial intelligence is inconsistent and there is no widely accepted definition. Several AI-based technologies and applications being developed (e.g. Machine Learning, Deep Learning, Natural Language Processing and Neural Networks) require a clear understanding of the affordances of such technologies to be able to make informed strategic decisions. Therefore, understanding the affordances of artificial intelligence in general plays an important role in making such decisions.

scholarly journals Sign Translation Via Natural Language Processing

2021 ◽  
pp. 1-7
Author(s):  
Shadman A. Khan ◽  
Zulfikar Ali Ansari ◽  
Riya Singh ◽  
Mohit Singh Rawat ◽  
Fiza Zafar Khan ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
User Interface ◽  
Sign Language ◽  
Language Processing ◽  
New Technologies ◽  
End User ◽  
User Input ◽  
Sign Recognition ◽  
Voice User ◽  
The Voice

Artificial Intelligence (AI) technologies are new technologies with new complicated features emerging quickly. Technology adoption has been beneficial for many general models. The models help in train the voice user-interface assistance (Alexa, Cortona, Siri). Voice assistants are easy to use, and thus millions of devices incorporate them in households nowadays. The primary purpose of the sign language translator prototype is to reduce interaction barriers between deaf and mute. To overcome this problem, we have proposed a prototype. It is named sign language translator with Sign Recognition Intelligence which takes the user input in sign language and processes it, and returns the output in voice out load to the end-user.

scholarly journals Gramática de usuario final extendida para procesos de negocios

2020 ◽  
Author(s):  
◽  
Enrique Eduardo Aramayo
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Business Processes ◽  
End User ◽  
El Sistema

El concepto proceso de negocio está estrechamente vinculado a la forma en la que una organización gestiona sus operaciones. Conocer y comprender las operaciones de una organización es un punto clave que se debe tener presente dentro del proceso de desarrollo de software. A su vez, el enfoque de desarrollo dirigido por modelos denominado MockupDD captura requerimientos usando prototipos de interfaz de usuario denominados Mockups. Los usuarios finales pueden comprender fácilmente dichos prototipos y realizar anotaciones sobre los mismos. Este enfoque se basa en ésta característica principal y a partir de la misma genera valiosos modelos conceptuales que luego pueden ser aprovechados por todos los integrantes de un equipo de desarrollo de software. Utilizar el lenguaje natural para realizar anotaciones sobre los Mockups es un aspecto clave que puede ser aprovechado. En éste último aspecto una rama de la inteligencia artificial denominada “Natural Language Processing – Procesamiento del Lenguaje Natural” (NLP) viene realizando importantes aportes vinculados al uso y al aprovechamiento del lenguaje natural de las personas. El presente trabajo de tesis propone una nueva técnica denominada “End User Grammar Extended for Business Processes – Gramática de Usuario Final Extendida para Procesos de Negocios” (EUGEBP). La misma está compuesta por un conjunto de reglas de redacción diseñada para ser aplicada sobre Mockups, y por una serie de pasos que permiten procesar dichas anotaciones con el propósito derivar procesos de negocios desde las mismas. Esto se logra a través de la identificación de los elementos que componen los procesos de negocios y de las relaciones que existen entre ellos. En esencia el presente trabajo propone utilizar las anotaciones de usuario final realizadas sobre los Mockups en lenguaje natural y a partir de las mismas derivar procesos de negocio. Las anotaciones del usuario final tienen como objetivo ayudar a describir las interfaces de usuario, pero también pueden ayudarnos a identificar los procesos de negocio que el sistema debe soportar. Mientras en analista recopila información para el desarrollo de una aplicación, implícitamente también está describiendo los procesos de negocio de la organización.

scholarly journals Enhancing the Value of Patents as Corporate Assets in South Africa: How can Artificial Intelligence (AI) Assist?

