I have made several previous attempts to make an app that help people to find their perfect house. In fact, my first data science project was to find a home that fit people’s needs. My first attempt was to find an apartment in New York City. There were so many people doing that. My top worry was about crime. As I moved out of NYC and into the suburbs of other states, school district became a more important factor. Doesn’t matter how I approach the problem, nothing beats seeing the pictures and actually visit the house. So here is my latest attempt to do that. Just a few simple filters to knock the choices down to a few. If you happen to use the app, drop a comment on how it worked for you.
Since my last post about Decision Stories. posted here, I received some feedback about the usefulness of Decision Stories as a product. The main critique is about the ease of use and adoption of this tool. First, it’s not easy to use. As in people need to invest too much effort in thinking about how they made decisions before. And sometimes it’s not easy for the person to recall how they made the decision. They might not be aware the process even if they try to recall. So there needs to be processes to guide for the user to think about how they make those decisions. I will expand these ideas in a later post.
What I want to talk in this post is about is the second point and possible pivots. And that is not a lot of people are making life changing decisions in their personal life. If not many people are using the product on a daily basis, it’s even harder for them to justify the initial investment of effort to record their decisions.
One of the suggestions is to use this tool to help mid-level managers to make everyday decisions, so they can spend more time on other tasks such as personal and employee development. There are potential benefits to this approach. Most decisions made by mid-level managers involve technical decisions that have data to back it up. These decisions are more quantifiable and involve less “gut feeling”. It’s easier for the model to pick up quantifiable features and make reliable predictions.
The type of decisions made by mid-level managers are more homogenous. For example, a customer service call center manger generally worries about the average handle time of calls, and don’t worry about marketing strategies of product lines. Whereas an executive manager needs to think about how the change in product line will impact the type of customer service changes in call centers branch of the customer service organization. And since a consistent decision type will more likely generate accurate decision predictions, this is more likely to work for mid-level managers and not executive levels.
A bonus for the mid-level managers to have consistent decisions is clarity in management expectations. If the managers are comfortable to share the predictions, it could be used to manage expectations within their department. For example, if the employees knows exact how their manager is going to react to a specific scenario, they could adjust their expectations accordingly and synchronize efforts to maximize results. This of course needs trust building between the manager and their direct reports prior to deployment. Ironically, well trusted teams probably already have clear expectations between team members. It’s the new team members that need help the most.
And of course we have to mention that any model prediction involving human decisions requires sanity checks. Blindly trusting a model decision without thinking about consequences invites disasters. Before people start using this more or less automatically, both the manager and their direct reports needs to understand the risk. And if they don’t feel comfortable using the tool, they should be compelled to use it.
I’m interested in what other pros and cons about this application people can think of. I would love to hear any suggestions!
About a month ago, I introduced an idea I had about retaining the intelligence of a human. Rather than building an AI to mimic humans, I want to capture how a human would make decisions. Because I think the decisions we made say a lot about who we are as a person.
So I went after the idea and developed a prototype. I wrote some decision stories or scenarios in life where one needs to make a decision. The decisions have the potential to shape who we are as a person. Each decision story has 4 choices one can choose from. They are not black-or-white decisions. Each decision could be a valid choice, depending on how the person chooses to live their life. Once the person made enough choices from various decision stories, the algorithm could help the person make a choice on a never seen scenario. This could help us make decisions in the event we are either unsure or don’t want emotion to influence our decisions. Or if we recorded the decisions of our role models and would like to know what decisions would they make in the same situation. You can actually ask, “What would X do?”. This is still a work in progress, so I’m just piecing together many parts as we go.
The backend uses a model to summarize how the person made decisions before. And come up with a generalization of the person’s profile. Then use the profile to guide future decisions.
The steps to do this are as follows:
First, go to this page to log in. https://www.panzoto.com/login/. This is used to track the decisions you made based on premade stories.
Then go to this page to make as many decisions as possible. https://www.panzoto.com/add-decision/. I recommend at least 10 decisions, but it will work with just one decision if making decisions is inherently difficult.
Then go to this page to type in the decision you would like to make. You can either provide several choices or simply ask a question. The model will return the choice number, or make up some reasonable choices based on the decisions you made before. https://www.panzoto.com/make-a-decision/.
If you like to submit more stories to help to expand the decision story repository. Please submit those on this page. https://www.panzoto.com/submit-your-decision-story/. Keep in mind to use gender-neutral references when building your story. Refrain from including personal detail in the stories. Make the stories as generic as you can. The stories will be approved by a human.
DISCLAIMER: By using this service, you assume the potential risk of asking a computer model to make suggestions to you. This is meant to be helpful and not inflict harm. It should be used in the case where you seriously considered the pros and cons of at least 2 decisions, but were still unable to make the decision because of your emotion. Please don’t ask for ethically questionable decisions. The model has filters for harmful language and self-inflicting harm. In general, please don’t ask questions that will get this service shut down.
I was always fascinated with artificial general intelligence. In particular, I’m constantly thinking about how to generate a computer equivalent of how humans think and act. It has been difficult to make such systems because the current deep learning techniques is focusing on detection techniques like vision and NLP. Not much is focused on how humans interpret information and make decisions. So I thought about what things can be useful to the masses, yet still reflect how the human brain works.
The project I come up with is in the form of presenting a short story to the user and asking how they make decisions based on the story. When the user needs to make similar decisions in the future, there is a repository of similar stories and decisions made previously by the user, and the repository can be used to mimic the closest decision the user would have made. Although not exactly replicating the intelligence of the user, if we can make similar decisions as the user, then the end result is similar in terms of impact on their life.
Our adult lives are filled with decisions we have to make. As much as we like to, we don’t normally change how we make decisions, unless there is a life-altering event, such as a near-death experience or the loss of a family member. If we can capture how people make decisions, and able to replicate those decisions, then it’s as if we replicated the person’s behavior and values.
It may also be useful to the individual, in exposing the way that they make decisions, and asking if they like to make changes to how they are making those decisions. Pointing out the consequences of the decision-making sometimes can trigger the changes they need, without going through the life-altering experiences