Stone Soup and Data Science
I've worked as a Data Scientist for several years and cooperated with non-technical people. Those experiences remind me that "Stone Soup," a folk story, has a profound insight into working as a Data Scientist. Let me share this story and my thought.
For the sake of a delicious meal
For those who don't know this story, here is the story from Wikipedia.
Some travelers come to a village, carrying nothing more than an empty cooking pot. Upon their arrival, the villagers are unwilling to share any of their food stores with the very hungry travelers. Then the travelers go to a stream and fill the pot with water, drop a large stone in it, and place it over a fire. One of the villagers becomes curious and asks what they are doing. The travelers answer that they are making “stone soup”, which tastes wonderful and which they would be delighted to share with the villager, although it still needs a little bit of garnish, which they are missing, to improve the flavor.
The villager, who anticipates enjoying a share of the soup, does not mind parting with a few carrots, so these are added to the soup. Another villager walks by, inquiring about the pot, and the travelers again mention their stone soup which has not yet reached its full potential. More and more villagers walk by, each adding another ingredient, like potatoes, onions, cabbages, peas, celery, tomatoes, sweetcorn, meat (like chicken, pork and beef), milk, butter, salt and pepper. Finally, the stone (being inedible) is removed from the pot, and a delicious and nourishing pot of soup is enjoyed by travelers and villagers alike. Although the travelers have thus tricked the villagers into sharing their food with them, they have successfully transformed it into a tasty meal which they share with the donors.
This story has several variations, yet we can find some insight.
- Villagers have enough resources to make delicious food, but no one can be aware of the possibility.
- Travelers have the ability to create a soup, but it won't help if they don't have enough resources.
- Delicious soup can be made only if villagers and travelers work together.
Build a fellowship
During our data science project, we often face various hurdles to achieving our goal. It is sometimes a technical matter and sometimes a business matter. Especially for a business, we may have a chance to work with non-technical people and possibly need to convince them. It may become laborious and time-consuming if they are unwilling to work with you proactively.
At such times, we can remember what travelers did to make a great soup. Travelers showed the possibility to villagers by demonstrating with a stone and water. They convinced each villager and led to achieve the big picture.
In the same way, we data scientists can build a fellowship with non-technical people to accomplish our goals together. We ask about their most painful issue to clarify our goal. We create a prototype for them to imagine how beneficial it is. Then we can convince them to extract data or provide domain-specific information like the soup's ingredients to make the product more meaningful. The more elements we can add to our product, the more people we can cooperate with in the same direction, and the faster we can move the project forward.
Conclusion
In the end, it has long been said that machine learning needs to be implemented in society. Still, it depends on how we can translate AI technology to business value for non-technical people and how valuable the big picture we can draw for them is.
As an aside, I saw this folk tale in the book "Pragmatic Programmer." This book is for software engineers, but it's full of insight so I would recommend it to data scientists.