2021 ◽  
Vol 24 ◽  
pp. 1-38
Author(s):  
Lonias Ndlovu
Keyword(s):  
Artificial Intelligence ◽  
South African ◽  
Language Processing ◽  
Case Law ◽  
Patent Law ◽  
Company Law ◽  
High Quality ◽  
Asset Value ◽  
Definition Of ◽  
The Internet Of Things

Although the accounting definition of assets contemplates intangible, abstract assets such as those embodied in intellectual property (IP), South African company law largely views IP as a legal and not a business asset. This paper tentatively suggests an approach that uses artificial intelligence (AI) to mitigate weaknesses in the South African patent law relating to the absence of patent searches and examinations. It is hoped that using AI will enable the filing of quality patents that satisfy the prescribed patentability criteria. High-quality patents will allow companies to accumulate patents as corporate assets. The approach is based on the algorithmic use of AI technologies such as machine learning, natural language processing, deep learning alongside the Internet of Things, and IP analytics to strengthen South Africa’s IP system and create asset value for corporations. The paper recommends using the proposed AI technologies by companies and the Patents Office to enable the filing of high-quality patents, which will lead to the accumulation of corporate assets in the form of patents. The methodology is doctrinal, and the paper relies on recent literature on IP and AI, South African law, case law and examples drawn from studies conducted in other countries.

scholarly journals Ai and Ml Based Google Assistant for an Organization using Google Cloud Platform and Dialogflow

2020 ◽  
Vol 8 (5) ◽  
pp. 2722-2727
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Natural Language ◽  
Language Processing ◽  
User Interaction ◽  
Machine Learning Algorithms ◽  
Learning Technology ◽  
Cloud Platform ◽  
Organization Process ◽  
Academic Information

Many people adopting Smart Assistant Devices such as Google Home. Now a days of solely engaging with a service through a keyboard are over. The new modes of user interaction are aided in part by this research will investigate how advancements in Artificial Intelligence and Machine Learning technology are being used to improve many services. In particular, it will look at the development of google assistants as a channel for information distribution. This project is aimed to implement an android-based chatbot to assist with Organization basic processes, using google tools such as Dialogflow that uses Natural language processing NLP, Actions on Google and Google Cloud Platform that expose artificial intelligence and Machine Learning methods such as natural language understanding. Allowing users to interact with the google assistant using natural language as input and to train the chatbot i.e. google assistant using Dialogflow Machine learning tool and some appropriate methods so it will be able to generate a dynamic response. The chatbot will allow users to view all their personal academic information, schedule meetings with higher officials, automating the organization process and organization resources information all from within the chatbot i.e. Google Assistant. This project uses the OAuth authentication for security purpose. The Dialogflow helps to understand the users query by using machine learning algorithms. By using this google assistant we are going to use the Cloud Vision API for advancement. We will use Dialogflow as key part to develop Google assistant.

scholarly journals Artificial Intelligence based BOT to Manage and Administer Cloud Services

2021 ◽  
Vol 9 (VI) ◽  
pp. 1688-1694
Author(s):  
P. Z Muzzamil
Keyword(s):  
Artificial Intelligence ◽  
Resource Management ◽  
Language Processing ◽  
Cloud Services ◽  
Basic Information ◽  
End User ◽  
Cognitive Services ◽  
Management Of Resources ◽  
Level Of Effort

In the era of cloud computing, every company uses cloud technology for its applications and other infrastructure to provide a highly available and easily accessible user experience. While monitoring and managing these assets becomes a hectic work for the IT admins. On which the Level of Effort (LOE) of the resource allocated will be high and the resource must reach different console for different information. Introducing an AI-powered bot which can monitor and manage the cloud assets will reduce the manpower drastically. Most enterprises currently have very rudimentary systems of resource management where someone in the role of an Azure or resource administrator log on to the Admin Portal of their resources and have to apply filters and search through multiple screens to find even the most basic information regarding utilization and cost. This leads to inefficient management of resources and almost leads to overspending in resources that are being underutilized. The implementation of the project will involve creating a cloud services management bot that can be integrated with an enterprise’s collaboration suite as a way to enhance the enterprise’s modern workspace. The bot is to be trained on a set of query data as part of the artificial intelligence process using the natural language processing packages that are included in the Azure Cognitive Services suite. Once queries are processed, the system will connect with the respective endpoints of the Azure Resource Management REST APIs to retrieve relevant resource utilization information and show that to the end-user.

scholarly journals Sentiment Analysis and Opinion Summarization of Product Feedback

