In this Harvard article: How data science can benefit your business decisions | Harvard Online, the author discusses how companies implement data science and AI to improve business decisions. Considering this content, try to write a personal diary in which you reflect on the technological product/systems/services you interact with every day and try to understand which models is behind. Here below, please find more detailed suggestions on how to draft the diary:  

  1. The objective is to keep an AI diary 
  2. Over the next days, take note of at least ten applications, products, or systems that you interact with that you believe incorporate AI, machine learning, or predictive modeling. These could be mobile apps, websites, smart devices, recommendation systems, social media algorithms, voice assistants, financial tools, or automated services in physical shops etc. 
  3. Try to classify eachsystem using the concepts you learned in the module 

For each system you identify, analyze it based on the following dimensions: 

  • Type of AI Model: Is it Predictive AI (making forecasts or recommendations) or Generative AI (creating new content or responses)? 
  • Learning Approach: Is it using Supervised Learning (trained on labeled data), Unsupervised Learning (discovering patterns from unlabeled data), or another approach (e.g., Reinforcement Learning, Semi-supervised Learning)? 
  • Data Type: Does it work primarily with structured data (e.g., spreadsheets, databases) or unstructured data (e.g., images, videos, text, speech)?

4. Analyze the Purpose and Impact of the technology BOTH from your side (user) and from the company side 

Reflect on the business or functional intent behind these AI-driven systems. For each system, consider the following: 

  • Why do you think the AI model was developed? (e.g., personalizing recommendations, optimizing search, automating tasks, improving efficiency) 

  • How does it impact your experience? (e.g., does it make things easier, more engaging, or possibly introduce bias or manipulation?) 

5. Write a Short Reflection 


After completing the listing summarizing your observations answering this questions: 

  • What surprised you about the AI-powered systems you use daily? 
  • Did you find any unexpected AI integrations in your routine? 
  • How do you feel about the level of AI involvement in your daily life? 
  • Do you think these systems are transparent about their AI usage? 

Use this short example as a guide 


  • App: Spotify 
  • AI Model Type: Predictive AI 
  • Learning Approach: Supervised & Unsupervised Learning (collaborative filtering and deep learning for audio features) 
  • Data Type: Structured (user behavior, song metadata) + Unstructured (audio analysis) 
  • Why was it developed? To recommend personalized music and improve user engagement.
  • Impact on experience: Makes discovering new music easy but sometimes limits exploration outside of preferred genres.