Understanding Artificial Intelligence (AI)

What is Artificial Intelligence?

Artificial Intelligence (AI) refers to systems or machines designed to mimic human intelligence. These systems can perform tasks such as learning, reasoning, and decision-making, which are typically associated with human cognition. AI enables computers and software to process data, identify patterns, and provide recommendations, enhancing efficiency and productivity across various sectors.

According to Stanford University's IT department, the primary goal of AI is to develop machines that operate independently, adapt to new situations, and improve over time. This technology has significant implications for industries like healthcare, finance, and transportation, where AI can streamline operations and enhance decision-making processes.

Defining AI

Despite its widespread use, there is no universally accepted definition of AI, which can lead to confusion and complicate regulation. A broad definition might include simple tools like Microsoft Excel, which performs automated tasks. AI has been integral to technologies such as email spam filtering, language translation, music recommendations, and credit card fraud detection for years.

As AI tools become more common, they often blend into the background, becoming seamless parts of everyday life. This integration highlights the pervasive influence of AI in modern technology.

Generative AI

Generative AI represents a significant advancement in the field. This technology can create content, including text, images, video, and audio. The emergence of generative AI gained widespread attention with the release of OpenAI's AI chatbot, ChatGPT, which demonstrated the potential of general-purpose AI with a broad range of knowledge.

Users interact with generative AI by typing commands in plain English, providing the AI with the necessary inputs to create content. This user-friendly approach makes generative AI accessible to anyone familiar with internet search or online messaging tools. The results can be refined continuously through additional notes and questions, allowing for iterative improvements.

Generative AI is built on large language models (LLMs), which are trained on vast amounts of data and computing power. These models learn language patterns to predict the next word, enabling the creation of various content types, from research reports to data analysis. LLMs can also be trained on images and videos to generate photos, movies, or 3D games. Another application is debugging and generating computer code.

Tech giants are investing in AI data centers to train and run internal AI models and host AI cloud computing for customers. Many in the tech industry view generative AI as the next major technological platform, with the potential to revolutionize various sectors.

AI Risks

While AI offers numerous benefits, it also presents risks, including bias, privacy, and security threats. Generative AI introduces unique risks, such as the creation of false content, known as hallucinations. AI chatbots can leak private data, offer dangerous recommendations, or infringe on intellectual property. Companies developing AI tools are working to mitigate these risks, especially in high-stakes environments.

Criminals and foreign actors can exploit generative AI to mass-produce online spam, email phishing scams, propaganda, and misinformation at low cost. This underscores the need for robust guardrails to ensure the responsible use of AI.

AI in Finance

Financial services companies leverage AI to process customer calls, fight fraud, create marketing materials, forecast sales, interpret regulations, and understand tax laws. Employees use AI to address IT issues, manage health benefits, and respond to client inquiries. Customer assistants powered by AI have been used billions of times, highlighting their effectiveness.

Nearly half of consumers are considering using generative AI tools for personal finances, trusting them as much or more than human advisors. An investing app plans to launch an AI virtual assistant for subscribers, demonstrating the growing integration of AI in financial services. The CFP Board has published a guide on generative AI for Certified Financial Planners, addressing ethical issues and noting that generative AI can assist with tasks such as summarizing client meeting notes and refining marketing materials.

However, the guide emphasizes that financial advisors are responsible for the final work product, as generative AI can produce inaccurate information. AI chatbots are also being used to pick stocks, but users must be cautious about sharing sensitive financial information and verifying the accuracy of AI-generated recommendations.