2019 ◽  
Vol 8 (2S4) ◽  
pp. 59-64
Keyword(s):  
Artificial Intelligence ◽  
Sentiment Analysis ◽  
Language Processing ◽  
Opinion Mining ◽  
Online Shopping ◽  
User Interaction ◽  
Decision Making Process ◽  
Rule Based ◽  
Opinion Summarization ◽  
Rule Based Approach

With the exponential growth of online shopping platforms, user interaction is made direct through their reviews and ratings. User’s opinions and experiences are a significant source of valuable information in decision making process. In recent days, almost every website encourages users to express and exchange their views, suggestions and opinions related to product, services, policies, etc. publicly. Opinion mining is an extensive branch of Artificial Intelligence and a form of Natural Language Processing which illustrates the attitude of the customers, in specific services or products. Also known as Sentiment Analysis, it aims at determining the response and mood or attitude of the speaker or the overall contextual and emotional polarity or reaction. Existing algorithms determine sentiment by training on datasets, lexicon-based approach by calculating polarity and rule-based approach for classification. Opinion Summarization is the process of consolidating a large amount of sentiments and opinions into a clear and brief statement for an easier grasp on the underlying context. Major summarization methods include, Extractive method, Sentence Ranking, Abstractive method and Clustering of Textual Segments. Hence it is important to judge and classify these reviews and present a laconic opinion so it would be easier for users to obtain a gist and overall polarity on the various reviews instead of going through all of them

scholarly journals Human-Centered Explainable Artificial Intelligence for Marine Autonomous Surface Vehicles

2021 ◽  
Vol 9 (11) ◽  
pp. 1227
Author(s):  
Erik Veitch ◽  
Ole Andreas Alsos
Keyword(s):  
Artificial Intelligence ◽  
User Interaction ◽  
Mental Simulation ◽  
End User ◽  
User Interactions ◽  
Model Interpretation ◽  
Autonomous Surface Vehicles ◽  
Research Activities ◽  
Explainable Artificial Intelligence ◽  
Carry Over

Explainable Artificial Intelligence (XAI) for Autonomous Surface Vehicles (ASVs) addresses developers’ needs for model interpretation, understandability, and trust. As ASVs approach wide-scale deployment, these needs are expanded to include end user interactions in real-world contexts. Despite recent successes of technology-centered XAI for enhancing the explainability of AI techniques to expert users, these approaches do not necessarily carry over to non-expert end users. Passengers, other vessels, and remote operators will have XAI needs distinct from those of expert users targeted in a traditional technology-centered approach. We formulate a concept called ‘human-centered XAI’ to address emerging end user interaction needs for ASVs. To structure the concept, we adopt a model-based reasoning method for concept formation consisting of three processes: analogy, visualization, and mental simulation, drawing from examples of recent ASV research at the Norwegian University of Science and Technology (NTNU). The examples show how current research activities point to novel ways of addressing XAI needs for distinct end user interactions and underpin the human-centered XAI approach. Findings show how representations of (1) usability, (2) trust, and (3) safety make up the main processes in human-centered XAI. The contribution is the formation of human-centered XAI to help advance the research community’s efforts to expand the agenda of interpretability, understandability, and trust to include end user ASV interactions.

The Impact of Chatbots in Driving Digital Transformation

2021 ◽  
Vol 13 (4) ◽  
pp. 88-104
Author(s):  
Hyrmet Mydyti ◽  
Arbana Kadriu
Keyword(s):  
Artificial Intelligence ◽  
Natural Language Processing ◽  
Language Processing ◽  
Business Processes ◽  
Evaluation Criteria ◽  
Digital Technologies ◽  
Digital Transformation ◽  
Call Centres ◽  
Reducing Costs ◽  
The Impact

Digital transformation is the process of consuming digital technologies that drives business improvements and customer experience. Artificial intelligence plays a crucial role in businesses' digital transformation agendas. Technologies and algorithms are an important perspective in the implementation of chatbots. AI chatbots use natural language processing technology and offer solutions for modernizing traditional business processes. The key advantage of the implementation of chatbots in different domains is the impact by improving customers' experience and reducing costs. Chatbots are pieces of software that simulate human conversation through voice commands and/or text chats, intending to offer companies an approach on how to use this software to revolutionize their businesses. The aim of this paper is the analysis of the evaluation criteria; the study of insights into how chatbots can be implemented in the domains of banking, e-commerce, tourism, and call centres; and the discussion of some benefits and challenges of chatbots in driving the digital transformation of businesses.

