Various Artificial Intelligence in Information Systems

In recent years, the popularity of artificial intelligence has skyrocketed. It can be indicated with many AI that appears like fylm.ai to do colour grading and DALL-E, an AI to draw what we write. Artificial Intelligence (AI) is a branch of computer science that deals with creating machines that can perform tasks that usually require human intelligence, such as understanding natural language, recognizing images, and making decisions. This definition highlights the main idea of AI as a field of study that aims to create intelligent machines that can perform tasks that would otherwise require human intelligence. In information systems, AI analyses large sets of data, understands natural language, and makes decisions. It can include applications such as data mining, natural language processing, and decision support systems. 

Many reasons make the author use this topic: AI capabilities, such as machine learning, natural language processing, and computer vision, are now being increasingly implemented to optimize information systems. For instance, AI can help identify and address problems quickly and detect and respond to cyber threats and other abnormal behaviours. The potential for AI to revolutionize information systems is immense, and its impact on the field will likely continue to grow. 

The author uses this topic to open the minds of the higher-ups to implement AI in their businesses. There are many benefits to it. AI can be used to automate daily tasks that require the processing of large amounts of data. AI can also offer powerful predictive analytics to help organizations make more informed and effective decisions. Therefore, AI will free up human resources to focus on more complex tasks. It can increase the efficiency and effectiveness of the human resources. 

The things that the author will discuss are as follows. 

1. Strong AI vs Weak AI 

Strong AI refers to a type of AI that can perform many different tasks and learn in the same way humans do, through experience. Examples of strong AI are currently theoretical and do not currently exist. Strong AI is defined as a type of AI that can perform any intellectual task that a human being can, and this level of intelligence has yet to be achieved in any AI system. Research towards this goal is ongoing. 

Weak AI refers to a type of AI that is designed to perform a specific task. This type of AI currently exists and is used in various applications. Examples of weak AI are image recognition systems, language translation systems, and virtual personal assistants. These examples illustrate AI systems specifically trained and designed for a particular task, as opposed to strong AI, which would have general intelligence to perform any intellectual task that a human can. 

 2. Good AI vs Bad AI 

Good AI in business refers to the use of AI in a way that is ethical, responsible, and aligned with the values and goals of the business. Several key factors contribute to good AI in business: 

• Ethics: It should be designed and used in a way that is ethical and responsible. It includes considering the potential impacts of AI on employees, customers, and society and ensuring that AI is not used to discriminate or unfairly advantage certain groups. 
• Transparency: It should be transparent, meaning that the algorithms and processes used should be explainable and understandable. It helps ensure that AI is used in a fair and accountable way. 
• Alignment with business goals: It should be used to achieve specific business goals rather than simply as a technology for its own sake. It helps ensure that AI is being used in a meaningful and valuable way to the business. 
• Inclusivity: It should be inclusive, meaning that it should consider the needs and perspectives of all stakeholders, including employees, customers, and society as a whole. 

There are several examples of bad AI where the technology has had unintended or negative consequences: 

• Bias in AI algorithms: AI algorithms can sometimes perpetuate or amplify existing biases in the data they are trained. For example, facial recognition software is less accurate for people with darker skin tones, leading to potential discrimination. 
• Misuse of AI: AI can be used for nefarious purposes, such as spreading misinformation or manipulating public opinion. 
• Unintended consequences: AI can sometimes have unintended consequences, such as when autonomous vehicles have caused accidents or AI-powered algorithms have made decisions that negatively impact individuals or groups. 
• Lack of transparency: AI algorithms that are not transparent or explainable can be difficult to understand or scrutinize, leading to mistrust and a lack of accountability. 

3. AI Application in Functional Area 

• Finance & Banking: AI can help with fraud detection, risk management, payment processing and streamlining processes that currently take up time and resources while increasing efficiency across the board. 
• Supply Chain & Logistics: AI has already optimized warehouse operations by eliminating human error using intelligent robots who know precisely how much to order from suppliers based on demand. It helps save money because it is not ordering too much or too little product, which is wasted if it does not sell quickly enough for customers who want them now when there is nothing else available in their inventory. 
• Human Recourse: AI can analyze job candidates’ qualifications data so recruiters don’t miss out on great talent just because they cannot see beyond someone’s resume. Recruiters could use this information instead of relying solely on gut instinct when deciding whether a candidate would make a good employee; they will also spend less time interviewing candidates who are not qualified, instead focusing only on those applicants who are worth interviewing further. 
• Marketing: AI can analyze customer data to understand better how they respond to specific messages or sales tactics. This information can then be used in marketing campaigns so that companies do not waste money on ineffective ads that get customers through the door and into their stores. 

Artificial Intelligence (AI) has dramatically impacted the field of Information Systems. AI can play a significant role in solving various problems in information systems, such as improving efficiency, reducing costs, and driving revenue for businesses. It is essential for businesses to carefully consider how they can use AI in an ethical way that aligns with their values, and to ensure that they have the necessary infrastructure and resources to implement and manage AI technologies effectively. AI is continually developing and has great potential across many sectors, allowing new and innovative ideas to be implemented in how we manage and process information. 

AI can automate and streamline many practical tasks traditionally associated with information systems, such as data management and analysis, and provide insights into customer behaviour and trends. Furthermore, AI is being used to develop sophisticated algorithms that can help improve decision-making processes and enhance customer service, and it can be used to anticipate future trends and customer needs. As AI continues to evolve and become more sophisticated, it will continue to improve the efficiency and effectiveness of information systems. AI is an invaluable asset for businesses and will become increasingly important in the future, as it is able to provide insights that are not possible with traditional methods. 

REFERENCES 

• Russell, S. J., & Norvig, P. (2020). Artificial intelligence: A modern approach (4th ed.). Prentice Hall. 
• Collins, C., Dennehy, D., Conboy, K., & Mikalef, P. (2021). Artificial intelligence in information systems research: A systematic literature review and research agenda. International Journal of Information Management, 60, Article 102383. https://doi.org/10.1016/j.ijinfomgt.2021.102383