Foundational Explanations: Understanding AI

What is AI?

Artificial Intelligence (AI) refers to computer systems designed to perform tasks that typically require human intelligence. These tasks include problem-solving, pattern recognition, decision-making, and language understanding. AI is built on algorithms that allow machines to process data, recognize trends, and adapt based on experience.

AI can be classified into different types:

• Rule-Based AI: Operates on predefined rules and logic (e.g., simple chatbots, automated scheduling tools).

• Machine Learning (ML): Improves performance through data analysis and pattern recognition (e.g., AI swing analysis tools).

• Deep Learning: Uses neural networks to mimic human thinking (e.g., advanced motion capture for golf swings).

Successful Examples of AI in Teaching & Athletics

AI is already transforming both education and sports coaching. Here are some notable examples:

Teaching & Education

• Khan Academy’s AI Tutor – Adapts lessons based on individual student needs.

• Duolingo – Uses AI to modify lessons based on language proficiency.

• ChatGPT in Classrooms – Helps educators create lesson plans, quizzes, and provide instant feedback.

Athletics & Coaching

• Trackman & Sportsbox AI (Golf) – AI-driven tools that analyze swing mechanics and provide real-time feedback.

• OnForm – AI-assisted video analysis for coaches and athletes.

• Mizuno Shaft Optimizer-”The Shaft Optimizer is a hittable seven iron, with internal strain gauges, micro-processors and a gyro – that combine to capture over 40 unique swing data points. Measuring how players load and unload the shaft during their swing.
  The swing data is sent via Bluetooth from the Optimizer to the Swing DNA app, where it maps out your entire bag.” Mizuno

• Wearables such as Whoop, Oura, Smartwatches – AI-powered wearable technology tracking athlete recovery and performance. “They’re evolving into AI-driven health coaches, assistants, and personal trainers, learning from your habits and delivering insights that actually matter and help improve your life.” Yahoo Tech

• IBM Watson in Tennis – Analyzes player movements, strategies, and opponent tendencies to optimize game plans.

• IBM Watsonx at The Masters-”IBM uses watsonx to manage the entire lifecycle of generative AI models that instantly reveal the risks and rewards for every shot on every hole at the Masters.”

Hazards of AI in Teaching & Athletics

Understanding the pros and cons of AI is imperative

Teaching & Education

• Keiser University –Artificial Intelligence and the Emotional Truth, Professor Rebecca Jensen explains the importance of students developing critical thinking skills and “emotional truth” in writing which allows for freedom of thought and perhaps mistakes.

• Georgetown School of Foreign Service – Andrew Imbrie, Associate professor of Emerging Technology at Georgetown’s School of Foreign Service explains the Five Key Issues to Watch in AI in 2025 and explains though AI may hallucinate, use synthetic data, and reflect our biases, it can also facilitate, empower and help innovate. Ultimately, he thinks now is the time for students to switch their majors to AI and International Affairs.

• Cognitive Resonance– Education hazards posed by AI is a scientific overview by the writers and thinkers at CR. Their warning is that administrators and policymakers “should not invest time and resources to incorporate AI in schools based on assumptions about what the future will bring. Nor should they drastically alter curricula to prepare students for an “AI world.” We simply do not know what such a world will look like or what it will require of future citizens.

What is an AI Agent?

An AI Agent is a system designed to sense its environment, process data, and take actions to achieve a goal. It operates by receiving input, analyzing it, and making decisions based on predefined rules or learned behaviors.

AI Agents can be:

• Reactive: Responding to real-time inputs (e.g., AI chatbots providing instant answers).

• Proactive: Predicting and making decisions ahead of time (e.g., AI suggesting training plans based on athlete data).

Examples of AI Agents in Sports & Coaching and Golf

• Chatbots & Virtual Assistants – Tools like ChatGPT help coaches develop lesson plans, provide feedback, and assist with scheduling.

• Golf Swing Analyzers – AI-powered systems that track swing mechanics and suggest improvements.

• Chip In (Julieta Stack’s AI Teaching Assistant) – Designed to help coaches streamline curriculum design, lesson planning, and student progress tracking.

  (Imagine if my Chip In model was developed by a team of the best professionals in golf coaching, exercise, rehab, mental game, club builders, fitters, course designers, players? That is where the LPGA or PGA could play a big part.)

Additional Concepts to Understand Before Diving In

Machine Learning vs. Traditional Programming

• Traditional Programming: Systems operate based on predefined rules (e.g., a golf simulator programmed to show ball flight paths based on input conditions).

• Machine Learning: Systems learn and improve from data (e.g., AI predicting swing adjustments based on thousands of previous shots).

Bias & Limitations in AI

AI is only as good as the data it’s trained on. If AI systems are fed biased or incomplete data, they may produce inaccurate or misleading recommendations. Coaches and educators should always combine AI insights with human expertise.

University of Illinois College of Education -The Office of Online Programs explains that “To best use AI in schools, teachers and administrators need to know AI’s advantages and challenges.” This applies to the world of coaching golf as well.

AI’s Role in Coaching vs. Human Expertise

AI is a powerful enhancement tool, but it does not replace the experience, intuition, and emotional intelligence of a great coach. The best results come from AI and human coaching working together—leveraging AI for data-driven insights while using human expertise to personalize instruction and mentorship.