Reports of the Workshops Held at the 2019 AAAI Conference on Artificial Intelligence

AI Magazine ◽  
2019 ◽  
Vol 40 (3) ◽  
pp. 67-78
Author(s):  
Guy Barash ◽  
Mauricio Castillo-Effen ◽  
Niyati Chhaya ◽  
Peter Clark ◽  
Huáscar Espinoza ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Language Processing ◽  
Cyber Security ◽  
Question Answering ◽  
Intent Recognition ◽  
Affective Content ◽  
Learning Plan ◽  
Dialog System ◽  
Affective Content Analysis ◽  
Games And Simulations

The workshop program of the Association for the Advancement of Artificial Intelligence’s 33rd Conference on Artificial Intelligence (AAAI-19) was held in Honolulu, Hawaii, on Sunday and Monday, January 27–28, 2019. There were fifteen workshops in the program: Affective Content Analysis: Modeling Affect-in-Action, Agile Robotics for Industrial Automation Competition, Artificial Intelligence for Cyber Security, Artificial Intelligence Safety, Dialog System Technology Challenge, Engineering Dependable and Secure Machine Learning Systems, Games and Simulations for Artificial Intelligence, Health Intelligence, Knowledge Extraction from Games, Network Interpretability for Deep Learning, Plan, Activity, and Intent Recognition, Reasoning and Learning for Human-Machine Dialogues, Reasoning for Complex Question Answering, Recommender Systems Meet Natural Language Processing, Reinforcement Learning in Games, and Reproducible AI. This report contains brief summaries of the all the workshops that were held.

Economic Mechanism for Managing the Communication Business Process of Industrial Enterprises in the Context of Globalization

2020 ◽  
pp. 63-73
Author(s):  
Konstyantyn Yu. Zavrazhnyi
Keyword(s):  
Economic Policy ◽  
Corporate Culture ◽  
Business Processes ◽  
Market Competition ◽  
Effective Interaction ◽  
Psychological Impact ◽  
Foreign Economic Policy ◽  
Economic Mechanism ◽  
Industrial Enterprises ◽  
Definition Of

The paper provides a definition of the economic mechanism for managing the communication business processes of industrial enterprises in the context of globalization as a set of a system of relations, authorities, forms and methods of organization and operation, which are regulated by legal and other norms of activity and provide effective interaction in internal and external environments. This allows to deepen the understanding of the essence in the context of globalization under the orientation towards communication (we mean interaction first of all). The composition of the comprehensive economic mechanism for managing the communication business processes of industrial enterprises is studied. This mechanism includes organizational, economic, legal, political, technical and technological, market, production, social, motivational, adaptive and communication submechanisms. This allows further formalization of the process of elemental improvement of the communication business processes of industrial enterprises. The components of mechanism are detailed. In particular, the economic submechanisms include the mechanisms of profits distribution, economic stimulus, financial, equity, investment and reinvestment in development and other mechanisms. The legal submechanisms include the mechanisms, which govern communication and professional legal relations. Organizational submechanisms include structural mechanisms, administrative and information mechanisms that ensure the development and modernization of communication activities at the enterprise, its information security. Political submechanisms include mechanisms of information policy, social and economic policy and foreign economic policy. Market submechanisms include the ones of market competition, demand and supply, etc. Social submechanisms include the ones of transparency of doing business, social responsibility, social and psychological impact, etc. Production submechanisms include the following ones: resource, implementation of new types of software and hardware and other. Technical and technological submechanisms include the ones of scientific and technological progress, technological updates. Motivational submechanisms include the mechanisms of material and non-material incentives of personnel. Adaptive submechanisms are the submechanisms of innovative development (including implementation of innovations in information field), managing the personnel potential, etc. Communication submechanisms include the ones of information-and-analytical activities (including research conducting); external communications (including the system of integrated communications tools, modern telecommunications and communications facilities); internal communications (including creating corporate culture). Key words: economic mechanism, submechanisms, management, communications, business processes, industrial enterprise.

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