Introduction to AI

Artificial Intelligence (AI), is a rapidly-advancing field of computer science that has the potential to transform the way we live, work, and interact with technology. At its core, AI seeks to create intelligent machines and systems that can perform tasks that typically require human intelligence. While AI is an incredible tool for increasing productivity and making tasks easier, it is important to recognize that AI cannot replace the need for human involvement and oversight. As we move forward into a future with AI, workplaces will likely evolve to have staff work collaboratively with AI to achieve business goals.

In this introductory guide to AI, we will explore the fundamental concepts, limitations and real-world applications of artificial intelligence.

Machine Learning

Machine Learning is a subset of AI that focuses on the development of algorithms and statistical models to enable computers to make improved predictions or decisions from data without being explicitly programmed. An example of this is when you tell an AI system if it's response or prediction was appropriate, by liking it or clicking a thumbs-up icon. Algorithms then take this "good" response into account when answering future requests. Machine learning helps improve user experience by producing more favourable outputs through human refinement.

You have likely run into examples of Machine Learning models in your daily activities from email/text spam detection and show/movie recommendations from streaming platforms.

AI Chatbots use artificial intelligence techniques and technologies to generate human-like responses based off of the data it's trained on. These AI Chatbots may also apply Machine Learning to further improve their performance and responses over time.

Limitations of AI

While AI has made remarkable strides in automating various tasks and processes, it is important to remember that AI responses are only as good as the data it was trained on. There are several reasons why it cannot entirely replace the need for humans to be involved in many aspects of work and decision-making. Some key reasons being:

  1. Complex Problem-Solving: AI excels at solving well-defined and structured problems. However, it struggles with unstructured, novel, or ill-defined problems that require critical thinking, adaptability, and the ability to analyze information from diverse sources. Think of how a business tries to predict market behaviour. They often consider factors that are not easily captured in figures or metrics that could be ingested by AI such as, current news or social trends.

  2. Lack of Common Sense and Contextual Understanding: AI systems operate based on algorithms and data. They lack common sense reasoning and the ability to understand contextual nuances the way humans do. They may struggle to provide appropriate guidance for situations that require a deep understanding of human emotions, behaviour, cultural sensitivities, or rapidly changing environments. This may be true when trying to use AI to create business processes that rely on people to behave in specific ways. It may be able to provide general guidance that fits the ideal or common cases, but neglects the edge cases that businesses often have to think of and prepare for.

  3. Human Interaction and Empathy: Certain tasks, particularly in fields of customer service and sales, greatly benefit from and require a level of human interaction and empathy. People often prefer speaking to humans for their capablity to understand diverse perspectives, sensitivity to emotional factors and compassion for extenuating circumatnces. This makes human involvement essential for creating customers that feel valued and heard.

  4. Ethical and Moral Decision-Making: Many tasks and decisions involve complex ethical and moral considerations. AI systems do not have the capacity for moral reasoning and cannot make value-based judgments. Decisions in fields like healthcare, law, and social work often require ethical judgment, empathy, and human discretion.

  5. Cultural and Social Bias: AI can inadvertently perpetuate biases present in the data it is trained on. Humans have a better understanding of current cultural, social, and historical contexts, which can be critical in making fair and equitable decisions.

  6. Creativity and Innovation: While AI can assist in generating ideas and patterns, true creativity and innovation often stem from human's ability to think outside the box. AI can support creative processes but cannot create entirely new concepts and inventions in the same way humans can.

  7. Adaptability: While AI can learn from data, it does not possess the same level of adaptability and the ability to learn from diverse experiences as humans do. Humans can apply their knowledge and skills to new and unexpected situations making rapid decisions and thinking on their feet. AI systems may struggle in such unpredictable scenarios where they are not privy to the latest information and lack the full situational context.

  8. Accountability and Responsibility: When things go wrong, it is crucial to have humans in the loop to take responsibility, be accountable, and make judgment calls. AI systems can make errors, but humans are responsible for designing, monitoring, and correcting them. It is important for humans to be reviewing and monitoring processes being automated by AI to ensure users are getting appropriate and consistent results.

In summary, AI lacks certain essential qualities that make humans irreplaceable in numerous roles. Leveraging AI with an understanding of it's limitations will allow you to effectively and responsibly use it for your tasks and to create more efficient and effective processes.