The Truth about AI in the Workplace
AI or Artificial Intelligence (AI) is the buzzword for 2023. But what do you really know about the truth about AI? What is it all about? What are the risks and benefits of having AI in the workplace? This article hopes to shed light on how Philippine companies can benefit from AI and manage the risks involved in adopting it in the Filipino workplace. What is Artificial Intelligence? AI can be defined as: The ability of a computer system to perform tasks commonly associated with intelligent beings. It applies to developing systems endowed with the intellectual processes of humans: Inherent to most AI systems is the ability to LEARN. Referred to as Machine Learning, this pertains to the computer program’s ability to generate insights or predict outcomes based on the data it is provided. For example, a computer program will know what a cat looks like by looking at hundreds, if not thousands, of photos of cats. ChatGPT was trained on at least 570GB of text gathered from the Internet. While some AI can learn by itself, most AI applications were trained by dozens or even hundreds of people. History of AI Types of Artificial Intelligence Narrow AI (Weak AI) Narrow AI refers to AI systems that are designed to perform specific tasks or functions within a limited domain. These systems are focused on excelling at a particular task rather than possessing general intelligence. Narrow AI is the current form of AI in use today and is applied in various industries such as healthcare, finance, and transportation. General AI (Strong AI) General AI refers to AI systems that possess the ability to understand, learn, and apply knowledge across a wide range of tasks and domains. Unlike Narrow AI, General AI aims to exhibit human-like intelligence and cognitive abilities. It would have the capacity to understand natural language, reason, learn from various sources, and perform tasks across diverse domains. As of 2023, General AI is yet to be achieved. Examples of Narrow AI Speech Recognition: Detecting and analyzing what a human is saying and converting it to actions/text. Examples: Amazon Alexa, Apple Siri, Google Assistant Natural Language Processing (NLP): NLP involves the understanding and interpretation of human language. Includes determining intent, sentiment, meaning, etc. Examples: IBM Watson, ChatGPT Computer Vision and Image Recognition: Enabling machines to understand and interpret visual information. Examples: Tesla Autopilot, Google Lens Recommendation Systems: Analyzes and cross-references user preferences and behavior and predicts/suggests products that the user might like. Examples: GoogleAds, Facebook, TikTok, Netflix, Amazon, etc. Benefits of AI AI offers several benefits across various domains. One of the key advantages is improved efficiency. By automating repetitive and time-consuming tasks, AI frees up employees to concentrate on more strategic work. This increased efficiency not only leads to higher productivity but also brings about significant cost savings. For instance, AI-powered chatbots, automated data analysis, and document processing are examples of how AI streamlines operations and enhances efficiency in different industries. Another benefit of AI is its ability to enhance decision-making processes. AI provides data-driven insights and analysis, enabling better-informed decisions. Through predictive analytics and machine learning algorithms, AI can identify patterns and trends in vast datasets, enabling organizations to make informed decisions promptly. Real-time data analysis is particularly valuable, as it empowers businesses to stay agile and respond to changing circumstances. Examples of AI-driven decision-making include recommendation engines used in social media and e-commerce websites, which offer personalized suggestions to users based on their preferences and behaviors. AI also contributes to increased accuracy and precision in tasks. AI systems can perform operations with minimal errors, eliminating human errors and biases that can impact outcomes. This is particularly relevant in fields such as automated quality control, image recognition, and natural language processing, where AI algorithms can achieve high levels of accuracy and consistency. Furthermore, AI plays a crucial role in improving customer experience. By analyzing user data and preferences, AI enables personalized experiences. Recommender systems, for instance, suggest relevant products, services, or content based on individual preferences, enhancing customer satisfaction and engagement. Additionally, AI can assist human representatives in real-time interactions, ensuring seamless customer engagement and addressing inquiries promptly. Lastly, AI drives workplace innovation by augmenting human workers. With AI-assisted systems, employees can focus on the creative, intellectual, and innovative aspects of their work. AI acts as a powerful tool to support and amplify human capabilities, allowing workers to explore new possibilities and push the boundaries of their roles. The uses of AI systems, such as ChatGPT, are only limited by the user’s imagination, highlighting the potential for innovation and transformation in the workplace. Risks of AI The widespread adoption of artificial intelligence (AI) poses several risks that need to be addressed. One significant concern is the potential disruption to the workforce. As AI technology advances, there is a growing risk of automation replacing low-skilled and repetitive jobs. This could lead to the redundancy of workers who perform tasks such as first-line customer support, transcription, and inventory management. To mitigate this risk, it is crucial for workers to upskill and reskill themselves to effectively leverage AI in their respective roles and maximize its benefits. Another important risk associated with AI is the potential for bias and discrimination. AI systems rely on training data, and if the data contains inherent biases, the AI algorithms may perpetuate and amplify these biases. This can result in discriminatory outcomes in areas such as hiring, promotions, and customer interactions. It is essential to address these biases and ensure that AI systems are designed and trained in a way that promotes fairness and equality. Privacy and security concerns also arise with the use of AI. The collection, storage, and processing of personal and sensitive data by AI systems raise concerns about data protection. There is a risk of data breaches, unauthorized access, and misuse of information, which can have serious implications for individuals and organizations. Appropriate measures need to be taken to safeguard data and ensure that AI systems comply with privacy regulations. Lack